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Clinical decision rule identifies AKI patients at low risk for hydronephrosis

Clinical Question:
In hospitalized patients with acute kidney injury, can a simple decision rule aid clinicians in determining the need for renal ultrasonography based on the patients? risk of obstruction?

Bottom Line:
Seven clinical factors combined into a single score can identify patients at low risk for obstructive kidney disease as a cause of acute kidney injury (AKI). Applying this decision rule to hospitalized patients can help clinicians avoid unnecessary renal ultrasonography. (LOE = 2b)

Reference:
Licurse A, Kim MC, Dziura J, et al. Renal ultrasonography in the evaluation of acute kidney injury. Arch Intern Med 2010:170(21):1900-1907.  [PMID:21098348]

Study Design:
Decision rule (validation)

Funding:
Foundation

Setting:
Inpatient (any location)

Synopsis:
These authors developed a prediction model for the risk of hydronephrosis (HN) by analyzing clinical data from 200 patients with suspected AKI who underwent renal ultrasonography: 100 patients with HN and 100 patients without HN. The mean age of participants was 66 years and 57% were men. The authors identified the 7 best predictors of HN as a cause of AKI: previous history of HN, recurrent urinary tract infections, diagnosis consistent with possible obstruction, nonblack race, lack of exposure to inpatient nephrotoxins, absence of congestive heart failure, and absence of prerenal AKI. Having a previous history of HN alone placed a patient in the high-risk category for HN. The remaining factors were given 1 point each, for a combined score resulting in 3 risk groups: low risk for HN = 2 points or less; medium risk = 3 points; and high risk = more than 3 points. This model was then validated retrospectively on a group of 797 patients with suspected AKI who underwent renal ultrasonography. In this validation cohort, the prevalence of HN was 3.1% in the low-risk group, 10.7% in the medium-risk group, and 16.1% in the high-risk group. Using this data, the prediction model had a sensitivity of 91.8%, a specificity of 30.3%, and negative predictive value of 96.9%. When the study outcome was further specified as HN requiring surgical intervention, the sensitivity and negative predictive value were even higher at 96.3% and 99.6%, respectively. In other words, if your patient falls into the low-risk category, you can essentially rule out HN as a cause of AKI and thus avoid unnecessary testing. The authors recommend future prospective studies to further validate this rule.

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