Group creates guide for PICC use

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PICC

A group of international experts has created a guide to promote the appropriate use of peripherally inserted central catheters (PICCs) in adults.

The guide, called Michigan Appropriateness Guide for Intravenous Catheters (MAGIC), was published in Annals of Internal Medicine.

MAGIC is based on a review of evidence and was designed to give clinicians an easy-to-use framework to pick the right venous access device for each patient.

“PICCs, or peripherally inserted central catheters, have become especially convenient to place, and their use has gone up dramatically, as have the complications from them,” said guideline author Vineet Chopra, MD, of the University of Michigan in Ann Arbor.

“The easiest way to prevent these complications is not to place a PICC in the first place. So we set out to determine when the use of a PICC is appropriate and when other choices are the best.”

The experts reviewed 665 scenarios in which PICCs were used. Their use was deemed appropriate in 38% (n=253) of cases and inappropriate in 43% (n=288). In 19% (n=124) of cases, the experts could not agree or were unsure about whether PICC use was appropriate.

The experts said that, in patients with cancer, PICCs are appropriate for irritant or vesicant infusion, regardless of the duration of use.

On the other hand, they said PICC use is inappropriate for peripherally compatible infusions when the proposed duration of use is 5 days or fewer. And when the duration is between 6 days and 14 days, midline and ultrasonography-guided peripheral intravenous catheters should be used over PICCs.

The experts also said that nontunneled central venous catheters should be used over PICCs in critically ill patients when the duration of use is likely to be 14 days or fewer.

How MAGIC happened

The panel of 15 experts included doctors and nurses from a range of fields where PICCs and other such devices are commonly used, such as vascular nursing, critical care, infectious disease, and oncology. Also participating was a patient who had suffered complications from various intravenous devices and still lives with the consequences.

The panel evaluated the scenarios and supporting medical literature, and made its recommendations, using the RAND/UCLA Appropriateness Method.

The panel did not consider pediatric use of PICCs and other vascular access devices, but they hope their work could provide a framework for a similar effort in pediatrics.

Putting MAGIC to the test

MAGIC is getting its first test in 47 Michigan hospitals taking part in a patient safety project known as the Michigan Hospital Medicine Safety Consortium.

Researchers also plan to test ways to deploy MAGIC across the Veterans Affairs health system, working with the VA National Center for Patient Safety and the No Preventable Harms Campaign.

Even as they evaluate MAGIC’s ability to improve appropriate use of different devices and reduce complications, the team behind the new guide hopes other clinicians will begin using it.

“IV devices of all kinds are being put into patients without much thought about risks, benefits, or alternatives,” Dr Chopra said. “At the end of the day, we hope MAGIC will give providers the information they need to make a good decision for their patient, one that will render these devices appropriate and safe.”

Dr Chopra and his colleagues have also launched a website, improvepicc.com, that provides links to research on PICCs and other resources for clinicians.

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PICC

A group of international experts has created a guide to promote the appropriate use of peripherally inserted central catheters (PICCs) in adults.

The guide, called Michigan Appropriateness Guide for Intravenous Catheters (MAGIC), was published in Annals of Internal Medicine.

MAGIC is based on a review of evidence and was designed to give clinicians an easy-to-use framework to pick the right venous access device for each patient.

“PICCs, or peripherally inserted central catheters, have become especially convenient to place, and their use has gone up dramatically, as have the complications from them,” said guideline author Vineet Chopra, MD, of the University of Michigan in Ann Arbor.

“The easiest way to prevent these complications is not to place a PICC in the first place. So we set out to determine when the use of a PICC is appropriate and when other choices are the best.”

The experts reviewed 665 scenarios in which PICCs were used. Their use was deemed appropriate in 38% (n=253) of cases and inappropriate in 43% (n=288). In 19% (n=124) of cases, the experts could not agree or were unsure about whether PICC use was appropriate.

The experts said that, in patients with cancer, PICCs are appropriate for irritant or vesicant infusion, regardless of the duration of use.

On the other hand, they said PICC use is inappropriate for peripherally compatible infusions when the proposed duration of use is 5 days or fewer. And when the duration is between 6 days and 14 days, midline and ultrasonography-guided peripheral intravenous catheters should be used over PICCs.

The experts also said that nontunneled central venous catheters should be used over PICCs in critically ill patients when the duration of use is likely to be 14 days or fewer.

How MAGIC happened

The panel of 15 experts included doctors and nurses from a range of fields where PICCs and other such devices are commonly used, such as vascular nursing, critical care, infectious disease, and oncology. Also participating was a patient who had suffered complications from various intravenous devices and still lives with the consequences.

The panel evaluated the scenarios and supporting medical literature, and made its recommendations, using the RAND/UCLA Appropriateness Method.

The panel did not consider pediatric use of PICCs and other vascular access devices, but they hope their work could provide a framework for a similar effort in pediatrics.

Putting MAGIC to the test

MAGIC is getting its first test in 47 Michigan hospitals taking part in a patient safety project known as the Michigan Hospital Medicine Safety Consortium.

Researchers also plan to test ways to deploy MAGIC across the Veterans Affairs health system, working with the VA National Center for Patient Safety and the No Preventable Harms Campaign.

Even as they evaluate MAGIC’s ability to improve appropriate use of different devices and reduce complications, the team behind the new guide hopes other clinicians will begin using it.

“IV devices of all kinds are being put into patients without much thought about risks, benefits, or alternatives,” Dr Chopra said. “At the end of the day, we hope MAGIC will give providers the information they need to make a good decision for their patient, one that will render these devices appropriate and safe.”

Dr Chopra and his colleagues have also launched a website, improvepicc.com, that provides links to research on PICCs and other resources for clinicians.

PICC

A group of international experts has created a guide to promote the appropriate use of peripherally inserted central catheters (PICCs) in adults.

The guide, called Michigan Appropriateness Guide for Intravenous Catheters (MAGIC), was published in Annals of Internal Medicine.

MAGIC is based on a review of evidence and was designed to give clinicians an easy-to-use framework to pick the right venous access device for each patient.

“PICCs, or peripherally inserted central catheters, have become especially convenient to place, and their use has gone up dramatically, as have the complications from them,” said guideline author Vineet Chopra, MD, of the University of Michigan in Ann Arbor.

“The easiest way to prevent these complications is not to place a PICC in the first place. So we set out to determine when the use of a PICC is appropriate and when other choices are the best.”

The experts reviewed 665 scenarios in which PICCs were used. Their use was deemed appropriate in 38% (n=253) of cases and inappropriate in 43% (n=288). In 19% (n=124) of cases, the experts could not agree or were unsure about whether PICC use was appropriate.

The experts said that, in patients with cancer, PICCs are appropriate for irritant or vesicant infusion, regardless of the duration of use.

On the other hand, they said PICC use is inappropriate for peripherally compatible infusions when the proposed duration of use is 5 days or fewer. And when the duration is between 6 days and 14 days, midline and ultrasonography-guided peripheral intravenous catheters should be used over PICCs.

The experts also said that nontunneled central venous catheters should be used over PICCs in critically ill patients when the duration of use is likely to be 14 days or fewer.

How MAGIC happened

The panel of 15 experts included doctors and nurses from a range of fields where PICCs and other such devices are commonly used, such as vascular nursing, critical care, infectious disease, and oncology. Also participating was a patient who had suffered complications from various intravenous devices and still lives with the consequences.

The panel evaluated the scenarios and supporting medical literature, and made its recommendations, using the RAND/UCLA Appropriateness Method.

The panel did not consider pediatric use of PICCs and other vascular access devices, but they hope their work could provide a framework for a similar effort in pediatrics.

Putting MAGIC to the test

MAGIC is getting its first test in 47 Michigan hospitals taking part in a patient safety project known as the Michigan Hospital Medicine Safety Consortium.

Researchers also plan to test ways to deploy MAGIC across the Veterans Affairs health system, working with the VA National Center for Patient Safety and the No Preventable Harms Campaign.

Even as they evaluate MAGIC’s ability to improve appropriate use of different devices and reduce complications, the team behind the new guide hopes other clinicians will begin using it.

“IV devices of all kinds are being put into patients without much thought about risks, benefits, or alternatives,” Dr Chopra said. “At the end of the day, we hope MAGIC will give providers the information they need to make a good decision for their patient, one that will render these devices appropriate and safe.”

Dr Chopra and his colleagues have also launched a website, improvepicc.com, that provides links to research on PICCs and other resources for clinicians.

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Two‐Item Bedside Test for Delirium

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Preliminary development of an ultrabrief two‐item bedside test for delirium

Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]

To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]

Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.

METHODS

Study Sample and Design

We analyzed data from the 3D‐CAM validation study,[16] which prospectively enrolled participants from a large urban teaching hospital in Boston, Massachusetts, using a consecutive enrollment sampling strategy. Inclusion criteria were: (1) 75 years old, (2) admitted to general or geriatric medicine services, (3) able to communicate in English, (4) without terminal conditions, (5) expected hospital stay of 2 days, (6) not a previous study participant. Experienced clinicians screened patients for eligibility. If the patient lacked capacity to provide consent, the designated surrogate decision maker was contacted. The study was approved by the institutional review board.

Reference Standard Delirium Diagnosis

The reference standard delirium diagnosis was based on an extensive (45 minutes) face‐to‐face patient interview by experienced clinician assessors (neuropsychologists or advanced practice nurses), medical record review, and input from the nurse and family members. This comprehensive assessment included: (1) reason for hospital admission, hospital course, and presence of cognitive concerns, (2) family, social, and functional history, (3) Montreal Cognitive Assessment,[18] (4) Geriatric Depression Scale,[19] (5) medical record review including scoring of comorbidities using the Charlson index,[20] determination of functional status using the basic and Instrumental Activities of Daily Living,[21, 22] psychoactive medications administered, and (6) a family member interview to assess the patient's baseline cognitive status that included the Eight‐Item Interview to Differentiate Aging and Dementia,[23] to assess the presence of dementia. Using all of these data, an expert panel, including the clinical assessor, the study principal investigator (E.R.M.), a geriatrician, and an experienced neuropsychologist, adjudicated the final delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV) criteria. The panel also adjudicated for the presence or absence of dementia and mild cognitive impairment based on National Institute on Aging‐Alzheimer's Association (NIA‐AA) criteria.[24] This approach has been used in other delirium studies.[25]

3D‐CAM Assessments

After the reference standard assessment, the 3D‐CAM was administered by trained research assistants (RAs) who were blinded to the results of the reference standard. To reduce the likelihood of fluctuations or temporal changes, all assessments were completed between 11:00 am and 2:00 pm and for each participant, within a 2‐hour time period (for example, 11:23 am to 1:23 pm).

Statistical Analyses to Determine the Best Single‐ and Two‐Item Screeners

To determine the best single 3D‐CAM item to identify delirium, the responses of the 20 individual items in the 3D‐CAM (see Supporting Table 1 in the online version of this article) were compared to the reference standard to determine their sensitivity and specificity. Similarly, an algorithm was used to generate all unique 2‐item combinations of the 20 items (190 unique pairs), which were compared to the reference. An error, no response, or an answer of I do not know by the patient was considered a positive screen for delirium. The 2‐item screeners were considered positive if 1 or both of the items were positive. Sensitivity and specificity were calculated along with 95% confidence intervals (CIs).

Subset analyses were performed to determine sensitivity and specificity of individual items and pairs of items stratified by the patient's baseline cognitive status. Two strata were createdpatients with dementia (N=56), and patients with normal baseline cognitive status or mild cognitive impairment (MCI) (N=145). We chose to group MCI with normal for 2 reasons: (1) dementia is a well‐established and strong risk factor for delirium, whereas the evidence for MCI being a risk factor for delirium is less established and (2) to achieve adequate allocation of delirious cases in both strata. Last, we report the sensitivity of altered level of consciousness (LOC), which included lethargy, stupor, coma, and hypervigilance as a single screening item for delirium in the overall sample and by cognitive status. Analyses were conducted using commercially available software (SAS version 9.3; SAS Institute, Inc., Cary, NC).

RESULTS

Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.

Sample Characteristics (N=201)
CharacteristicN (%)
  • NOTE: Abbreviations: ADL, activities of daily living; IADL, instrumental activities of daily living; MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; SD, standard deviation.

Age, y, mean (SD)84 (5.4)
Sex, n (%) female125 (62)
White, n (%)177 (88)
Education, n (%) 
Less than high school20 (10)
High school graduate75 (38)
College plus100 (49)
Vision interfered with interview, n (%)5 (2)
Hearing interfered with interview, n (%)18 (9)
English second language n (%)10 (5)
Charlson, mean (SD)3 (2.3)
ADL, n (% impaired)110 (55)
IADL, n (% impaired)163 (81)
MCI, n (%)50 (25)
Dementia, n (%)56 (28)
Delirium, n (%)42 (21)
MoCA, mean (SD)19 (6.6)
MoCA, median (range)20 (030)

Single Item Screens

Table 2 reports the results of single‐item screens for delirium with sensitivity, the ability to correctly identify delirium when it is present by the reference standard, and specificity, the ability to correctly identify patients without delirium when it is not present by reference standard and 95% CIs. Items are listed in descending order of sensitivity; in the case of ties, the item with the higher specificity is listed first. The screening items with the highest sensitivity for delirium are Months of the year backwards, and Four digits backwards, both with a sensitivity of 83% (95% CI: 69%‐93%). Of these 2 items, Months of the year backwards had a much better specificity of 69% (95% CI: 61%‐76%), whereas Four digits backwards had a specificity of 52% (95% CI: 44%‐60%). The item What is the day of the week? had lower sensitivity at 71% (95% CI: 55%‐84%), but excellent specificity at 92% (95% CI: 87%‐96%).

Top Ten Single‐Item Screen for Delirium (N=201)
Screen ItemScreen Positive (%)cSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Number of patients with delirium=42. Abbreviations: CI, confidence interval; LR, likelihood ratio.

  • There were 20 different items and 190 possible item pairs considered.

  • Top 10 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

Months of the year backwards420.83 (0.69‐0.93)0.69 (0.61‐0.76)2.70.24
Four digits backwards560.83 (0.69‐0.93)0.52 (0.44‐0.60)1.720.32
What is the day of the week?210.71 (0.55‐0.84)0.92 (0.87‐0.96)9.460.31
What is the year?160.55 (0.39‐0.70)0.94 (0.9‐0.97)9.670.48
Have you felt confused during the past day?140.50 (0.34‐0.66)0.95 (0.9‐0.98)9.940.53
Days of the week backwards150.50 (0.34‐0.66)0.94 (0.89‐0.97)7.950.53
During the past day, did you see things that were not really there?110.45 (0.3‐0.61)0.97 (0.94‐0.99)17.980.56
Three digits backwards150.45 (0.3‐0.61)0.92 (0.87‐0.96)5.990.59
What type of place is this?90.38 (0.24‐0.54)0.99 (0.96‐1)30.290.63
During the past day, did you think you were not in the hospital?100.38 (0.24‐0.54)0.97 (0.94‐0.99)15.140.64

We then examined performance of single‐item screeners in patients with and without dementia (Table 3). In persons with dementia, the best single item was also Months of the year backwards, with a sensitivity of 89% (95% CI: 72%‐98%) and a specificity of 61% (95% CI: 41%‐78%). In persons with normal baseline cognition or MCI, the best performing single item was Four digits backwards, with sensitivity of 79% (95% CI: 49%‐95%) and specificity of 51% (95% CI: 42%‐60%). Months of the year backwards also performed well, with sensitivity of 71% (95% CI: 42%‐92%) and specificity of 71% (95% CI: 62%‐79%).

