RESUMO
Objective: To explore risk factors for hyperkalemia in hemodialysis (HD) patients, and establish and verify a risk assessment model of hyperkalemia in HD patients. Methods: The clinical data of HD patients who were admitted to the Department of Nephrology of the First Affiliated Hospital of Zhengzhou University between April 2020 and January 2021 were retrospectively collected and divided into training dataset and validation dataset by using the conversion-random number generator. In the training dataset, multivariate logistic regression analysis was used to screen the risk factors for hyperkalemia in HD patients and the factors were scored to establish the risk assessment model. The validation dataset was substituted into the model and the receiver operating characteristic (ROC) curve was drawn and the area under the curve (AUC) was calculated to verify the effectiveness of the risk prediction model in predicting hyperkalemia. Results: A total of 502 HD patients were enrolled and further divided into training dataset (n=372) and validation dataset (n=130). There were 268 males and 234 females, with a mean age of (54±13) years. Multivariate logistic regression analysis showed that metabolic acidosis, high potassium diet, history of hyperkalemia, the change of electrocardiogram (ECG), disfunction of vascular access and time interval from last dialysis were risk factors for causing hyperkalemia in patients undergoing HD. Risk assessment model was established based on these risk factors. The AUC of the ROC curve was 0.799. Using 5 as the cut-off value, the sensitivity and specificity for predicting hyperkalemia events was 61.4% and 86.3%, respectively. Conclusion: The current study preliminarily established a risk assessment model for hyperkalemia in HD patients, which can help clinicians manage the potassium level of HD patients.