Point-of-Care Potassium Measurement vs Artificial Intelligence–Enabled Electrocardiography for Hyperkalemia Detection. - Lin, Chin; Chen, Chien-Chou; Lin, Chin-Sheng; Shang, Hung-Sheng; Lee, Chia-Cheng; Chau, Tom; Lin, Shih-Hua (American Journal of Critical Care, 2025)
Background: Hyperkalemia can be detected by point-of-care (POC) blood testing and by artificial intelligence– enabled electrocardiography (ECG). These 2 methods of detecting hyperkalemia have not been compared. Objective: To determine the accuracy of POC and ECG potassium measurements for hyperkalemia detection in patients with critical illness. Methods: This retrospective study involved intensive care patients in an academic medical center from October 2020 to September 2021. Patients who had 12-lead ECG, POC potassium measurement, and central laboratory potassium measurement within 1 hour were included. The POC potassium measurements were obtained from arterial blood gas analysis; ECG potassium measurements were calculated by a previously developed deep learning model. Hyperkalemia was defined as a central laboratory potassium measurement of 5.5 mEq/L or greater. Results: Fifteen patients with hyperkalemia and 252 patients without hyperkalemia were included. The POC and ECG potassium measurements were available about 35 minutes earlier than central laboratory results. Correlation with central laboratory potassium measurement was better for POC testing than for ECG (mean absolute errors of 0.211 mEq/L and 0.684 mEq/L, respectively). For POC potassium measurement, area under the receiver operating characteristic curve (AUC) to detect hyperkalemia was 0.933, sensitivity was 73.3%, and specificity was 98.4%. For ECG potassium measurement, AUC was 0.884, sensitivity was 93.3%, and specificity was 63.5%. Conclusions: The ECG potassium measurement, with its high sensitivity and coverage rate, may be used initially and followed by POC potassium measurement for rapid detection of life-threatening hyperkalemia.