Top Three Single‐Item Screen for Delirium Stratified by Baseline Cognition
Test ItemNormal/MCI Patients (n=145)Dementia Patients (n=56)
Screen Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLRScreen Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Participants with learning problems (1) grouped with dementia and MCI participants (44) grouped with normal. Number of patients with delirium=28. Abbreviations: CI, confidence interval; LR, likelihood ratio; MCI, mild cognitive impairment.

  • Top 3 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

Months backwards330.71 (0.42‐0.92)0.71 (0.62‐0.79)2.460.4640.89 (0.72‐0.98)0.61 (0.41‐0.78)2.270.18
Four digits backwards520.79 (0.49‐0.95)0.51 (0.42‐0.60)1.610.42660.86 (0.67‐0.96)0.54 (0.34‐0.72)1.850.27
What is the day of the week?100.64 (0.35‐0.87)0.96 (0.91‐0.99)16.840.37500.75 (0.55‐0.89)0.75 (0.55‐0.89)30.33

Two‐Item Screens

Table 4 reports the results of 2‐item screens for delirium with sensitivity, specificity, and 95% CIs. Item pairs are listed in descending order of sensitivity following the same convention as in Table 2. The 2‐item screen with the highest sensitivity for delirium is the combination of What is the day of the week? and Months of the year backwards, with a sensitivity of 93% (95% CI: 81%‐99%) and specificity of 64% (95% CI: 56%‐70%). This screen had a positive and negative likelihood ratio (LR) of 2.59 and 0.11, respectively. The combination of What is the day of the week? and Four digits backwards had the same sensitivity 93% (95% CI: 81%‐99%), but lower specificity of 48% (95% CI: 40%‐56%). The combination of What type of place is this? (hospital) and Four digits backwards had a sensitivity of 90% (95% CI: 77%‐97%) and specificity of 51% (95% CI: 43%‐50%).

Top Ten Two‐Item Screen for Delirium (N=201)
Screen Item 1Screen Item 2Screen Positive (%)cSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Number of patients with delirium=42. Abbreviations: CI, confidence interval; LR, likelihood ratio.

  • There were 20 different items and 190 possible item pairs considered.

  • Top 10 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

What is the day of the week?Months backwards480.93 (0.81‐0.99)0.64 (0.56‐0.70)2.590.11
What is the day of the week?Four digits backwards600.93 (0.81‐0.99)0.48 (0.4‐0.56)1.80.15
Four digits backwardsMonths backwards650.93 (0.81‐0.99)0.42 (0.34‐0.50)1.60.17
What type of place is this?Four digits backwards580.90 (0.77‐0.97)0.51 (0.43‐0.50)1.840.19
What is the year?Four digits backwards590.9 (0.77‐0.97)0.5 (0.42‐0.5)1.800.19
What is the day of the week?Three digits backwards300.88 (0.74‐0.96)0.86 (0.79‐0.90)6.090.14
What is the year?Months backwards440.88 (0.74‐0.96)0.68 (0.6‐0.75)2.750.18
What type of place is this?Months backwards430.86 (0.71‐0.95)0.69 (0.61‐0.70)2.730.21
During the past day, did you think you were not in the hospital?Months backwards430.86 (0.71‐0.95)0.69 (0.61‐0.70)2.730.21
Days of the week backwardsMonths backwards430.86 (0.71‐0.95)0.68 (0.6‐0.75)2.670.21

When subjects were stratified by baseline cognition, the best 2‐item screens for normal and MCI patients was What is the day of the week? and Four digits backwards, with 93% sensitivity (95% CI: 66%‐100%) and 50% specificity (95% CI: 42%‐59%). The best pair of items for patients with dementia (Table 5) was the same as the overall sample, What is the day of the week? and Months of the year backwards, but its performance differed with a higher sensitivity of 96% (95% CI: 82%‐100%) and lower specificity of 43% (95% CI: 24%‐63%). This same pair of items had 86% sensitivity (95% CI: 57%‐98%) and 69% (95% CI: 60%‐77%) specificity for persons with either normal cognition or MCI.

Top Three Two‐Item Screen for Normal/MCI and Persons With Dementia
Test Item 1Test Item 2Normal/MCI Patients (n=145)Dementia Patients (n=56) 
Item Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLRItem Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Participants with learning problems (1) grouped with dementia and MCI participants (44) grouped with normal. Number of patients with delirium=28. Abbreviations: CI, confidence interval; LR, likelihood ratio; MCI, mild cognitive impairment.

  • Top 3 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

What is the day of the week?Months backwards360.86 (0.57‐0.98)0.69 (0.60‐0.77)2.740.21770.96 (0.82‐1)0.43 (0.24‐0.63)1.690.08
What is the day of the week?Four digits backwards540.93 (0.66‐1)0.5 (0.42‐0.59)1.870.14770.93 (0.76‐0.99)0.39 (0.22‐0.59)1.530.18
Four digits backwardsMonths backwards610.93 (0.66‐1)0.43 (0.34‐0.52)1.620.17770.93 (0.76‐0.99)0.39 (0.22‐0.59)1.530.18

Altered Level of Consciousness as a Screener for Delirium

Altered level of consciousness (ALOC) was uncommon in our sample, with an overall prevalence of 10/201 (4.9%). When examined as a screening item for delirium, ALOC had very poor sensitivity of 19% (95% CI: 9%‐34%) but had excellent specificity 99% (95% CI: 96%‐100%). Altered LOC also demonstrated poor screening performance when stratified by cognitive status, with a sensitivity of 14% in the normal and MCI group (95% CI: 2%‐43%) and sensitivity of 21% (95% CI: 8%‐41%) in persons with dementia.

Positive and Negative Predictive Values

Although we focused on sensitivity and specificity in evaluating 1‐ and 2‐item screeners, we also examined positive and negative predictive values. These values will vary depending on the overall prevalence of delirium, which was 21% in this dataset. The best 1‐item screener, Months of the year backwards, had a positive predictive value of 31% and negative predictive value of 94%. The best 2‐item screener, Months of the year backwards with What is the day of the week?, had a positive predictive value of 41% and negative predictive value of 97% (see Supporting Tables 2 and 3 in the online version of this article) LRs for the items are in Tables 2 through 5.

DISCUSSION

Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.

Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.

Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.

Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.

It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]

Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.

In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.

Disclosures

Author contributionsD.M.F. conceived the study idea, participated in its design and coordination, and drafted the initial manuscript. S.K.I. contributed to the study design and conceptualization, supervision, funding, preliminary analysis, and interpretation of the data, and critical revision of the manuscript. J.G. conducted the analysis for the study and critically revised the manuscript. L.N. supervised the analysis for the study and critically revised the manuscript. R.J. contributed to the study design and critical revision of the manuscript. J.S.S. critically revised the manuscript. E.R.M. obtained funding for the study, supervised all data collection, assisted in drafting and critically revising the manuscript, and contributed to the conceptualization, design, and supervision of the study. All authors have seen and agree with the contents of the manuscript.

This work was supported by the National Institute of Aging grant number R01AG030618 and K24AG035075 to Dr. Marcantonio. Dr. Inouye's time was supported in part by grants P01AG031720, R01AG044518, and K07AG041835 from the National Institute on Aging. Dr. Inouye holds the Milton and Shirley F. Levy Family Chair (Hebrew Senior Life/Harvard Medical School). Dr. Fick is partially supported from National Institute of Nursing Research grant number R01 NR011042. Dr. Saczynski was supported in part by funding from the National Institute on Aging (K01AG33643) and from the National Heart Lung and Blood Institute (U01HL105268). The funding agencies had no role and the authors retained full autonomy in the preparation of this article. All authors and coauthors have no financial or nonfinancial conflicts of interest to disclose regarding this article.

This article was presented at the Presidential Poster Session at the American Geriatrics Society 2014 Annual Meeting in Orlando, Florida, May 14, 2014.

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References
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Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]

To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]

Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.

METHODS

Study Sample and Design

We analyzed data from the 3D‐CAM validation study,[16] which prospectively enrolled participants from a large urban teaching hospital in Boston, Massachusetts, using a consecutive enrollment sampling strategy. Inclusion criteria were: (1) 75 years old, (2) admitted to general or geriatric medicine services, (3) able to communicate in English, (4) without terminal conditions, (5) expected hospital stay of 2 days, (6) not a previous study participant. Experienced clinicians screened patients for eligibility. If the patient lacked capacity to provide consent, the designated surrogate decision maker was contacted. The study was approved by the institutional review board.

Reference Standard Delirium Diagnosis

The reference standard delirium diagnosis was based on an extensive (45 minutes) face‐to‐face patient interview by experienced clinician assessors (neuropsychologists or advanced practice nurses), medical record review, and input from the nurse and family members. This comprehensive assessment included: (1) reason for hospital admission, hospital course, and presence of cognitive concerns, (2) family, social, and functional history, (3) Montreal Cognitive Assessment,[18] (4) Geriatric Depression Scale,[19] (5) medical record review including scoring of comorbidities using the Charlson index,[20] determination of functional status using the basic and Instrumental Activities of Daily Living,[21, 22] psychoactive medications administered, and (6) a family member interview to assess the patient's baseline cognitive status that included the Eight‐Item Interview to Differentiate Aging and Dementia,[23] to assess the presence of dementia. Using all of these data, an expert panel, including the clinical assessor, the study principal investigator (E.R.M.), a geriatrician, and an experienced neuropsychologist, adjudicated the final delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV) criteria. The panel also adjudicated for the presence or absence of dementia and mild cognitive impairment based on National Institute on Aging‐Alzheimer's Association (NIA‐AA) criteria.[24] This approach has been used in other delirium studies.[25]

3D‐CAM Assessments

After the reference standard assessment, the 3D‐CAM was administered by trained research assistants (RAs) who were blinded to the results of the reference standard. To reduce the likelihood of fluctuations or temporal changes, all assessments were completed between 11:00 am and 2:00 pm and for each participant, within a 2‐hour time period (for example, 11:23 am to 1:23 pm).

Statistical Analyses to Determine the Best Single‐ and Two‐Item Screeners

To determine the best single 3D‐CAM item to identify delirium, the responses of the 20 individual items in the 3D‐CAM (see Supporting Table 1 in the online version of this article) were compared to the reference standard to determine their sensitivity and specificity. Similarly, an algorithm was used to generate all unique 2‐item combinations of the 20 items (190 unique pairs), which were compared to the reference. An error, no response, or an answer of I do not know by the patient was considered a positive screen for delirium. The 2‐item screeners were considered positive if 1 or both of the items were positive. Sensitivity and specificity were calculated along with 95% confidence intervals (CIs).

Subset analyses were performed to determine sensitivity and specificity of individual items and pairs of items stratified by the patient's baseline cognitive status. Two strata were createdpatients with dementia (N=56), and patients with normal baseline cognitive status or mild cognitive impairment (MCI) (N=145). We chose to group MCI with normal for 2 reasons: (1) dementia is a well‐established and strong risk factor for delirium, whereas the evidence for MCI being a risk factor for delirium is less established and (2) to achieve adequate allocation of delirious cases in both strata. Last, we report the sensitivity of altered level of consciousness (LOC), which included lethargy, stupor, coma, and hypervigilance as a single screening item for delirium in the overall sample and by cognitive status. Analyses were conducted using commercially available software (SAS version 9.3; SAS Institute, Inc., Cary, NC).

RESULTS

Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.

Sample Characteristics (N=201)
CharacteristicN (%)
  • NOTE: Abbreviations: ADL, activities of daily living; IADL, instrumental activities of daily living; MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; SD, standard deviation.

Age, y, mean (SD)84 (5.4)
Sex, n (%) female125 (62)
White, n (%)177 (88)
Education, n (%) 
Less than high school20 (10)
High school graduate75 (38)
College plus100 (49)
Vision interfered with interview, n (%)5 (2)
Hearing interfered with interview, n (%)18 (9)
English second language n (%)10 (5)
Charlson, mean (SD)3 (2.3)
ADL, n (% impaired)110 (55)
IADL, n (% impaired)163 (81)
MCI, n (%)50 (25)
Dementia, n (%)56 (28)
Delirium, n (%)42 (21)
MoCA, mean (SD)19 (6.6)
MoCA, median (range)20 (030)

Single Item Screens

Table 2 reports the results of single‐item screens for delirium with sensitivity, the ability to correctly identify delirium when it is present by the reference standard, and specificity, the ability to correctly identify patients without delirium when it is not present by reference standard and 95% CIs. Items are listed in descending order of sensitivity; in the case of ties, the item with the higher specificity is listed first. The screening items with the highest sensitivity for delirium are Months of the year backwards, and Four digits backwards, both with a sensitivity of 83% (95% CI: 69%‐93%). Of these 2 items, Months of the year backwards had a much better specificity of 69% (95% CI: 61%‐76%), whereas Four digits backwards had a specificity of 52% (95% CI: 44%‐60%). The item What is the day of the week? had lower sensitivity at 71% (95% CI: 55%‐84%), but excellent specificity at 92% (95% CI: 87%‐96%).

Top Ten Single‐Item Screen for Delirium (N=201)
Screen ItemScreen Positive (%)cSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Number of patients with delirium=42. Abbreviations: CI, confidence interval; LR, likelihood ratio.

  • There were 20 different items and 190 possible item pairs considered.

  • Top 10 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

Months of the year backwards420.83 (0.69‐0.93)0.69 (0.61‐0.76)2.70.24
Four digits backwards560.83 (0.69‐0.93)0.52 (0.44‐0.60)1.720.32
What is the day of the week?210.71 (0.55‐0.84)0.92 (0.87‐0.96)9.460.31
What is the year?160.55 (0.39‐0.70)0.94 (0.9‐0.97)9.670.48
Have you felt confused during the past day?140.50 (0.34‐0.66)0.95 (0.9‐0.98)9.940.53
Days of the week backwards150.50 (0.34‐0.66)0.94 (0.89‐0.97)7.950.53
During the past day, did you see things that were not really there?110.45 (0.3‐0.61)0.97 (0.94‐0.99)17.980.56
Three digits backwards150.45 (0.3‐0.61)0.92 (0.87‐0.96)5.990.59
What type of place is this?90.38 (0.24‐0.54)0.99 (0.96‐1)30.290.63
During the past day, did you think you were not in the hospital?100.38 (0.24‐0.54)0.97 (0.94‐0.99)15.140.64

We then examined performance of single‐item screeners in patients with and without dementia (Table 3). In persons with dementia, the best single item was also Months of the year backwards, with a sensitivity of 89% (95% CI: 72%‐98%) and a specificity of 61% (95% CI: 41%‐78%). In persons with normal baseline cognition or MCI, the best performing single item was Four digits backwards, with sensitivity of 79% (95% CI: 49%‐95%) and specificity of 51% (95% CI: 42%‐60%). Months of the year backwards also performed well, with sensitivity of 71% (95% CI: 42%‐92%) and specificity of 71% (95% CI: 62%‐79%).

