Nephrolithiasis affects 1 in 11 people in the United States resulting in several million emergency department visits annually. The prevalence of nephrolithiasis is higher among men, obese individuals, and white non-Hispanics. The prevalence of kidney stones also appears to be increasing.
Our patients tell us that few things hurt worse than kidney stones. We may feel especially compelled to make a diagnosis given pain severity in otherwise healthy adults who have "never experienced this kind of pain before." Perhaps because of this, lots of patients are undergoing CT imaging for kidney stones ... in the United States. Interestingly, the European Urology Association recommends ultrasonography as the first-line test for urolithiasis.
Can we predict who has a kidney stone?
Moore and colleagues derived and validated a clinical prediction rule for uncomplicated ureteral stone. The derivation cohort was 1,040 patients undergoing noncontrast CT for suspected uncomplicated kidney stone. The validation cohort was 491 consecutively enrolled patients.
Data analysis revealed five factors that were significantly associated with the presence of a ureteral stone: male sex (2 points), duration of pain to presentation (greater than 24 hours: 0 points; 6-24 hours: 1 point; less than 6 hours: 3 points), nonblack race (3 points), presence of nausea or vomiting (nausea alone: 1 point; vomiting alone: 2 points), and microscopic hematuria (3 points). The points add up to low probability (0-5 points = 10% chance of stone), moderate probability (6-9 points = about 50% chance of stone), and high probability (10-13 points = about 90% chance of stone). Acutely important alternative causes were found in 1.6% of the high-probability group in the validation set. These causes were diverticulitis, appendicitis, mass, pyelonephritis, cholecystitis, pneumonia, bowel obstruction, colitis, aortic aneurysm, and pancreatitis.
This algorithm was derived and validated in the emergency setting so it will have different performance characteristics in the outpatient, ambulatory, phone-triage world. However, as the authors discuss, this algorithm could be used to help institutions make decisions about lowering radiation doses for "stone protocol" scans. Scales such as these should be incorporated into electronic medical record systems to improve care delivery.
Dr. Ebbert is professor of medicine, a general internist at the Mayo Clinic in Rochester, Minn., and a diplomate of the American Board of Addiction Medicine. The opinions expressed are those of the author. He reports no disclosures.