Abstract：Objective: To analyze the factors related to poor prognosis in chronic heart failure (CHF) and construct a risk model for poor prognosis. Methods: A retrospective analysis was conducted on 216 CHF patients. Patients were divided into good prognosis and poor prognosis groups based on the NYHA classification. Baseline characteristics and admission indicators were compared between the two groups. Logistic regression analysis was used to identify independent risk factors associated with adverse prognosis. Results: Patients in the poor prognosis group were older, had longer hospital stays, and higher NYHA classes. They also had lower weight, systolic blood pressure, and levels of potassium, sodium, and chloride. Multivariate logistic regression analysis showed that older age, longer hospital stay, and higher NYHA class were independent risk factors for adverse prognosis, while higher systolic blood pressure, weight, sodium, chloride, and potassium levels were protective factors. A risk model based on sodium levels had a high predictive value for adverse prognosis. Conclusion: The established risk model can be used to predict adverse outcomes in CHF patients. Early identification of high-risk patients and targeted interventions can improve the prognosis of CHF patients.
2024, Vol. 30 
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