Top Three Single‐Item Screen for Delirium Stratified by Baseline Cognition
Test ItemNormal/MCI Patients (n=145)Dementia Patients (n=56)
Screen Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLRScreen Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Participants with learning problems (1) grouped with dementia and MCI participants (44) grouped with normal. Number of patients with delirium=28. Abbreviations: CI, confidence interval; LR, likelihood ratio; MCI, mild cognitive impairment.

  • Top 3 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

Months backwards330.71 (0.42‐0.92)0.71 (0.62‐0.79)2.460.4640.89 (0.72‐0.98)0.61 (0.41‐0.78)2.270.18
Four digits backwards520.79 (0.49‐0.95)0.51 (0.42‐0.60)1.610.42660.86 (0.67‐0.96)0.54 (0.34‐0.72)1.850.27
What is the day of the week?100.64 (0.35‐0.87)0.96 (0.91‐0.99)16.840.37500.75 (0.55‐0.89)0.75 (0.55‐0.89)30.33

Two‐Item Screens

Table 4 reports the results of 2‐item screens for delirium with sensitivity, specificity, and 95% CIs. Item pairs are listed in descending order of sensitivity following the same convention as in Table 2. The 2‐item screen with the highest sensitivity for delirium is the combination of What is the day of the week? and Months of the year backwards, with a sensitivity of 93% (95% CI: 81%‐99%) and specificity of 64% (95% CI: 56%‐70%). This screen had a positive and negative likelihood ratio (LR) of 2.59 and 0.11, respectively. The combination of What is the day of the week? and Four digits backwards had the same sensitivity 93% (95% CI: 81%‐99%), but lower specificity of 48% (95% CI: 40%‐56%). The combination of What type of place is this? (hospital) and Four digits backwards had a sensitivity of 90% (95% CI: 77%‐97%) and specificity of 51% (95% CI: 43%‐50%).

Top Ten Two‐Item Screen for Delirium (N=201)
Screen Item 1Screen Item 2Screen Positive (%)cSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Number of patients with delirium=42. Abbreviations: CI, confidence interval; LR, likelihood ratio.

  • There were 20 different items and 190 possible item pairs considered.

  • Top 10 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

What is the day of the week?Months backwards480.93 (0.81‐0.99)0.64 (0.56‐0.70)2.590.11
What is the day of the week?Four digits backwards600.93 (0.81‐0.99)0.48 (0.4‐0.56)1.80.15
Four digits backwardsMonths backwards650.93 (0.81‐0.99)0.42 (0.34‐0.50)1.60.17
What type of place is this?Four digits backwards580.90 (0.77‐0.97)0.51 (0.43‐0.50)1.840.19
What is the year?Four digits backwards590.9 (0.77‐0.97)0.5 (0.42‐0.5)1.800.19
What is the day of the week?Three digits backwards300.88 (0.74‐0.96)0.86 (0.79‐0.90)6.090.14
What is the year?Months backwards440.88 (0.74‐0.96)0.68 (0.6‐0.75)2.750.18
What type of place is this?Months backwards430.86 (0.71‐0.95)0.69 (0.61‐0.70)2.730.21
During the past day, did you think you were not in the hospital?Months backwards430.86 (0.71‐0.95)0.69 (0.61‐0.70)2.730.21
Days of the week backwardsMonths backwards430.86 (0.71‐0.95)0.68 (0.6‐0.75)2.670.21

When subjects were stratified by baseline cognition, the best 2‐item screens for normal and MCI patients was What is the day of the week? and Four digits backwards, with 93% sensitivity (95% CI: 66%‐100%) and 50% specificity (95% CI: 42%‐59%). The best pair of items for patients with dementia (Table 5) was the same as the overall sample, What is the day of the week? and Months of the year backwards, but its performance differed with a higher sensitivity of 96% (95% CI: 82%‐100%) and lower specificity of 43% (95% CI: 24%‐63%). This same pair of items had 86% sensitivity (95% CI: 57%‐98%) and 69% (95% CI: 60%‐77%) specificity for persons with either normal cognition or MCI.

Top Three Two‐Item Screen for Normal/MCI and Persons With Dementia
Test Item 1Test Item 2Normal/MCI Patients (n=145)Dementia Patients (n=56) 
Item Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLRItem Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Participants with learning problems (1) grouped with dementia and MCI participants (44) grouped with normal. Number of patients with delirium=28. Abbreviations: CI, confidence interval; LR, likelihood ratio; MCI, mild cognitive impairment.

  • Top 3 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

What is the day of the week?Months backwards360.86 (0.57‐0.98)0.69 (0.60‐0.77)2.740.21770.96 (0.82‐1)0.43 (0.24‐0.63)1.690.08
What is the day of the week?Four digits backwards540.93 (0.66‐1)0.5 (0.42‐0.59)1.870.14770.93 (0.76‐0.99)0.39 (0.22‐0.59)1.530.18
Four digits backwardsMonths backwards610.93 (0.66‐1)0.43 (0.34‐0.52)1.620.17770.93 (0.76‐0.99)0.39 (0.22‐0.59)1.530.18

Altered Level of Consciousness as a Screener for Delirium

Altered level of consciousness (ALOC) was uncommon in our sample, with an overall prevalence of 10/201 (4.9%). When examined as a screening item for delirium, ALOC had very poor sensitivity of 19% (95% CI: 9%‐34%) but had excellent specificity 99% (95% CI: 96%‐100%). Altered LOC also demonstrated poor screening performance when stratified by cognitive status, with a sensitivity of 14% in the normal and MCI group (95% CI: 2%‐43%) and sensitivity of 21% (95% CI: 8%‐41%) in persons with dementia.

Positive and Negative Predictive Values

Although we focused on sensitivity and specificity in evaluating 1‐ and 2‐item screeners, we also examined positive and negative predictive values. These values will vary depending on the overall prevalence of delirium, which was 21% in this dataset. The best 1‐item screener, Months of the year backwards, had a positive predictive value of 31% and negative predictive value of 94%. The best 2‐item screener, Months of the year backwards with What is the day of the week?, had a positive predictive value of 41% and negative predictive value of 97% (see Supporting Tables 2 and 3 in the online version of this article) LRs for the items are in Tables 2 through 5.

DISCUSSION

Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.

Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.

Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.

Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.

It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]

Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.

In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.

Disclosures

Author contributionsD.M.F. conceived the study idea, participated in its design and coordination, and drafted the initial manuscript. S.K.I. contributed to the study design and conceptualization, supervision, funding, preliminary analysis, and interpretation of the data, and critical revision of the manuscript. J.G. conducted the analysis for the study and critically revised the manuscript. L.N. supervised the analysis for the study and critically revised the manuscript. R.J. contributed to the study design and critical revision of the manuscript. J.S.S. critically revised the manuscript. E.R.M. obtained funding for the study, supervised all data collection, assisted in drafting and critically revising the manuscript, and contributed to the conceptualization, design, and supervision of the study. All authors have seen and agree with the contents of the manuscript.

This work was supported by the National Institute of Aging grant number R01AG030618 and K24AG035075 to Dr. Marcantonio. Dr. Inouye's time was supported in part by grants P01AG031720, R01AG044518, and K07AG041835 from the National Institute on Aging. Dr. Inouye holds the Milton and Shirley F. Levy Family Chair (Hebrew Senior Life/Harvard Medical School). Dr. Fick is partially supported from National Institute of Nursing Research grant number R01 NR011042. Dr. Saczynski was supported in part by funding from the National Institute on Aging (K01AG33643) and from the National Heart Lung and Blood Institute (U01HL105268). The funding agencies had no role and the authors retained full autonomy in the preparation of this article. All authors and coauthors have no financial or nonfinancial conflicts of interest to disclose regarding this article.

This article was presented at the Presidential Poster Session at the American Geriatrics Society 2014 Annual Meeting in Orlando, Florida, May 14, 2014.

Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]

To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]

Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.

METHODS

Study Sample and Design

We analyzed data from the 3D‐CAM validation study,[16] which prospectively enrolled participants from a large urban teaching hospital in Boston, Massachusetts, using a consecutive enrollment sampling strategy. Inclusion criteria were: (1) 75 years old, (2) admitted to general or geriatric medicine services, (3) able to communicate in English, (4) without terminal conditions, (5) expected hospital stay of 2 days, (6) not a previous study participant. Experienced clinicians screened patients for eligibility. If the patient lacked capacity to provide consent, the designated surrogate decision maker was contacted. The study was approved by the institutional review board.

Reference Standard Delirium Diagnosis

The reference standard delirium diagnosis was based on an extensive (45 minutes) face‐to‐face patient interview by experienced clinician assessors (neuropsychologists or advanced practice nurses), medical record review, and input from the nurse and family members. This comprehensive assessment included: (1) reason for hospital admission, hospital course, and presence of cognitive concerns, (2) family, social, and functional history, (3) Montreal Cognitive Assessment,[18] (4) Geriatric Depression Scale,[19] (5) medical record review including scoring of comorbidities using the Charlson index,[20] determination of functional status using the basic and Instrumental Activities of Daily Living,[21, 22] psychoactive medications administered, and (6) a family member interview to assess the patient's baseline cognitive status that included the Eight‐Item Interview to Differentiate Aging and Dementia,[23] to assess the presence of dementia. Using all of these data, an expert panel, including the clinical assessor, the study principal investigator (E.R.M.), a geriatrician, and an experienced neuropsychologist, adjudicated the final delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV) criteria. The panel also adjudicated for the presence or absence of dementia and mild cognitive impairment based on National Institute on Aging‐Alzheimer's Association (NIA‐AA) criteria.[24] This approach has been used in other delirium studies.[25]

3D‐CAM Assessments

After the reference standard assessment, the 3D‐CAM was administered by trained research assistants (RAs) who were blinded to the results of the reference standard. To reduce the likelihood of fluctuations or temporal changes, all assessments were completed between 11:00 am and 2:00 pm and for each participant, within a 2‐hour time period (for example, 11:23 am to 1:23 pm).

Statistical Analyses to Determine the Best Single‐ and Two‐Item Screeners

To determine the best single 3D‐CAM item to identify delirium, the responses of the 20 individual items in the 3D‐CAM (see Supporting Table 1 in the online version of this article) were compared to the reference standard to determine their sensitivity and specificity. Similarly, an algorithm was used to generate all unique 2‐item combinations of the 20 items (190 unique pairs), which were compared to the reference. An error, no response, or an answer of I do not know by the patient was considered a positive screen for delirium. The 2‐item screeners were considered positive if 1 or both of the items were positive. Sensitivity and specificity were calculated along with 95% confidence intervals (CIs).

Subset analyses were performed to determine sensitivity and specificity of individual items and pairs of items stratified by the patient's baseline cognitive status. Two strata were createdpatients with dementia (N=56), and patients with normal baseline cognitive status or mild cognitive impairment (MCI) (N=145). We chose to group MCI with normal for 2 reasons: (1) dementia is a well‐established and strong risk factor for delirium, whereas the evidence for MCI being a risk factor for delirium is less established and (2) to achieve adequate allocation of delirious cases in both strata. Last, we report the sensitivity of altered level of consciousness (LOC), which included lethargy, stupor, coma, and hypervigilance as a single screening item for delirium in the overall sample and by cognitive status. Analyses were conducted using commercially available software (SAS version 9.3; SAS Institute, Inc., Cary, NC).

RESULTS

Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.

Sample Characteristics (N=201)
CharacteristicN (%)
  • NOTE: Abbreviations: ADL, activities of daily living; IADL, instrumental activities of daily living; MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; SD, standard deviation.

Age, y, mean (SD)84 (5.4)
Sex, n (%) female125 (62)
White, n (%)177 (88)
Education, n (%) 
Less than high school20 (10)
High school graduate75 (38)
College plus100 (49)
Vision interfered with interview, n (%)5 (2)
Hearing interfered with interview, n (%)18 (9)
English second language n (%)10 (5)
Charlson, mean (SD)3 (2.3)
ADL, n (% impaired)110 (55)
IADL, n (% impaired)163 (81)
MCI, n (%)50 (25)
Dementia, n (%)56 (28)
Delirium, n (%)42 (21)
MoCA, mean (SD)19 (6.6)
MoCA, median (range)20 (030)

Single Item Screens

Table 2 reports the results of single‐item screens for delirium with sensitivity, the ability to correctly identify delirium when it is present by the reference standard, and specificity, the ability to correctly identify patients without delirium when it is not present by reference standard and 95% CIs. Items are listed in descending order of sensitivity; in the case of ties, the item with the higher specificity is listed first. The screening items with the highest sensitivity for delirium are Months of the year backwards, and Four digits backwards, both with a sensitivity of 83% (95% CI: 69%‐93%). Of these 2 items, Months of the year backwards had a much better specificity of 69% (95% CI: 61%‐76%), whereas Four digits backwards had a specificity of 52% (95% CI: 44%‐60%). The item What is the day of the week? had lower sensitivity at 71% (95% CI: 55%‐84%), but excellent specificity at 92% (95% CI: 87%‐96%).

Top Ten Single‐Item Screen for Delirium (N=201)
Screen ItemScreen Positive (%)cSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Number of patients with delirium=42. Abbreviations: CI, confidence interval; LR, likelihood ratio.

  • There were 20 different items and 190 possible item pairs considered.

  • Top 10 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

Months of the year backwards420.83 (0.69‐0.93)0.69 (0.61‐0.76)2.70.24
Four digits backwards560.83 (0.69‐0.93)0.52 (0.44‐0.60)1.720.32
What is the day of the week?210.71 (0.55‐0.84)0.92 (0.87‐0.96)9.460.31
What is the year?160.55 (0.39‐0.70)0.94 (0.9‐0.97)9.670.48
Have you felt confused during the past day?140.50 (0.34‐0.66)0.95 (0.9‐0.98)9.940.53
Days of the week backwards150.50 (0.34‐0.66)0.94 (0.89‐0.97)7.950.53
During the past day, did you see things that were not really there?110.45 (0.3‐0.61)0.97 (0.94‐0.99)17.980.56
Three digits backwards150.45 (0.3‐0.61)0.92 (0.87‐0.96)5.990.59
What type of place is this?90.38 (0.24‐0.54)0.99 (0.96‐1)30.290.63
During the past day, did you think you were not in the hospital?100.38 (0.24‐0.54)0.97 (0.94‐0.99)15.140.64

We then examined performance of single‐item screeners in patients with and without dementia (Table 3). In persons with dementia, the best single item was also Months of the year backwards, with a sensitivity of 89% (95% CI: 72%‐98%) and a specificity of 61% (95% CI: 41%‐78%). In persons with normal baseline cognition or MCI, the best performing single item was Four digits backwards, with sensitivity of 79% (95% CI: 49%‐95%) and specificity of 51% (95% CI: 42%‐60%). Months of the year backwards also performed well, with sensitivity of 71% (95% CI: 42%‐92%) and specificity of 71% (95% CI: 62%‐79%).

Top Three Single‐Item Screen for Delirium Stratified by Baseline Cognition
Test ItemNormal/MCI Patients (n=145)Dementia Patients (n=56)
Screen Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLRScreen Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Participants with learning problems (1) grouped with dementia and MCI participants (44) grouped with normal. Number of patients with delirium=28. Abbreviations: CI, confidence interval; LR, likelihood ratio; MCI, mild cognitive impairment.

