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

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: Hypokalemia was associated with significantly higher in-hospital mortality, poorer functional outcomes, longer hospital stays, and more frequent neurological deterioration (all P < 0.05). Univariate and multivariate logistic regression identified female gender (OR=2.713), higher NIHSS scores at admission (OR=2.375), GFR ≤ 60 mL/min/1.73 m2 (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: Female gender, higher neurological deficit severity (NIHSS score), impaired renal function (GFR ≤ 60 mL/min/1.73 m2), 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.