A simple model to predict bacteremia in women with acute pyelonephritis

SummaryObjectivesTo construct a simple model to predict bacteremia in women with uncomplicated acute pyelonephritis (APN) for the judicious use of blood cultures.MethodsA prospective database including 735 women with uncomplicated APN at an academic urban emergency department was analyzed retrospectively. Independent risk factors were determined using multivariate logistic regression in two-thirds of patients. Cutoff values representing 10% and 30% of risk were selected for the stratification. This model was internally and externally validated using a remaining one-thirds of patients and 169 independent patients, respectively.ResultsIndependent risk factors were as follows: age ≥65 years (odds ratio [OR]=5.18, 4 points), vomiting (OR = 2.40, 2 points), heart rate >110 beats/min (OR = 2.35, 2 points), segmented neutrophils >90% (OR = 3.17, 3 points), and urine WBC ≥50/HPF (OR = 4.27, 4 points). Patients were stratified as low (points <4), intermediate (points, 4–6), or high risk (7≤ points). The areas under receiver operating characteristics curves were 0.707 and 0.792 in internal and external validation cohorts, respectively. The model stratified internal and external validation cohort into low (8.5% and 5.7%), intermediate (16.5% and 14.8%), and high risk of bacteremia (42.0% and 56.4%).ConclusionsThis model provides a useful tool to predict the risk of bacteremia, which can be helpful to decide whether to perform blood cultures and whether to admit the patient for the intravenous antibiotics in women with uncomplicated APN.

► There is no consensus whether to perform blood culture in acute pyelonephritis.
► We derive a model to predict bacteremia in women with acute pyelonephritis.
► Five variables are selected and corresponding points are assigned for the model.
► Derived model performs well in internal and external validation cohorts.
► This model will be helpful to manage women with acute pyelonephritis.