  • Top 3 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

Months backwards330.71 (0.42‐0.92)0.71 (0.62‐0.79)2.460.4640.89 (0.72‐0.98)0.61 (0.41‐0.78)2.270.18
Four digits backwards520.79 (0.49‐0.95)0.51 (0.42‐0.60)1.610.42660.86 (0.67‐0.96)0.54 (0.34‐0.72)1.850.27
What is the day of the week?100.64 (0.35‐0.87)0.96 (0.91‐0.99)16.840.37500.75 (0.55‐0.89)0.75 (0.55‐0.89)30.33

Two‐Item Screens

Table 4 reports the results of 2‐item screens for delirium with sensitivity, specificity, and 95% CIs. Item pairs are listed in descending order of sensitivity following the same convention as in Table 2. The 2‐item screen with the highest sensitivity for delirium is the combination of What is the day of the week? and Months of the year backwards, with a sensitivity of 93% (95% CI: 81%‐99%) and specificity of 64% (95% CI: 56%‐70%). This screen had a positive and negative likelihood ratio (LR) of 2.59 and 0.11, respectively. The combination of What is the day of the week? and Four digits backwards had the same sensitivity 93% (95% CI: 81%‐99%), but lower specificity of 48% (95% CI: 40%‐56%). The combination of What type of place is this? (hospital) and Four digits backwards had a sensitivity of 90% (95% CI: 77%‐97%) and specificity of 51% (95% CI: 43%‐50%).

Top Ten Two‐Item Screen for Delirium (N=201)
Screen Item 1Screen Item 2Screen Positive (%)cSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Number of patients with delirium=42. Abbreviations: CI, confidence interval; LR, likelihood ratio.

  • There were 20 different items and 190 possible item pairs considered.

  • Top 10 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

What is the day of the week?Months backwards480.93 (0.81‐0.99)0.64 (0.56‐0.70)2.590.11
What is the day of the week?Four digits backwards600.93 (0.81‐0.99)0.48 (0.4‐0.56)1.80.15
Four digits backwardsMonths backwards650.93 (0.81‐0.99)0.42 (0.34‐0.50)1.60.17
What type of place is this?Four digits backwards580.90 (0.77‐0.97)0.51 (0.43‐0.50)1.840.19
What is the year?Four digits backwards590.9 (0.77‐0.97)0.5 (0.42‐0.5)1.800.19
What is the day of the week?Three digits backwards300.88 (0.74‐0.96)0.86 (0.79‐0.90)6.090.14
What is the year?Months backwards440.88 (0.74‐0.96)0.68 (0.6‐0.75)2.750.18
What type of place is this?Months backwards430.86 (0.71‐0.95)0.69 (0.61‐0.70)2.730.21
During the past day, did you think you were not in the hospital?Months backwards430.86 (0.71‐0.95)0.69 (0.61‐0.70)2.730.21
Days of the week backwardsMonths backwards430.86 (0.71‐0.95)0.68 (0.6‐0.75)2.670.21

When subjects were stratified by baseline cognition, the best 2‐item screens for normal and MCI patients was What is the day of the week? and Four digits backwards, with 93% sensitivity (95% CI: 66%‐100%) and 50% specificity (95% CI: 42%‐59%). The best pair of items for patients with dementia (Table 5) was the same as the overall sample, What is the day of the week? and Months of the year backwards, but its performance differed with a higher sensitivity of 96% (95% CI: 82%‐100%) and lower specificity of 43% (95% CI: 24%‐63%). This same pair of items had 86% sensitivity (95% CI: 57%‐98%) and 69% (95% CI: 60%‐77%) specificity for persons with either normal cognition or MCI.

Top Three Two‐Item Screen for Normal/MCI and Persons With Dementia
Test Item 1Test Item 2Normal/MCI Patients (n=145)Dementia Patients (n=56) 
Item Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLRItem Positive (%)bSensitivity (95% CI)Specificity (95% CI)LRLR
  • NOTE: Participants with learning problems (1) grouped with dementia and MCI participants (44) grouped with normal. Number of patients with delirium=28. Abbreviations: CI, confidence interval; LR, likelihood ratio; MCI, mild cognitive impairment.

  • Top 3 items: our primary criterion for determining this was sensitivity, with a secondary criterion of specificity in the case of ties. Items are listed in descending order on this basis.

  • Screen positive: error, do not know, or no response.

What is the day of the week?Months backwards360.86 (0.57‐0.98)0.69 (0.60‐0.77)2.740.21770.96 (0.82‐1)0.43 (0.24‐0.63)1.690.08
What is the day of the week?Four digits backwards540.93 (0.66‐1)0.5 (0.42‐0.59)1.870.14770.93 (0.76‐0.99)0.39 (0.22‐0.59)1.530.18
Four digits backwardsMonths backwards610.93 (0.66‐1)0.43 (0.34‐0.52)1.620.17770.93 (0.76‐0.99)0.39 (0.22‐0.59)1.530.18

Altered Level of Consciousness as a Screener for Delirium

Altered level of consciousness (ALOC) was uncommon in our sample, with an overall prevalence of 10/201 (4.9%). When examined as a screening item for delirium, ALOC had very poor sensitivity of 19% (95% CI: 9%‐34%) but had excellent specificity 99% (95% CI: 96%‐100%). Altered LOC also demonstrated poor screening performance when stratified by cognitive status, with a sensitivity of 14% in the normal and MCI group (95% CI: 2%‐43%) and sensitivity of 21% (95% CI: 8%‐41%) in persons with dementia.

Positive and Negative Predictive Values

Although we focused on sensitivity and specificity in evaluating 1‐ and 2‐item screeners, we also examined positive and negative predictive values. These values will vary depending on the overall prevalence of delirium, which was 21% in this dataset. The best 1‐item screener, Months of the year backwards, had a positive predictive value of 31% and negative predictive value of 94%. The best 2‐item screener, Months of the year backwards with What is the day of the week?, had a positive predictive value of 41% and negative predictive value of 97% (see Supporting Tables 2 and 3 in the online version of this article) LRs for the items are in Tables 2 through 5.

DISCUSSION

Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.

Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.

Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.

Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.

It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]

Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.

In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.

Disclosures

Author contributionsD.M.F. conceived the study idea, participated in its design and coordination, and drafted the initial manuscript. S.K.I. contributed to the study design and conceptualization, supervision, funding, preliminary analysis, and interpretation of the data, and critical revision of the manuscript. J.G. conducted the analysis for the study and critically revised the manuscript. L.N. supervised the analysis for the study and critically revised the manuscript. R.J. contributed to the study design and critical revision of the manuscript. J.S.S. critically revised the manuscript. E.R.M. obtained funding for the study, supervised all data collection, assisted in drafting and critically revising the manuscript, and contributed to the conceptualization, design, and supervision of the study. All authors have seen and agree with the contents of the manuscript.

This work was supported by the National Institute of Aging grant number R01AG030618 and K24AG035075 to Dr. Marcantonio. Dr. Inouye's time was supported in part by grants P01AG031720, R01AG044518, and K07AG041835 from the National Institute on Aging. Dr. Inouye holds the Milton and Shirley F. Levy Family Chair (Hebrew Senior Life/Harvard Medical School). Dr. Fick is partially supported from National Institute of Nursing Research grant number R01 NR011042. Dr. Saczynski was supported in part by funding from the National Institute on Aging (K01AG33643) and from the National Heart Lung and Blood Institute (U01HL105268). The funding agencies had no role and the authors retained full autonomy in the preparation of this article. All authors and coauthors have no financial or nonfinancial conflicts of interest to disclose regarding this article.

This article was presented at the Presidential Poster Session at the American Geriatrics Society 2014 Annual Meeting in Orlando, Florida, May 14, 2014.

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  4. Fick DM, Steis MR, Waller JL, Inouye SK. Delirium superimposed on dementia is associated with prolonged length of stay and poor outcomes in hospitalized older adults. J Hosp Med. 2013;8(9):500505.
  5. Leslie DL, Marcantonio ER, Zhang Y, Leo‐Summers L, Inouye SK. One‐year health care costs associated with delirium in the elderly population. Arch Intern Med. 2008;168(1):2732.
  6. Leslie DL, Inouye SK. The importance of delirium: Economic and societal costs. J Am Geriatr Soc. 2011;59(suppl 2):S241S243.
  7. Marcantonio ER. Delirium. Ann Intern Med. 2011;154(11):ITC6.
  8. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50.
  9. Rice KL, Bennett MJ, Clesi T, Linville L. Mixed‐methods approach to understanding nurses' clinical reasoning in recognizing delirium in hospitalized older adults. J Contin Educ Nurs. 2014;45:1–13.
  10. Yanamadala M, Wieland D, Heflin MT. Educational interventions to improve recognition of delirium: a systematic review. J Am Geriatr Soc. 2013;61(11):19831993.
  11. Steis MR, Fick DM. Delirium superimposed on dementia: accuracy of nurse documentation. J Gerontol Nurs. 2012;38(1):3242.
  12. Lemiengre J, Nelis T, Joosten E, et al. Detection of delirium by bedside nurses using the confusion assessment method. J Am Geriatr Soc. 2006;54:685689.
  13. Milisen K, Foreman MD, Wouters B, et al. Documentation of delirium in elderly patients with hip fracture. J Gerontol Nurs. 2002;28(11):2329.
  14. Kales HC, Kamholz BA, Visnic SG, Blow FC. Recorded delirium in a national sample of elderly inpatients: potential implications for recognition. J Geriatr Psychiatry Neurol. 2003;16(1):3238.
  15. Saczynski JS, Kosar CM, Xu G, et al. A tale of two methods: chart and interview methods for identifying delirium. J Am Geriatr Soc. 2014;62(3):518524.
  16. Marcantonio E, Ngo L, Jones R, et al. 3D‐CAM: Derivation and validation of a 3‐minute diagnostic interview for CAM‐defined delirium: a cross‐sectional diagnostic test study. Ann Intern Med. 2014;161(8):554561.
  17. Yang FM, Jones RN, Inouye SK, et al. Selecting optimal screening items for delirium: an application of item response theory. BMC Med Res Methodol. 2013;13:8.
  18. Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695699.
  19. Yesavage JA. Geriatric Depression Scale. Psychopharmacol Bull. 1988;24(4):709711.
  20. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373383.
  21. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:914919.
  22. Lawton MP, Brody EM. Assessment of older people: self‐maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179186.
  23. Galvin J, Roe C, Powlishta K, et al. The AD8: a brief informant interview to detect dementia. Neurology. 2005;65(4):559564.
  24. McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging‐Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):263269.
  25. Neufeld KJ, Nelliot A, Inouye SK, et al. Delirium diagnosis methodology used in research: a survey‐based study. Am J Geriatr Psychiatry. 2014;22(12):15131521.
  26. Sands M, Dantoc B, Hartshorn A, Ryan C, Lujic S. Single Question in Delirium (SQiD): testing its efficacy against psychiatrist interview, the Confusion Assessment Method and the Memorial Delirium Assessment Scale. Palliat Med. 2010;24(6):561565.
  27. Han JH, Wilson A, Vasilevskis EE, et al. Diagnosing delirium in older emergency department patients: validity and reliability of the delirium triage screen and the brief confusion assessment method. Ann Emerg Med. 2013;62(5):457465.
  28. O'Regan NA, Ryan DJ, Boland E, et al. Attention! A good bedside test for delirium? J Neurol Neurosurg Psychiatry. 2014;85(10):11221131.
  29. Bergmann MA, Murphy KM, Kiely DK, Jones RN, Marcantonio ER. A model for management of delirious postacute care patients. J Am Geriatr Soc. 2005;53(10):18171825.
  30. Fick DM, Steis MR, Mion LC, Walls JL. Computerized decision support for delirium superimposed on dementia in older adults: a pilot study. J Gerontol Nurs. 2011;37(4):3947.
  31. Yevchak AM, Fick DM, McDowell J, et al. Barriers and facilitators to implementing delirium rounds in a clinical trial across three diverse hospital settings. Clin Nurs Res. 2014;23(2):201215.
  32. Meehl PE, Rosen A. Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychol Bull. 1955;52(3):194.
References
  1. Witlox J, Eurelings LS, Jonghe JF, Kalisvaart KJ, Eikelenboom P, Gool WA. Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: a meta‐analysis. JAMA. 2010;304(4):443451.
  2. Saczynski JS, Marcantonio ER, Quach L, et al. Cognitive trajectories after postoperative delirium. N Engl J Med. 2012;367(1):3039.
  3. Inouye SK, Westendorp RG, Saczynski JS. Delirium in elderly people. Lancet. 2014;383:911922.
  4. Fick DM, Steis MR, Waller JL, Inouye SK. Delirium superimposed on dementia is associated with prolonged length of stay and poor outcomes in hospitalized older adults. J Hosp Med. 2013;8(9):500505.
  5. Leslie DL, Marcantonio ER, Zhang Y, Leo‐Summers L, Inouye SK. One‐year health care costs associated with delirium in the elderly population. Arch Intern Med. 2008;168(1):2732.
  6. Leslie DL, Inouye SK. The importance of delirium: Economic and societal costs. J Am Geriatr Soc. 2011;59(suppl 2):S241S243.
  7. Marcantonio ER. Delirium. Ann Intern Med. 2011;154(11):ITC6.
  8. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50.
  9. Rice KL, Bennett MJ, Clesi T, Linville L. Mixed‐methods approach to understanding nurses' clinical reasoning in recognizing delirium in hospitalized older adults. J Contin Educ Nurs. 2014;45:1–13.
  10. Yanamadala M, Wieland D, Heflin MT. Educational interventions to improve recognition of delirium: a systematic review. J Am Geriatr Soc. 2013;61(11):19831993.
  11. Steis MR, Fick DM. Delirium superimposed on dementia: accuracy of nurse documentation. J Gerontol Nurs. 2012;38(1):3242.
  12. Lemiengre J, Nelis T, Joosten E, et al. Detection of delirium by bedside nurses using the confusion assessment method. J Am Geriatr Soc. 2006;54:685689.
  13. Milisen K, Foreman MD, Wouters B, et al. Documentation of delirium in elderly patients with hip fracture. J Gerontol Nurs. 2002;28(11):2329.
  14. Kales HC, Kamholz BA, Visnic SG, Blow FC. Recorded delirium in a national sample of elderly inpatients: potential implications for recognition. J Geriatr Psychiatry Neurol. 2003;16(1):3238.
  15. Saczynski JS, Kosar CM, Xu G, et al. A tale of two methods: chart and interview methods for identifying delirium. J Am Geriatr Soc. 2014;62(3):518524.
  16. Marcantonio E, Ngo L, Jones R, et al. 3D‐CAM: Derivation and validation of a 3‐minute diagnostic interview for CAM‐defined delirium: a cross‐sectional diagnostic test study. Ann Intern Med. 2014;161(8):554561.
  17. Yang FM, Jones RN, Inouye SK, et al. Selecting optimal screening items for delirium: an application of item response theory. BMC Med Res Methodol. 2013;13:8.
  18. Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695699.
  19. Yesavage JA. Geriatric Depression Scale. Psychopharmacol Bull. 1988;24(4):709711.
  20. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373383.
  21. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:914919.
  22. Lawton MP, Brody EM. Assessment of older people: self‐maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179186.
  23. Galvin J, Roe C, Powlishta K, et al. The AD8: a brief informant interview to detect dementia. Neurology. 2005;65(4):559564.
  24. McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging‐Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):263269.
  25. Neufeld KJ, Nelliot A, Inouye SK, et al. Delirium diagnosis methodology used in research: a survey‐based study. Am J Geriatr Psychiatry. 2014;22(12):15131521.
  26. Sands M, Dantoc B, Hartshorn A, Ryan C, Lujic S. Single Question in Delirium (SQiD): testing its efficacy against psychiatrist interview, the Confusion Assessment Method and the Memorial Delirium Assessment Scale. Palliat Med. 2010;24(6):561565.
  27. Han JH, Wilson A, Vasilevskis EE, et al. Diagnosing delirium in older emergency department patients: validity and reliability of the delirium triage screen and the brief confusion assessment method. Ann Emerg Med. 2013;62(5):457465.
  28. O'Regan NA, Ryan DJ, Boland E, et al. Attention! A good bedside test for delirium? J Neurol Neurosurg Psychiatry. 2014;85(10):11221131.
  29. Bergmann MA, Murphy KM, Kiely DK, Jones RN, Marcantonio ER. A model for management of delirious postacute care patients. J Am Geriatr Soc. 2005;53(10):18171825.
  30. Fick DM, Steis MR, Mion LC, Walls JL. Computerized decision support for delirium superimposed on dementia in older adults: a pilot study. J Gerontol Nurs. 2011;37(4):3947.
  31. Yevchak AM, Fick DM, McDowell J, et al. Barriers and facilitators to implementing delirium rounds in a clinical trial across three diverse hospital settings. Clin Nurs Res. 2014;23(2):201215.
  32. Meehl PE, Rosen A. Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychol Bull. 1955;52(3):194.
Issue
Journal of Hospital Medicine - 10(10)
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Journal of Hospital Medicine - 10(10)
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Preliminary development of an ultrabrief two‐item bedside test for delirium
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Address for correspondence and reprint requests: Donna M. Fick, PhD, Distinguished Professor, College of Nursing, Penn State University, Health and Human Development East, University Park, PA 16802; Telephone: 814‐865‐9325; Fax: 814‐865‐3779; E‐mail: dmf21@psu.edu
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MedPAC to look at physician prescribing tools as a way to control drug spending

