Construction of risk prediction model for hyponatremia in patients with acute decompensated heart failure

BACKGROUND: Patients with Heart failure (HF) commonly have a water-electrolyte imbalance due to various reasons and mechanisms, and hyponatremia is one of the most common types. However, currently, there are very few local studies on hyponatremia risk assessment in patients with acute decompensated heart failure (ADHF), and there is a lack of specific screening tools. The aim of this study is to identify a prediction model of hyponatremia in patients with acute decompensated heart failure (ADHF) and verify the prediction effect of the model. METHODS: A total of 532 patients with ADHF were enrolled from March 2014 to December 2019. Univariate and multivariate logistic regression analyses were performed to investigate the independently associated risk factors of hyponatremia in patients with ADHF. The prediction model of hyponatremia in patients with ADHF was constructed by R software, and validation of the model was performed using the area under the receiver operating characteristic curve (AUC) and calibration curves. RESULTS: A total of 65 patients (12.2%) had hyponatremia in patients with ADHF. Multivariate logistic regression analysis demonstrated that NYHA cardiac function classification (NYHA III vs II, OR = 12.31, NYHA IV vs II, OR = 11.55), systolic blood pressure (OR = 0.978), serum urea nitrogen (OR = 1.046) and creatinine (OR = 1.006) were five independent prognostic factors for hyponatremia in patients with ADHF. The AUC was 0.757; The calibration curve was near the ideal curve, which showed that the model can accurately predict the occurrence of hyponatremia in patients with ADHF. CONCLUSIONS: The prediction model constructed in our study has good discrimination and accuracy and can be used to predict the occurrence of hyponatremia in patients with ADHF.