Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury

Key Points Question What is the accuracy of a single-center machine learning algorithm for predicting acute kidney injury (AKI) when internally and externally tested? Findings In this multicenter diagnostic study of approximately 500 000 admissions from 6 hospitals in 3 health systems, the machine learning algorithm had similarly high discrimination in both internal and external validation cohorts. Alert thresholds fired nearly a day and a half before the event. Meaning These findings demonstrate that the AKI algorithm is generalizable to patients in the center in which it was derived and to patients from other hospitals, suggesting that implementation could prompt early identification and therapy aimed at decreasing preventable AKI.