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MedPAC to look at physician prescribing tools as a way to control drug spending

WASHINGTON – The Medicare Payment Advisory Commission is going to look at physician prescribing tools as part of a broader examination of how to rein in Medicare drug spending.

Members acknowledged during the Sept. 11, 2015, meeting that when it comes to the prices of drugs in the Medicare programs, the tools are limited to keep the prices low. Between statutory requirements for coverage of drugs in protected classes and a prohibition against the secretary of Health and Human Services negotiating prices for the Part D prescription drug benefit and other statutory requirements, even for intermediaries such as plan providers and hospital groups, leverage in price negotiations is very limited.

©Kenishirotie/Thinkstock

However, commission member Dr. Craig Samitt, former partner at Oliver Wyman of Paradise Valley, Ariz., suggested that the focus should be more on what leverage providers might have when it comes to utilization.

“So if we feel that neither CMS nor the intermediaries have sufficient leverage, well then who has significant leverage? The prescribing clinician,” Dr. Samitt said. “How well have we aligned interests around utilization in particular, not so much price, with the clinicians?”

Dr. Samitt noted that on the commercial side, there is a focus on utilization as a more effective driver of price, rather than simply targeting price first in the negotiation process, and suggested there might be room in Medicare for that kind of focus.

He also suggested that perhaps including drug utilization within the context of accountable care organizations could result in “additional focus on more effective prescribing patterns.”

The conversation occurred against a backdrop of examination of drug spending in general. MedPAC staff noted that Medicare is becoming a more prominent payer for drugs in the wake of Part D’s launch.

MedPAC staff estimates that in 2013, retail drugs made up 13% of Medicare spending, versus 9% of national health expenditures. Additionally, of the $574 billion spent by Medicare in that year, 19% was drugs and pharmacy, with the majority of drug spending (57%) coming from Part D.

The discussion was just the first on the subject as the group will look at other aspects of drug pricing and spending in future meetings. A specific timetable for offering policy recommendations was not discussed.

Dr. William Hall, professor at the University of Rochester (N.Y.) School of Medicine, added that it is not the price of the drug per se, but its value that needs to be focused on. He noted that the prices of the latest hepatitis C drugs might be high, but the value they have to the health care system is much greater and needs to be taken into consideration.

“One of the big differences from 2004 is we know a great deal more about the efficacy of drugs,” Dr. Hall said, suggesting that more needs to be done to educate clinicians on the proper use of medications as part of finding the right way to use physician prescribing patterns as leverage in price negotiations.

gtwachtman@frontlinemedcom.com

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WASHINGTON – The Medicare Payment Advisory Commission is going to look at physician prescribing tools as part of a broader examination of how to rein in Medicare drug spending.

Members acknowledged during the Sept. 11, 2015, meeting that when it comes to the prices of drugs in the Medicare programs, the tools are limited to keep the prices low. Between statutory requirements for coverage of drugs in protected classes and a prohibition against the secretary of Health and Human Services negotiating prices for the Part D prescription drug benefit and other statutory requirements, even for intermediaries such as plan providers and hospital groups, leverage in price negotiations is very limited.

©Kenishirotie/Thinkstock

However, commission member Dr. Craig Samitt, former partner at Oliver Wyman of Paradise Valley, Ariz., suggested that the focus should be more on what leverage providers might have when it comes to utilization.

“So if we feel that neither CMS nor the intermediaries have sufficient leverage, well then who has significant leverage? The prescribing clinician,” Dr. Samitt said. “How well have we aligned interests around utilization in particular, not so much price, with the clinicians?”

Dr. Samitt noted that on the commercial side, there is a focus on utilization as a more effective driver of price, rather than simply targeting price first in the negotiation process, and suggested there might be room in Medicare for that kind of focus.

He also suggested that perhaps including drug utilization within the context of accountable care organizations could result in “additional focus on more effective prescribing patterns.”

The conversation occurred against a backdrop of examination of drug spending in general. MedPAC staff noted that Medicare is becoming a more prominent payer for drugs in the wake of Part D’s launch.

MedPAC staff estimates that in 2013, retail drugs made up 13% of Medicare spending, versus 9% of national health expenditures. Additionally, of the $574 billion spent by Medicare in that year, 19% was drugs and pharmacy, with the majority of drug spending (57%) coming from Part D.

The discussion was just the first on the subject as the group will look at other aspects of drug pricing and spending in future meetings. A specific timetable for offering policy recommendations was not discussed.

Dr. William Hall, professor at the University of Rochester (N.Y.) School of Medicine, added that it is not the price of the drug per se, but its value that needs to be focused on. He noted that the prices of the latest hepatitis C drugs might be high, but the value they have to the health care system is much greater and needs to be taken into consideration.

“One of the big differences from 2004 is we know a great deal more about the efficacy of drugs,” Dr. Hall said, suggesting that more needs to be done to educate clinicians on the proper use of medications as part of finding the right way to use physician prescribing patterns as leverage in price negotiations.

gtwachtman@frontlinemedcom.com

WASHINGTON – The Medicare Payment Advisory Commission is going to look at physician prescribing tools as part of a broader examination of how to rein in Medicare drug spending.

Members acknowledged during the Sept. 11, 2015, meeting that when it comes to the prices of drugs in the Medicare programs, the tools are limited to keep the prices low. Between statutory requirements for coverage of drugs in protected classes and a prohibition against the secretary of Health and Human Services negotiating prices for the Part D prescription drug benefit and other statutory requirements, even for intermediaries such as plan providers and hospital groups, leverage in price negotiations is very limited.

©Kenishirotie/Thinkstock

However, commission member Dr. Craig Samitt, former partner at Oliver Wyman of Paradise Valley, Ariz., suggested that the focus should be more on what leverage providers might have when it comes to utilization.

“So if we feel that neither CMS nor the intermediaries have sufficient leverage, well then who has significant leverage? The prescribing clinician,” Dr. Samitt said. “How well have we aligned interests around utilization in particular, not so much price, with the clinicians?”

Dr. Samitt noted that on the commercial side, there is a focus on utilization as a more effective driver of price, rather than simply targeting price first in the negotiation process, and suggested there might be room in Medicare for that kind of focus.

He also suggested that perhaps including drug utilization within the context of accountable care organizations could result in “additional focus on more effective prescribing patterns.”

The conversation occurred against a backdrop of examination of drug spending in general. MedPAC staff noted that Medicare is becoming a more prominent payer for drugs in the wake of Part D’s launch.

MedPAC staff estimates that in 2013, retail drugs made up 13% of Medicare spending, versus 9% of national health expenditures. Additionally, of the $574 billion spent by Medicare in that year, 19% was drugs and pharmacy, with the majority of drug spending (57%) coming from Part D.

The discussion was just the first on the subject as the group will look at other aspects of drug pricing and spending in future meetings. A specific timetable for offering policy recommendations was not discussed.

Dr. William Hall, professor at the University of Rochester (N.Y.) School of Medicine, added that it is not the price of the drug per se, but its value that needs to be focused on. He noted that the prices of the latest hepatitis C drugs might be high, but the value they have to the health care system is much greater and needs to be taken into consideration.

“One of the big differences from 2004 is we know a great deal more about the efficacy of drugs,” Dr. Hall said, suggesting that more needs to be done to educate clinicians on the proper use of medications as part of finding the right way to use physician prescribing patterns as leverage in price negotiations.

gtwachtman@frontlinemedcom.com

References

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MedPAC to look at physician prescribing tools as a way to control drug spending
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AT A MEETING OF THE MEDICARE PAYMENT ADVISORY COMMISSION

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Metronidazole and alcohol

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Metronidazole and alcohol

A 32-year-old man develops diarrhea after receiving amoxicillin/clavulanate to treat an infection following a dog bite. He is diagnosed with Clostridium difficile and prescribed a 10-day course of metronidazole. He has no other medical problems. He will be the best man at his brother’s wedding tomorrow. What advice should you give him about alcohol use at the reception?

A. Do not take metronidazole the day of the wedding if you will be drinking alcohol.

B. Take metronidazole, do not drink alcohol.

C. It’s okay to drink alcohol.

For years, we have advised patients to not use alcohol if they are taking metronidazole because of concern for a disulfiram-like reaction between alcohol and metronidazole. This has been a standard warning given by physicians and appears as a contraindication in the prescribing information. It has been well accepted as a true, proven reaction.

Is it true?

As early as the 1960s, case reports and an uncontrolled study suggested that combining metronidazole with alcohol produced a disulfiram-like reaction, with case reports of severe reactions, including death.1, 2, 3 This was initially considered an area that might be therapeutic in the treatment of alcoholism, but several studies showed no benefit.4, 5

Caroline S. Williams and Dr. Kevin R. Woodcock reviewed the case reports for evidence of proof of a true interaction between metronidazole and ethanol.6 The case reports referenced textbooks to substantiate the interaction, but they did not present clear evidence of an interaction as the cause of elevated acetaldehyde levels.

Researchers have shown in a rat model that metronidazole can increase intracolonic, but not blood, acetaldehyde levels in rats that have received a combination of ethanol and metronidazole.7 Metronidazole did not have any inhibitory effect on hepatic or colonic alcohol dehydrogenase or aldehyde dehydrogenase. What was found was that rats treated with metronidazole had increased growth of Enterobacteriaceae, an alcohol dehydrogenase–containing aerobe, which could be the cause of the higher intracolonic acetaldehyde levels.

Jukka-Pekka Visapää and his colleagues studied the effect of coadministration of metronidazole and ethanol in young, healthy male volunteers.8 The study was a placebo-controlled, randomized trial. The study was small, with 12 participants. One-half of the study participants received metronidazole three times a day for 5 days; the other half received placebo. All participants then received ethanol 0.4g/kg, with blood testing being done every 20 minutes for the next 4 hours. Blood was tested for ethanol concentrations and for acetaldehyde levels. The study participants also had blood pressure, pulse, skin temperature, and symptoms monitored during the study.

There was no difference in blood acetaldehyde levels, vital signs, or symptoms between patients who received metronidazole or placebo. None of the subjects in the study had any measurable symptoms.

Metronidazole has many side effects, including nausea, vomiting, headache, dizziness, and seizures. These symptoms have a great deal of overlap with the symptoms of alcohol-disulfiram interaction. It has been assumed in early case reports that metronidazole caused a similar interaction with alcohol and raised acetaldehyde levels by interfering with aldehyde dehydrogenase.

Animal models and the human study do not show this to be the case. It is possible that metronidazole side effects alone were the cause of the symptoms in case reports. The one human study done was on healthy male volunteers, so projecting the results to a population with liver disease or other serious illness is a bit of a stretch. I think that if a problem exists with alcohol and metronidazole, it is uncommon and unlikely to occur in healthy individuals.

So, what would I advise the patient in the case about whether he can drink alcohol? I think that the risk would be minimal and that it would be safe for him to drink alcohol.

References

1. Br J Clin Pract. 1985 Jul;39(7):292-3.

2. Psychiatr Neurol. 1966;152:395-401.

3. Am J Forensic Med Pathol. 1996 Dec;17(4):343-6.

4. Q J Stud Alcohol. 1972 Sep;33: 734-40.

5. Q J Stud Ethanol. 1969 Mar;30: 140-51.

6. Ann Pharmacother. 2000 Feb;34(2):255-7.

7. Alcohol Clin Exp Res. 2000 Apr;24(4):570-5.

8. Ann Pharmacother. 2002 Jun;36(6):971-4.

Dr. Paauw is professor of medicine in the division of general internal medicine at the University of Washington, Seattle, and he serves as third-year medical student clerkship director at the University of Washington. Contact Dr. Paauw at dpaauw@uw.edu.

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A 32-year-old man develops diarrhea after receiving amoxicillin/clavulanate to treat an infection following a dog bite. He is diagnosed with Clostridium difficile and prescribed a 10-day course of metronidazole. He has no other medical problems. He will be the best man at his brother’s wedding tomorrow. What advice should you give him about alcohol use at the reception?

A. Do not take metronidazole the day of the wedding if you will be drinking alcohol.

B. Take metronidazole, do not drink alcohol.

C. It’s okay to drink alcohol.

For years, we have advised patients to not use alcohol if they are taking metronidazole because of concern for a disulfiram-like reaction between alcohol and metronidazole. This has been a standard warning given by physicians and appears as a contraindication in the prescribing information. It has been well accepted as a true, proven reaction.

Is it true?

As early as the 1960s, case reports and an uncontrolled study suggested that combining metronidazole with alcohol produced a disulfiram-like reaction, with case reports of severe reactions, including death.1, 2, 3 This was initially considered an area that might be therapeutic in the treatment of alcoholism, but several studies showed no benefit.4, 5

Caroline S. Williams and Dr. Kevin R. Woodcock reviewed the case reports for evidence of proof of a true interaction between metronidazole and ethanol.6 The case reports referenced textbooks to substantiate the interaction, but they did not present clear evidence of an interaction as the cause of elevated acetaldehyde levels.

