Risk Factors and Prediction Model for Hypokalemia as a Complication in Older Adults with Acute Cerebral Hemorrhage

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Objective: This study aimed to identify the key risk factors for hypokalemia in older adults with acute cerebral hemorrhage (ACH) and to develop a clinically practical risk predictive model based on logistic regression. Methods: A total of 209 older adult ACH patients (age 60-82 years) treated at The First Hospital of Hebei Medical University from July 2022 to July 2024 were included in this retrospective cohort study. Patients were divided into two groups: hypokalemic (serum potassium < 3.5 mmol/L, n = 56) and normokalemic (serum potassium 3.5-5.5 mmol/L, n = 153). Clinical outcomes were compared, and logistic regression was used to identify risk factors for hypokalemia. A risk prediction model was constructed and presented as a nomogram. The diagnostic value of the model was assessed using receiver operating characteristic (ROC) curves. Results: (OR=2.316), and furosemide use > 20 mg/d (OR=2.351) as independent risk factors for hypokalemia. ROC analysis showed an area under the curve (AUC) for the multivariable predictive model of 0.859, which was superior to individual predictors. Conclusion: ), and use of furosemide > 20 mg/d are significant independent risk factors for hypokalemia in older adult ACH patients. Given its association with adverse outcomes, early prediction is crucial. The predictive model and corresponding nomogram provide a practical tool for identifying high-risk patients, facilitating timely intervention.

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