Retrospective study identifies five predictors for hypokalemia in STEMI patients

BackgroundHypokalemia is common in patients with ST-segment elevation myocardial infarction (STEMI) and significantly elevates the risk of life-threatening arrhythmias and mortality. Yet no validated prehospital prediction tool exists to identify this high-risk condition early.ObjectiveTo develop and validate a prediction model for hypokalemia in STEMI patients using readily available clinical and electrocardiographic parameters that are fully accessible in prehospital settings, and to systematically evaluate its prehospital application potential.MethodsA retrospective observational study was conducted involving 320 STEMI patients admitted to the Second Affiliated Hospital of Soochow University between January 2023 and December 2024. Patients were categorized into hypokalemia (n = 114) and non-hypokalemia (n = 206) groups based on initial serum potassium levels. Univariate logistic regression, least absolute shrinkage and selection operator (LASSO), and multivariate logistic regression were used to identify independent predictors. A nomogram was constructed and evaluated for discrimination, calibration, and clinical utility.ResultsFive independent predictors were identified: symptom-to-door time (OR = 0.85, 95% CI: 0.78–0.94), syncope/coma (OR = 3.57, 95% CI: 1.12–11.37), atrial arrhythmia (OR = 4.18, 95% CI: 1.33–13.17), PR interval (OR = 1.01, 95% CI: 1.00–1.02), and U wave (OR = 5.20, 95% CI: 2.59–10.46). The prediction model demonstrated good discrimination with an AUC of 0.735 (95% CI: 0.680–0.791). Calibration curves and decision curve analysis confirmed satisfactory model performance and clinical usefulness.ConclusionWe developed and validated a practical nomogram for predicting hypokalemia risk in STEMI patients using five variables readily available in prehospital and emergency settings. This tool enables early risk stratification, facilitates targeted intervention in high-risk individuals, and guides early potassium supplementation. It may improve prehospital care and clinical outcomes in STEMI patients.