Researchers have shown in a rat model that metronidazole can increase intracolonic, but not blood, acetaldehyde levels in rats that have received a combination of ethanol and metronidazole.7 Metronidazole did not have any inhibitory effect on hepatic or colonic alcohol dehydrogenase or aldehyde dehydrogenase. What was found was that rats treated with metronidazole had increased growth of Enterobacteriaceae, an alcohol dehydrogenase–containing aerobe, which could be the cause of the higher intracolonic acetaldehyde levels.

Jukka-Pekka Visapää and his colleagues studied the effect of coadministration of metronidazole and ethanol in young, healthy male volunteers.8 The study was a placebo-controlled, randomized trial. The study was small, with 12 participants. One-half of the study participants received metronidazole three times a day for 5 days; the other half received placebo. All participants then received ethanol 0.4g/kg, with blood testing being done every 20 minutes for the next 4 hours. Blood was tested for ethanol concentrations and for acetaldehyde levels. The study participants also had blood pressure, pulse, skin temperature, and symptoms monitored during the study.

There was no difference in blood acetaldehyde levels, vital signs, or symptoms between patients who received metronidazole or placebo. None of the subjects in the study had any measurable symptoms.

Metronidazole has many side effects, including nausea, vomiting, headache, dizziness, and seizures. These symptoms have a great deal of overlap with the symptoms of alcohol-disulfiram interaction. It has been assumed in early case reports that metronidazole caused a similar interaction with alcohol and raised acetaldehyde levels by interfering with aldehyde dehydrogenase.

Animal models and the human study do not show this to be the case. It is possible that metronidazole side effects alone were the cause of the symptoms in case reports. The one human study done was on healthy male volunteers, so projecting the results to a population with liver disease or other serious illness is a bit of a stretch. I think that if a problem exists with alcohol and metronidazole, it is uncommon and unlikely to occur in healthy individuals.

So, what would I advise the patient in the case about whether he can drink alcohol? I think that the risk would be minimal and that it would be safe for him to drink alcohol.

References

1. Br J Clin Pract. 1985 Jul;39(7):292-3.

2. Psychiatr Neurol. 1966;152:395-401.

3. Am J Forensic Med Pathol. 1996 Dec;17(4):343-6.

4. Q J Stud Alcohol. 1972 Sep;33: 734-40.

5. Q J Stud Ethanol. 1969 Mar;30: 140-51.

6. Ann Pharmacother. 2000 Feb;34(2):255-7.

7. Alcohol Clin Exp Res. 2000 Apr;24(4):570-5.

8. Ann Pharmacother. 2002 Jun;36(6):971-4.

Dr. Paauw is professor of medicine in the division of general internal medicine at the University of Washington, Seattle, and he serves as third-year medical student clerkship director at the University of Washington. Contact Dr. Paauw at dpaauw@uw.edu.

A 32-year-old man develops diarrhea after receiving amoxicillin/clavulanate to treat an infection following a dog bite. He is diagnosed with Clostridium difficile and prescribed a 10-day course of metronidazole. He has no other medical problems. He will be the best man at his brother’s wedding tomorrow. What advice should you give him about alcohol use at the reception?

A. Do not take metronidazole the day of the wedding if you will be drinking alcohol.

B. Take metronidazole, do not drink alcohol.

C. It’s okay to drink alcohol.

For years, we have advised patients to not use alcohol if they are taking metronidazole because of concern for a disulfiram-like reaction between alcohol and metronidazole. This has been a standard warning given by physicians and appears as a contraindication in the prescribing information. It has been well accepted as a true, proven reaction.

Is it true?

As early as the 1960s, case reports and an uncontrolled study suggested that combining metronidazole with alcohol produced a disulfiram-like reaction, with case reports of severe reactions, including death.1, 2, 3 This was initially considered an area that might be therapeutic in the treatment of alcoholism, but several studies showed no benefit.4, 5

Caroline S. Williams and Dr. Kevin R. Woodcock reviewed the case reports for evidence of proof of a true interaction between metronidazole and ethanol.6 The case reports referenced textbooks to substantiate the interaction, but they did not present clear evidence of an interaction as the cause of elevated acetaldehyde levels.

Researchers have shown in a rat model that metronidazole can increase intracolonic, but not blood, acetaldehyde levels in rats that have received a combination of ethanol and metronidazole.7 Metronidazole did not have any inhibitory effect on hepatic or colonic alcohol dehydrogenase or aldehyde dehydrogenase. What was found was that rats treated with metronidazole had increased growth of Enterobacteriaceae, an alcohol dehydrogenase–containing aerobe, which could be the cause of the higher intracolonic acetaldehyde levels.

Jukka-Pekka Visapää and his colleagues studied the effect of coadministration of metronidazole and ethanol in young, healthy male volunteers.8 The study was a placebo-controlled, randomized trial. The study was small, with 12 participants. One-half of the study participants received metronidazole three times a day for 5 days; the other half received placebo. All participants then received ethanol 0.4g/kg, with blood testing being done every 20 minutes for the next 4 hours. Blood was tested for ethanol concentrations and for acetaldehyde levels. The study participants also had blood pressure, pulse, skin temperature, and symptoms monitored during the study.

There was no difference in blood acetaldehyde levels, vital signs, or symptoms between patients who received metronidazole or placebo. None of the subjects in the study had any measurable symptoms.

Metronidazole has many side effects, including nausea, vomiting, headache, dizziness, and seizures. These symptoms have a great deal of overlap with the symptoms of alcohol-disulfiram interaction. It has been assumed in early case reports that metronidazole caused a similar interaction with alcohol and raised acetaldehyde levels by interfering with aldehyde dehydrogenase.

Animal models and the human study do not show this to be the case. It is possible that metronidazole side effects alone were the cause of the symptoms in case reports. The one human study done was on healthy male volunteers, so projecting the results to a population with liver disease or other serious illness is a bit of a stretch. I think that if a problem exists with alcohol and metronidazole, it is uncommon and unlikely to occur in healthy individuals.

So, what would I advise the patient in the case about whether he can drink alcohol? I think that the risk would be minimal and that it would be safe for him to drink alcohol.

References

1. Br J Clin Pract. 1985 Jul;39(7):292-3.

2. Psychiatr Neurol. 1966;152:395-401.

3. Am J Forensic Med Pathol. 1996 Dec;17(4):343-6.

4. Q J Stud Alcohol. 1972 Sep;33: 734-40.

5. Q J Stud Ethanol. 1969 Mar;30: 140-51.

6. Ann Pharmacother. 2000 Feb;34(2):255-7.

7. Alcohol Clin Exp Res. 2000 Apr;24(4):570-5.

8. Ann Pharmacother. 2002 Jun;36(6):971-4.

Dr. Paauw is professor of medicine in the division of general internal medicine at the University of Washington, Seattle, and he serves as third-year medical student clerkship director at the University of Washington. Contact Dr. Paauw at dpaauw@uw.edu.

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E-cigarette Smokers Less Exposed to Carbon Monoxide

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NEW YORK—Smokers who switch to e-cigarettes - even if only some of the time - may dramatically reduce their exposure to air pollutants including carbon monoxide and acrolein, a British study suggests.

Researchers gave e-cigarettes to 40 smokers who said they wanted to quit. After four weeks, the 16 participants using only e-cigarettes had about an 80% drop in exposure both to carbon monoxide and to acrolein, a harmful breakdown product that is also in some e-cigarettes' vapor. Acrolein is known to irritate exposed tissues and can destroy cilia.

The 17 participants who swapped some regular cigarettes for the electronic version had a 52% decline in carbon monoxide exposure and a 60% decline for acrolein, according to a report online September 3 in Cancer Prevention Research.

To get the most benefit from switching to e-cigarettes, smokers need to completely give up traditional cigarettes, lead study author Dr. Hayden McRobbie, of the Wolfson Institute of Preventive Medicine at Queen Mary University of London, said by email.

"Smokers may get some encouragement from the finding that there is some potential health benefit as soon as they start the process," Dr. McRobbie said.

While tobacco control advocates fear that e-cigarettes may give rise to a new generation of nicotine addicts who eventually transition to conventional cigarettes, the current study adds to a small but growing body of evidence suggesting the devices might benefit the health of people who already smoke.

An international analysis of published research by the Cochrane Review in December concluded the devices could help smokers quit but said much of the existing research on e-cigarettes was thin.

Even though the current study points to another potential benefit of e-cigarettes, more evidence is still needed from longer and larger trials before scientists can draw firm conclusions about any safety advantages, Dr. Nancy Rigotti, director of tobacco research at Massachusetts General Hospital in Boston, said by email.

"It is exactly the type of incremental, careful work that is needed but it is not yet a definitive study," Rigotti, who wasn't involved in the study, said.

Study participants were typically in their 40s and had attempted to quit at least twice before joining the trial. All of them were offered the same type of e-cigarette and encouraged to completely abandon traditional cigarettes.

Researchers measured carbon monoxide in participants' breath one week before switching to e-cigarettes, on the day they switched, and again four weeks later. They followed the same schedule for testing urine for exposure to acrolein.

A limitation of the study, the authors acknowledged, is that it only included people with a desire to quit smoking, making it possible the results would be different for smokers with no intention of quitting. It's also possible that the specific model of e-cigarette used in the study might not be representative of other devices.

Still, the findings suggest smokers should be told e-cigarettes may curb their exposure to toxic chemicals, Dr. Riccardo Polosa, head of the tobacco research center at the University of Catania in Italy, said by email.

"This study adds to the evidence that e-cigarettes are much less harmful compared to conventional cigarettes," said Polosa, who wasn't involved in the study.

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NEW YORK—Smokers who switch to e-cigarettes - even if only some of the time - may dramatically reduce their exposure to air pollutants including carbon monoxide and acrolein, a British study suggests.

Researchers gave e-cigarettes to 40 smokers who said they wanted to quit. After four weeks, the 16 participants using only e-cigarettes had about an 80% drop in exposure both to carbon monoxide and to acrolein, a harmful breakdown product that is also in some e-cigarettes' vapor. Acrolein is known to irritate exposed tissues and can destroy cilia.

The 17 participants who swapped some regular cigarettes for the electronic version had a 52% decline in carbon monoxide exposure and a 60% decline for acrolein, according to a report online September 3 in Cancer Prevention Research.

To get the most benefit from switching to e-cigarettes, smokers need to completely give up traditional cigarettes, lead study author Dr. Hayden McRobbie, of the Wolfson Institute of Preventive Medicine at Queen Mary University of London, said by email.

"Smokers may get some encouragement from the finding that there is some potential health benefit as soon as they start the process," Dr. McRobbie said.

While tobacco control advocates fear that e-cigarettes may give rise to a new generation of nicotine addicts who eventually transition to conventional cigarettes, the current study adds to a small but growing body of evidence suggesting the devices might benefit the health of people who already smoke.

An international analysis of published research by the Cochrane Review in December concluded the devices could help smokers quit but said much of the existing research on e-cigarettes was thin.

Even though the current study points to another potential benefit of e-cigarettes, more evidence is still needed from longer and larger trials before scientists can draw firm conclusions about any safety advantages, Dr. Nancy Rigotti, director of tobacco research at Massachusetts General Hospital in Boston, said by email.

"It is exactly the type of incremental, careful work that is needed but it is not yet a definitive study," Rigotti, who wasn't involved in the study, said.

Study participants were typically in their 40s and had attempted to quit at least twice before joining the trial. All of them were offered the same type of e-cigarette and encouraged to completely abandon traditional cigarettes.

Researchers measured carbon monoxide in participants' breath one week before switching to e-cigarettes, on the day they switched, and again four weeks later. They followed the same schedule for testing urine for exposure to acrolein.

A limitation of the study, the authors acknowledged, is that it only included people with a desire to quit smoking, making it possible the results would be different for smokers with no intention of quitting. It's also possible that the specific model of e-cigarette used in the study might not be representative of other devices.

Still, the findings suggest smokers should be told e-cigarettes may curb their exposure to toxic chemicals, Dr. Riccardo Polosa, head of the tobacco research center at the University of Catania in Italy, said by email.

"This study adds to the evidence that e-cigarettes are much less harmful compared to conventional cigarettes," said Polosa, who wasn't involved in the study.

NEW YORK—Smokers who switch to e-cigarettes - even if only some of the time - may dramatically reduce their exposure to air pollutants including carbon monoxide and acrolein, a British study suggests.

Researchers gave e-cigarettes to 40 smokers who said they wanted to quit. After four weeks, the 16 participants using only e-cigarettes had about an 80% drop in exposure both to carbon monoxide and to acrolein, a harmful breakdown product that is also in some e-cigarettes' vapor. Acrolein is known to irritate exposed tissues and can destroy cilia.

The 17 participants who swapped some regular cigarettes for the electronic version had a 52% decline in carbon monoxide exposure and a 60% decline for acrolein, according to a report online September 3 in Cancer Prevention Research.

To get the most benefit from switching to e-cigarettes, smokers need to completely give up traditional cigarettes, lead study author Dr. Hayden McRobbie, of the Wolfson Institute of Preventive Medicine at Queen Mary University of London, said by email.

"Smokers may get some encouragement from the finding that there is some potential health benefit as soon as they start the process," Dr. McRobbie said.

While tobacco control advocates fear that e-cigarettes may give rise to a new generation of nicotine addicts who eventually transition to conventional cigarettes, the current study adds to a small but growing body of evidence suggesting the devices might benefit the health of people who already smoke.

An international analysis of published research by the Cochrane Review in December concluded the devices could help smokers quit but said much of the existing research on e-cigarettes was thin.

Even though the current study points to another potential benefit of e-cigarettes, more evidence is still needed from longer and larger trials before scientists can draw firm conclusions about any safety advantages, Dr. Nancy Rigotti, director of tobacco research at Massachusetts General Hospital in Boston, said by email.

"It is exactly the type of incremental, careful work that is needed but it is not yet a definitive study," Rigotti, who wasn't involved in the study, said.

Study participants were typically in their 40s and had attempted to quit at least twice before joining the trial. All of them were offered the same type of e-cigarette and encouraged to completely abandon traditional cigarettes.

Researchers measured carbon monoxide in participants' breath one week before switching to e-cigarettes, on the day they switched, and again four weeks later. They followed the same schedule for testing urine for exposure to acrolein.

A limitation of the study, the authors acknowledged, is that it only included people with a desire to quit smoking, making it possible the results would be different for smokers with no intention of quitting. It's also possible that the specific model of e-cigarette used in the study might not be representative of other devices.

Still, the findings suggest smokers should be told e-cigarettes may curb their exposure to toxic chemicals, Dr. Riccardo Polosa, head of the tobacco research center at the University of Catania in Italy, said by email.

"This study adds to the evidence that e-cigarettes are much less harmful compared to conventional cigarettes," said Polosa, who wasn't involved in the study.

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Social factors may impact survival in AML

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Patient receiving chemotherapy

Photo by Rhoda Baer

A new study indicates that certain social factors may impact survival in adults with acute myelogenous leukemia (AML) who are under 65.

