A retrospective study of acute kidney injury in cats and development of a novel clinical scoring system for predicting outcome for cats managed by hemodialysis.

Abstract

BACKGROUND: Information regarding acute kidney injury (AKI) in cats is limited, and there are no reliable tools to objectively assess disease severity and predict outcome. OBJECTIVES: To assess clinical signs, clinicopathologic abnormalities, etiology, and outcome of cats with AKI, and to develop models using clinical metrics and empirically derived scores to predict outcome. ANIMALS: One hundred and thirty-two client-owned cats. METHODS: Retrospective study. Bivariate logistic regression analyses were performed to identify variables predictive of 30-day survival. Continuous variables outside the reference range were divided into quartiles to yield quartile-specific odds ratios (OR) for survival. Models were developed incorporating weighting factors assigned to each quartile based on the OR. A predictive score for each model was calculated for each cat by summing all weighting factors. A second, multivariable logistic regression model was created from actual values of the same variables. Receiver operating characteristic curve analyses were performed to determine the models' performance. Models were further tested using a subset of cases not used in initial assessment. RESULTS: Fifty five of 132 cats (42%) remained dialysis-independent for at least 30 days after discharge, and the remaining 77 cats either died (n = 37, 28%) or were euthanized (n = 40, 30%). The most common etiology was ureteral obstruction (n = 46, 35%). Higher scores were associated with decreased probability of survival (P < .001). Models correctly classified outcomes in 75-77% of the cases and 84-89% of the cases in the subsequent evaluation. CONCLUSIONS AND CLINICAL IMPORTANCE: Models can provide objective guidance in assessing AKI prognosis and severity, but should be validated in other cohorts of cats.