The research showed associations between patient survival and insurance status, marital status, and county-level income.

“We believe these 3 factors indicate lack of material and social support preventing young patients from successfully walking the long and difficult road towards a cure,” said Uma Borate, MD, of the University of Alabama at Birmingham.

To conduct this study, Dr Borate and her colleagues analyzed data on 5541 patients, ages 19 to 64, who were diagnosed with AML between 2007 and 2011.

The team reported their findings in Cancer.

Multivariable analysis showed that AML subtype, age, and sex were independently associated with patients’ survival. And the non-biological factors independently associated with survival were insurance status, marital status, and county-level median household income.

Specifically, there was a significantly increased risk of premature death among patients who were uninsured (P=0.005) or Medicaid beneficiaries (P<0.001), compared to patients with private insurance.

Single (P<0.001) or divorced (P=0.011) patients had a significantly higher risk of premature death than married patients. But there was no significant difference between married and widowed patients (P=0.206).

And patients who lived in areas with lower income—the lowest 3 of 5 income groups—had a significantly increased risk of premature death.

Compared to patients in the fifth income quintile ($58.3K-$79.9K), there was an increased risk of death in the first quintile ($16.2K-$38.8K, P=0.001), second quintile ($38.8K-$42.2K, P<0.001), and third quintile ($42.2K-$47.9K, P<0.001).

Early and late mortality

The researchers wanted to determine if the impact of non-biological factors on survival was related to early mortality (a possible surrogate for access to care or late presentation) or late mortality (a possible surrogate for access to post-remission therapy and hematopoietic stem cell transplant).

So they conducted an exploratory analysis of factors influencing the risk of death within the first 2 months of diagnosis.

Being a Medicaid beneficiary (P=0.01) or uninsured (P<0.001) was independently associated with an increased risk of death within the first 2 months.

The same was true for patients belonging to the first income quartile (P=0.001), second quartile (P=0.003), third quartile (P=0.02), and fourth quartile (P=0.028).

On the other hand, there was no significant difference in early death according to marital status.

The researchers also performed a landmark survival analysis including only patients who survived at least 2 months from diagnosis.

In this analysis, marital status (P<0.001), insurance status (P=0.001), and income (P=0.021) were all independent predictors of survival.

Implications

“As physicians, we often emphasize more of the biology of the cancer, especially with the recent focus on personalized medicine,” said study author Luciano Jose Costa, MD, PhD, also of the University of Alabama at Birmingham.

“But we need to pay the same attention to resources available to our patients, as this greatly impacts their chances to survive leukemia.”

The researchers believe this will be especially important as the US transitions to a healthcare system that ties physician and hospital payments to patient outcomes.

“Taking from the results of this study, factors that have nothing to do with quality of care need to be accounted for when comparing predicted with actual outcomes,” Dr Borate said. “Otherwise, we will create a disincentive for hospitals and doctors to care for less privileged patients.”

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Patient receiving chemotherapy

Photo by Rhoda Baer

A new study indicates that certain social factors may impact survival in adults with acute myelogenous leukemia (AML) who are under 65.

The research showed associations between patient survival and insurance status, marital status, and county-level income.

“We believe these 3 factors indicate lack of material and social support preventing young patients from successfully walking the long and difficult road towards a cure,” said Uma Borate, MD, of the University of Alabama at Birmingham.

To conduct this study, Dr Borate and her colleagues analyzed data on 5541 patients, ages 19 to 64, who were diagnosed with AML between 2007 and 2011.

The team reported their findings in Cancer.

Multivariable analysis showed that AML subtype, age, and sex were independently associated with patients’ survival. And the non-biological factors independently associated with survival were insurance status, marital status, and county-level median household income.

Specifically, there was a significantly increased risk of premature death among patients who were uninsured (P=0.005) or Medicaid beneficiaries (P<0.001), compared to patients with private insurance.

Single (P<0.001) or divorced (P=0.011) patients had a significantly higher risk of premature death than married patients. But there was no significant difference between married and widowed patients (P=0.206).

And patients who lived in areas with lower income—the lowest 3 of 5 income groups—had a significantly increased risk of premature death.

Compared to patients in the fifth income quintile ($58.3K-$79.9K), there was an increased risk of death in the first quintile ($16.2K-$38.8K, P=0.001), second quintile ($38.8K-$42.2K, P<0.001), and third quintile ($42.2K-$47.9K, P<0.001).

Early and late mortality

The researchers wanted to determine if the impact of non-biological factors on survival was related to early mortality (a possible surrogate for access to care or late presentation) or late mortality (a possible surrogate for access to post-remission therapy and hematopoietic stem cell transplant).

So they conducted an exploratory analysis of factors influencing the risk of death within the first 2 months of diagnosis.

Being a Medicaid beneficiary (P=0.01) or uninsured (P<0.001) was independently associated with an increased risk of death within the first 2 months.

The same was true for patients belonging to the first income quartile (P=0.001), second quartile (P=0.003), third quartile (P=0.02), and fourth quartile (P=0.028).

On the other hand, there was no significant difference in early death according to marital status.

The researchers also performed a landmark survival analysis including only patients who survived at least 2 months from diagnosis.

In this analysis, marital status (P<0.001), insurance status (P=0.001), and income (P=0.021) were all independent predictors of survival.

Implications

“As physicians, we often emphasize more of the biology of the cancer, especially with the recent focus on personalized medicine,” said study author Luciano Jose Costa, MD, PhD, also of the University of Alabama at Birmingham.

“But we need to pay the same attention to resources available to our patients, as this greatly impacts their chances to survive leukemia.”

The researchers believe this will be especially important as the US transitions to a healthcare system that ties physician and hospital payments to patient outcomes.

“Taking from the results of this study, factors that have nothing to do with quality of care need to be accounted for when comparing predicted with actual outcomes,” Dr Borate said. “Otherwise, we will create a disincentive for hospitals and doctors to care for less privileged patients.”

Patient receiving chemotherapy

Photo by Rhoda Baer

A new study indicates that certain social factors may impact survival in adults with acute myelogenous leukemia (AML) who are under 65.

The research showed associations between patient survival and insurance status, marital status, and county-level income.

“We believe these 3 factors indicate lack of material and social support preventing young patients from successfully walking the long and difficult road towards a cure,” said Uma Borate, MD, of the University of Alabama at Birmingham.

To conduct this study, Dr Borate and her colleagues analyzed data on 5541 patients, ages 19 to 64, who were diagnosed with AML between 2007 and 2011.

The team reported their findings in Cancer.

Multivariable analysis showed that AML subtype, age, and sex were independently associated with patients’ survival. And the non-biological factors independently associated with survival were insurance status, marital status, and county-level median household income.

Specifically, there was a significantly increased risk of premature death among patients who were uninsured (P=0.005) or Medicaid beneficiaries (P<0.001), compared to patients with private insurance.

Single (P<0.001) or divorced (P=0.011) patients had a significantly higher risk of premature death than married patients. But there was no significant difference between married and widowed patients (P=0.206).

And patients who lived in areas with lower income—the lowest 3 of 5 income groups—had a significantly increased risk of premature death.

Compared to patients in the fifth income quintile ($58.3K-$79.9K), there was an increased risk of death in the first quintile ($16.2K-$38.8K, P=0.001), second quintile ($38.8K-$42.2K, P<0.001), and third quintile ($42.2K-$47.9K, P<0.001).

Early and late mortality

The researchers wanted to determine if the impact of non-biological factors on survival was related to early mortality (a possible surrogate for access to care or late presentation) or late mortality (a possible surrogate for access to post-remission therapy and hematopoietic stem cell transplant).

So they conducted an exploratory analysis of factors influencing the risk of death within the first 2 months of diagnosis.

Being a Medicaid beneficiary (P=0.01) or uninsured (P<0.001) was independently associated with an increased risk of death within the first 2 months.

The same was true for patients belonging to the first income quartile (P=0.001), second quartile (P=0.003), third quartile (P=0.02), and fourth quartile (P=0.028).

On the other hand, there was no significant difference in early death according to marital status.

The researchers also performed a landmark survival analysis including only patients who survived at least 2 months from diagnosis.

In this analysis, marital status (P<0.001), insurance status (P=0.001), and income (P=0.021) were all independent predictors of survival.

Implications

“As physicians, we often emphasize more of the biology of the cancer, especially with the recent focus on personalized medicine,” said study author Luciano Jose Costa, MD, PhD, also of the University of Alabama at Birmingham.

“But we need to pay the same attention to resources available to our patients, as this greatly impacts their chances to survive leukemia.”

The researchers believe this will be especially important as the US transitions to a healthcare system that ties physician and hospital payments to patient outcomes.

“Taking from the results of this study, factors that have nothing to do with quality of care need to be accounted for when comparing predicted with actual outcomes,” Dr Borate said. “Otherwise, we will create a disincentive for hospitals and doctors to care for less privileged patients.”

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EMA recommends orphan designation for LJPC-401

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Sickled and normal

red blood cells

Image by Graham Beards

The European Medicines Agency’s (EMA’s) Committee for Orphan Medicinal Products (COMP) has adopted a positive opinion recommending that LJPC-401, a novel formulation of hepcidin, receive orphan designation to treat chronic iron overload requiring chelation therapy.

Chronic iron overload occurs in patients suffering from beta thalassemia, sickle cell disease, and hereditary hemochromatosis.

The COMP’s opinion, which is subject to review and approval by the European Commission, may include all or a subset of these conditions.

About LJPC-401

LJPC-401 is a novel formulation of hepcidin, an endogenous peptide hormone that is the body’s naturally occurring regulator of iron absorption and distribution. Hepcidin prevents excessive iron accumulation in tissues, such as the liver and heart, where it can cause significant damage and even result in death.

La Jolla Pharmaceutical Company is developing LJPC-401 for the treatment of iron overload occurring as a results of hereditary hemochromatosis, beta thalassemia, and sickle cell disease.

LJPC-401 has been shown to be effective in reducing serum iron in preclinical testing, according to La Jolla. The company said it expects to release preliminary results from a phase 1 trial of LJPC-401 by the end of this year.

About orphan designation

The EMA’s COMP adopts an opinion on the granting of orphan drug designation, and that opinion is submitted to the European Commission for endorsement.

In the European Union, orphan designation is granted to therapies intended to treat a life-threatening or chronically debilitating condition that affects no more than 5 in 10,000 persons and where no satisfactory treatment is available.

Companies that obtain orphan designation for a drug benefit from a number of incentives, including protocol assistance, a type of scientific advice specific for designated orphan medicines, and 10 years of market exclusivity if the medicine is approved. Fee reductions are also available, depending on the status of the sponsor and the type of service required.

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Sickled and normal

red blood cells

Image by Graham Beards

The European Medicines Agency’s (EMA’s) Committee for Orphan Medicinal Products (COMP) has adopted a positive opinion recommending that LJPC-401, a novel formulation of hepcidin, receive orphan designation to treat chronic iron overload requiring chelation therapy.

Chronic iron overload occurs in patients suffering from beta thalassemia, sickle cell disease, and hereditary hemochromatosis.

The COMP’s opinion, which is subject to review and approval by the European Commission, may include all or a subset of these conditions.

About LJPC-401

LJPC-401 is a novel formulation of hepcidin, an endogenous peptide hormone that is the body’s naturally occurring regulator of iron absorption and distribution. Hepcidin prevents excessive iron accumulation in tissues, such as the liver and heart, where it can cause significant damage and even result in death.

La Jolla Pharmaceutical Company is developing LJPC-401 for the treatment of iron overload occurring as a results of hereditary hemochromatosis, beta thalassemia, and sickle cell disease.

LJPC-401 has been shown to be effective in reducing serum iron in preclinical testing, according to La Jolla. The company said it expects to release preliminary results from a phase 1 trial of LJPC-401 by the end of this year.

About orphan designation

The EMA’s COMP adopts an opinion on the granting of orphan drug designation, and that opinion is submitted to the European Commission for endorsement.

In the European Union, orphan designation is granted to therapies intended to treat a life-threatening or chronically debilitating condition that affects no more than 5 in 10,000 persons and where no satisfactory treatment is available.

Companies that obtain orphan designation for a drug benefit from a number of incentives, including protocol assistance, a type of scientific advice specific for designated orphan medicines, and 10 years of market exclusivity if the medicine is approved. Fee reductions are also available, depending on the status of the sponsor and the type of service required.

Sickled and normal

red blood cells

Image by Graham Beards

The European Medicines Agency’s (EMA’s) Committee for Orphan Medicinal Products (COMP) has adopted a positive opinion recommending that LJPC-401, a novel formulation of hepcidin, receive orphan designation to treat chronic iron overload requiring chelation therapy.

Chronic iron overload occurs in patients suffering from beta thalassemia, sickle cell disease, and hereditary hemochromatosis.

The COMP’s opinion, which is subject to review and approval by the European Commission, may include all or a subset of these conditions.

About LJPC-401

LJPC-401 is a novel formulation of hepcidin, an endogenous peptide hormone that is the body’s naturally occurring regulator of iron absorption and distribution. Hepcidin prevents excessive iron accumulation in tissues, such as the liver and heart, where it can cause significant damage and even result in death.

La Jolla Pharmaceutical Company is developing LJPC-401 for the treatment of iron overload occurring as a results of hereditary hemochromatosis, beta thalassemia, and sickle cell disease.

LJPC-401 has been shown to be effective in reducing serum iron in preclinical testing, according to La Jolla. The company said it expects to release preliminary results from a phase 1 trial of LJPC-401 by the end of this year.

About orphan designation

The EMA’s COMP adopts an opinion on the granting of orphan drug designation, and that opinion is submitted to the European Commission for endorsement.

In the European Union, orphan designation is granted to therapies intended to treat a life-threatening or chronically debilitating condition that affects no more than 5 in 10,000 persons and where no satisfactory treatment is available.

Companies that obtain orphan designation for a drug benefit from a number of incentives, including protocol assistance, a type of scientific advice specific for designated orphan medicines, and 10 years of market exclusivity if the medicine is approved. Fee reductions are also available, depending on the status of the sponsor and the type of service required.

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Communication key to helping kids after disasters

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Posttraumatic stress disorder can be hard to spot in kids after natural or manmade disasters.

They may not understand that intrusive thoughts, panic attacks, and other symptoms are problems that can be addressed, and are unlikely to mention them.

As a result, parents, teachers, and others often underestimate children’s distress levels and overestimate their resilience. One way around the problem is to ask children how they’re doing, and probe for signs of trouble. It helps to let them know that PTSD and adjustment problems are normal after a frightening event, and to teach them how to anticipate and cope with PTSD triggers.

That’s just a small fraction of the useful advice in new guidance from the American Academy of Pediatrics on the psychosocial support of children and families after disasters, published online Sept. 14 (Pediatrics. 2015 Sept. 14. doi:10.1542/peds.2015-2861).

“Children are particularly vulnerable to the effects of disasters and other traumatic events because of a lack of experience, skills, and resources to be able to independently meet their developmental, socioemotional, mental, and behavioral health needs,” said the authors, led by Dr. David Schonfeld of St. Christopher’s Hospital for Children, and Thomas Demaria, Ph.D., of Long Island (N.Y.) University.

Mental health triage should come right after medical stabilization. Dissociative symptoms; extreme confusion or inability to concentrate or make even simple decisions; intense fear, anxiety, panic, helplessness, or horror; depression at the time of the event; uncontrollable and intense grief; suicidal ideation; and marked somatization are among the warning signs that kids are in trouble.

Psychiatric medications to blunt such reactions are usually the wrong call. “Children need to develop an understanding of the event and learn to express and cope with their reactions.” If medication does seem necessary, its best to let an expert in childhood trauma make the decision, the authors said.

Dismissing children’s concerns is a mistake. “In reality, if children feel worried, then they are worried. Telling them that they should not be worried is usually ineffective.” It’s also a mistake to avoid talking about grief for fear of making it worse. Children’s “distress is caused by the reaction to the death itself, rather than any question or invitation to talk. Talking may provide some relief if not coerced. Avoiding discussion is rarely helpful and often isolates children at a time when they are most in need of support and assistance,” they said.

Simple, basic facts about the event – as long as they’re not graphic or overwhelming – will help children make sense of what they’ve been through, and reassurance that things will eventually be okay can be healing. Kids also have to know that the situation isn’t their fault, and how to cope with it.

Parents can share how they’re upset about losing their home, for instance, but then discuss how talking to another trusted adult, getting exercise, meditating, and helping others makes them feel better. Pediatricians can boost spirits by saying something like “the tornado created a big mess, but we are pulling together as a community” or “living in a shelter with all the other children in the neighborhood must have been a real adventure,” the authors said.

Having children contribute to food drives or draw hopeful pictures for victims in the hospital can help them regain a sense of control and usefulness. Resuming their routines as soon as possible will also help bring back a sense of normalcy.

Bereavement counseling is in order when children are struggling with the loss of a loved one, and cognitive behavioral therapy for kids with PTSD.

aotto@frontlinemedcom.com

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Posttraumatic stress disorder can be hard to spot in kids after natural or manmade disasters.

They may not understand that intrusive thoughts, panic attacks, and other symptoms are problems that can be addressed, and are unlikely to mention them.

As a result, parents, teachers, and others often underestimate children’s distress levels and overestimate their resilience. One way around the problem is to ask children how they’re doing, and probe for signs of trouble. It helps to let them know that PTSD and adjustment problems are normal after a frightening event, and to teach them how to anticipate and cope with PTSD triggers.

That’s just a small fraction of the useful advice in new guidance from the American Academy of Pediatrics on the psychosocial support of children and families after disasters, published online Sept. 14 (Pediatrics. 2015 Sept. 14. doi:10.1542/peds.2015-2861).

“Children are particularly vulnerable to the effects of disasters and other traumatic events because of a lack of experience, skills, and resources to be able to independently meet their developmental, socioemotional, mental, and behavioral health needs,” said the authors, led by Dr. David Schonfeld of St. Christopher’s Hospital for Children, and Thomas Demaria, Ph.D., of Long Island (N.Y.) University.

Mental health triage should come right after medical stabilization. Dissociative symptoms; extreme confusion or inability to concentrate or make even simple decisions; intense fear, anxiety, panic, helplessness, or horror; depression at the time of the event; uncontrollable and intense grief; suicidal ideation; and marked somatization are among the warning signs that kids are in trouble.

Psychiatric medications to blunt such reactions are usually the wrong call. “Children need to develop an understanding of the event and learn to express and cope with their reactions.” If medication does seem necessary, its best to let an expert in childhood trauma make the decision, the authors said.

Dismissing children’s concerns is a mistake. “In reality, if children feel worried, then they are worried. Telling them that they should not be worried is usually ineffective.” It’s also a mistake to avoid talking about grief for fear of making it worse. Children’s “distress is caused by the reaction to the death itself, rather than any question or invitation to talk. Talking may provide some relief if not coerced. Avoiding discussion is rarely helpful and often isolates children at a time when they are most in need of support and assistance,” they said.

Simple, basic facts about the event – as long as they’re not graphic or overwhelming – will help children make sense of what they’ve been through, and reassurance that things will eventually be okay can be healing. Kids also have to know that the situation isn’t their fault, and how to cope with it.

Parents can share how they’re upset about losing their home, for instance, but then discuss how talking to another trusted adult, getting exercise, meditating, and helping others makes them feel better. Pediatricians can boost spirits by saying something like “the tornado created a big mess, but we are pulling together as a community” or “living in a shelter with all the other children in the neighborhood must have been a real adventure,” the authors said.

Having children contribute to food drives or draw hopeful pictures for victims in the hospital can help them regain a sense of control and usefulness. Resuming their routines as soon as possible will also help bring back a sense of normalcy.

Bereavement counseling is in order when children are struggling with the loss of a loved one, and cognitive behavioral therapy for kids with PTSD.

aotto@frontlinemedcom.com

Posttraumatic stress disorder can be hard to spot in kids after natural or manmade disasters.

They may not understand that intrusive thoughts, panic attacks, and other symptoms are problems that can be addressed, and are unlikely to mention them.

As a result, parents, teachers, and others often underestimate children’s distress levels and overestimate their resilience. One way around the problem is to ask children how they’re doing, and probe for signs of trouble. It helps to let them know that PTSD and adjustment problems are normal after a frightening event, and to teach them how to anticipate and cope with PTSD triggers.

That’s just a small fraction of the useful advice in new guidance from the American Academy of Pediatrics on the psychosocial support of children and families after disasters, published online Sept. 14 (Pediatrics. 2015 Sept. 14. doi:10.1542/peds.2015-2861).

“Children are particularly vulnerable to the effects of disasters and other traumatic events because of a lack of experience, skills, and resources to be able to independently meet their developmental, socioemotional, mental, and behavioral health needs,” said the authors, led by Dr. David Schonfeld of St. Christopher’s Hospital for Children, and Thomas Demaria, Ph.D., of Long Island (N.Y.) University.

Mental health triage should come right after medical stabilization. Dissociative symptoms; extreme confusion or inability to concentrate or make even simple decisions; intense fear, anxiety, panic, helplessness, or horror; depression at the time of the event; uncontrollable and intense grief; suicidal ideation; and marked somatization are among the warning signs that kids are in trouble.

Psychiatric medications to blunt such reactions are usually the wrong call. “Children need to develop an understanding of the event and learn to express and cope with their reactions.” If medication does seem necessary, its best to let an expert in childhood trauma make the decision, the authors said.

Dismissing children’s concerns is a mistake. “In reality, if children feel worried, then they are worried. Telling them that they should not be worried is usually ineffective.” It’s also a mistake to avoid talking about grief for fear of making it worse. Children’s “distress is caused by the reaction to the death itself, rather than any question or invitation to talk. Talking may provide some relief if not coerced. Avoiding discussion is rarely helpful and often isolates children at a time when they are most in need of support and assistance,” they said.

Simple, basic facts about the event – as long as they’re not graphic or overwhelming – will help children make sense of what they’ve been through, and reassurance that things will eventually be okay can be healing. Kids also have to know that the situation isn’t their fault, and how to cope with it.

Parents can share how they’re upset about losing their home, for instance, but then discuss how talking to another trusted adult, getting exercise, meditating, and helping others makes them feel better. Pediatricians can boost spirits by saying something like “the tornado created a big mess, but we are pulling together as a community” or “living in a shelter with all the other children in the neighborhood must have been a real adventure,” the authors said.

Having children contribute to food drives or draw hopeful pictures for victims in the hospital can help them regain a sense of control and usefulness. Resuming their routines as soon as possible will also help bring back a sense of normalcy.

Bereavement counseling is in order when children are struggling with the loss of a loved one, and cognitive behavioral therapy for kids with PTSD.

aotto@frontlinemedcom.com

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Product News: 09 2015

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Cyclosporine A

Immune Pharmaceuticals acquires a nanoparticle topical formulation of cyclosporine A for the treatment of psoriasis, atopic dermatitis, pemphigus vulgaris, and other severe inflammatory dermatoses. Researchers have incorporated cyclosporine A into biodegradable nanocapsules and have developed stable topical formulations that are able to achieve therapeutic cyclosporine A levels in the targeted skin layers. This topical treatment provides a potential alternative to oral cyclosporine A and other topical immunosuppressive drugs. For more information, visit www.immunepharmaceuticals.com.


Picato Gel Warning

The US Food and Drug Administration (FDA) issues a warning about reports of severe allergic reactions and herpes zoster associated with the use of Picato Gel (ingenol mebutate) for the treatment of actinic keratosis. The allergic reaction may include throat tightness, difficulty breathing, feeling faint, or swelling of the lips or tongue. The FDA received reports of cases involving severe eye injuries associated with Picato Gel not being used according to the instructions for use on the label. Changes to the labeling have been requested by the FDA to warn about these new safety risks. Patients should not use Picato Gel for a longer period or on an area of skin larger than instructed on the drug label. Patients also should avoid application in, near, and around the mouth, lips, and eye area. For more information, visit www.fda.gov/MedWatch.


Ximino Extended-Release Capsules

Sun Pharmaceutical Industries Ltd announces US Food and Drug Administration approval of the Supplemental New Drug Application for Ximino (minocycline hydrochloride) extended-release 
capsules (45, 90, and 135 mg). Ximino 
extended-release capsules are indicated for the treatment of inflammatory lesions of nonnodular moderate to severe acne vulgaris in patients 
12 years and older. Ximino extended-release capsules are expected to be available for patients during the fourth quarter of 2015. For more information, visit www.sunpharma.com.

 

If you would like your product included in Product News, please e-mail a press release to the Editorial Office at cutis@frontlinemedcom.com.

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Cyclosporine A

Immune Pharmaceuticals acquires a nanoparticle topical formulation of cyclosporine A for the treatment of psoriasis, atopic dermatitis, pemphigus vulgaris, and other severe inflammatory dermatoses. Researchers have incorporated cyclosporine A into biodegradable nanocapsules and have developed stable topical formulations that are able to achieve therapeutic cyclosporine A levels in the targeted skin layers. This topical treatment provides a potential alternative to oral cyclosporine A and other topical immunosuppressive drugs. For more information, visit www.immunepharmaceuticals.com.


Picato Gel Warning

The US Food and Drug Administration (FDA) issues a warning about reports of severe allergic reactions and herpes zoster associated with the use of Picato Gel (ingenol mebutate) for the treatment of actinic keratosis. The allergic reaction may include throat tightness, difficulty breathing, feeling faint, or swelling of the lips or tongue. The FDA received reports of cases involving severe eye injuries associated with Picato Gel not being used according to the instructions for use on the label. Changes to the labeling have been requested by the FDA to warn about these new safety risks. Patients should not use Picato Gel for a longer period or on an area of skin larger than instructed on the drug label. Patients also should avoid application in, near, and around the mouth, lips, and eye area. For more information, visit www.fda.gov/MedWatch.


Ximino Extended-Release Capsules

Sun Pharmaceutical Industries Ltd announces US Food and Drug Administration approval of the Supplemental New Drug Application for Ximino (minocycline hydrochloride) extended-release 
capsules (45, 90, and 135 mg). Ximino 
extended-release capsules are indicated for the treatment of inflammatory lesions of nonnodular moderate to severe acne vulgaris in patients 
12 years and older. Ximino extended-release capsules are expected to be available for patients during the fourth quarter of 2015. For more information, visit www.sunpharma.com.

 

If you would like your product included in Product News, please e-mail a press release to the Editorial Office at cutis@frontlinemedcom.com.

Cyclosporine A

Immune Pharmaceuticals acquires a nanoparticle topical formulation of cyclosporine A for the treatment of psoriasis, atopic dermatitis, pemphigus vulgaris, and other severe inflammatory dermatoses. Researchers have incorporated cyclosporine A into biodegradable nanocapsules and have developed stable topical formulations that are able to achieve therapeutic cyclosporine A levels in the targeted skin layers. This topical treatment provides a potential alternative to oral cyclosporine A and other topical immunosuppressive drugs. For more information, visit www.immunepharmaceuticals.com.


Picato Gel Warning

The US Food and Drug Administration (FDA) issues a warning about reports of severe allergic reactions and herpes zoster associated with the use of Picato Gel (ingenol mebutate) for the treatment of actinic keratosis. The allergic reaction may include throat tightness, difficulty breathing, feeling faint, or swelling of the lips or tongue. The FDA received reports of cases involving severe eye injuries associated with Picato Gel not being used according to the instructions for use on the label. Changes to the labeling have been requested by the FDA to warn about these new safety risks. Patients should not use Picato Gel for a longer period or on an area of skin larger than instructed on the drug label. Patients also should avoid application in, near, and around the mouth, lips, and eye area. For more information, visit www.fda.gov/MedWatch.


Ximino Extended-Release Capsules

Sun Pharmaceutical Industries Ltd announces US Food and Drug Administration approval of the Supplemental New Drug Application for Ximino (minocycline hydrochloride) extended-release 
capsules (45, 90, and 135 mg). Ximino 
extended-release capsules are indicated for the treatment of inflammatory lesions of nonnodular moderate to severe acne vulgaris in patients 
12 years and older. Ximino extended-release capsules are expected to be available for patients during the fourth quarter of 2015. For more information, visit www.sunpharma.com.

 

If you would like your product included in Product News, please e-mail a press release to the Editorial Office at cutis@frontlinemedcom.com.

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Erratum (Cutis. 2015;95:47-51)

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Due to a submission error, the article “Reduced Degree of Irritation During a Second Cycle of Ingenol Mebutate Gel 0.015% for the Treatment of Actinic Keratosis” (Cutis. 2015;95:47-51) contained the incorrect scale for local skin reactions (LSRs). The text in the Methods should have stated:

Using standardized photographic guides, 6 individual LSRs—erythema, flaking/scaling, crusting, 
swelling, vesiculation/pustulation, and erosion/ulceration—were assessed on a scale of 0 (none) to 
4 (severe), with higher numbers indicating more severe reactions.

The staff of Cutis® makes every possible effort to ensure accuracy in its articles and apologizes for the mistake.

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Due to a submission error, the article “Reduced Degree of Irritation During a Second Cycle of Ingenol Mebutate Gel 0.015% for the Treatment of Actinic Keratosis” (Cutis. 2015;95:47-51) contained the incorrect scale for local skin reactions (LSRs). The text in the Methods should have stated:

Using standardized photographic guides, 6 individual LSRs—erythema, flaking/scaling, crusting, 
swelling, vesiculation/pustulation, and erosion/ulceration—were assessed on a scale of 0 (none) to 
4 (severe), with higher numbers indicating more severe reactions.

The staff of Cutis® makes every possible effort to ensure accuracy in its articles and apologizes for the mistake.

Due to a submission error, the article “Reduced Degree of Irritation During a Second Cycle of Ingenol Mebutate Gel 0.015% for the Treatment of Actinic Keratosis” (Cutis. 2015;95:47-51) contained the incorrect scale for local skin reactions (LSRs). The text in the Methods should have stated:

Using standardized photographic guides, 6 individual LSRs—erythema, flaking/scaling, crusting, 
swelling, vesiculation/pustulation, and erosion/ulceration—were assessed on a scale of 0 (none) to 
4 (severe), with higher numbers indicating more severe reactions.

The staff of Cutis® makes every possible effort to ensure accuracy in its articles and apologizes for the mistake.

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