江苏大学学报（医学版）2025，Vol.35Issue(5)：429-436,8.DOI:10.13312/j.issn.1671-7783.y250017
慢性心力衰竭急性发作患者利尿剂抵抗危险因素分析及预测模型构建
Risk factor analysis and predictive model development for diuretic resistance in patients with acute exacerbation of chronic heart failure
摘要
Abstract
Objective:To investigate the risk factors for diuretic resistance in patients with acute exacerbation of chronic heart failure and to construct a Nomogram model,aiming to provide a reference for the early identification of patients with diuretic resistance.Methods:A retrospective study was designed by including 215 patients with acute exacerbation of chronic heart failure who were admitted to the Affiliated People's Hospital of Jiangsu University from January 2021 to August 2024.Patients were grouped into two groups,one is resistance group,the other non-resistance based on the criteria for diagnosing diuretic resistance,and baseline data were collected for both groups.Using the least absolute shrinkage and selection operator(LASSO)regression for univariate screening,followed by multifactorial Logistic regression for further screening,a nomogram model was constructed and subjected to internal validation.Results:LASSO regression selected 6 variables,and further analysis using multiple Logistic regression revealed that an elevated N-terminal pro B-type natriuretic peptide(NT-proBNP)level was an independent risk factor for diuretic resistance[OR(95%CI):2.342(1.087-5.043),P<0.05],while higher levels of estimated glomerular filtration rate(eGFR),hemoglobin,serum sodium,and left ventricular ejection fraction(LVEF)were identified as protective factors[OR(95%CI):0.978(0.965-0.990),0.973(0.958-0.989),0.893(0.822-0.971),0.944(0.918-0.971),all P<0.05].A nomogram model was constructed based on the above risk factors.The area under the receiver operating characteristic(ROC)curve was 0.846(95%CI:0.795-0.897).The calibration curve and Hosmer-Lemeshow test indicated that the model fit well(P=0.159).The clinical decision curve analysis demonstrated that the model provided a favorable net clinical benefit when the threshold probability ranged from 0%to 87.0%.Conclusion:The Nomogram model,incorporating NT-proBNP,hemoglobin,blood sodium,eGFR,and LVEF,effectively assesses the risk of diuretic resistance in patients with acute exacerbation of chronic heart failure.关键词
慢性心力衰竭/利尿剂抵抗/LASSO回归/Nomogram模型/影响因素Key words
chronic heart failure/diuretic resistance/LASSO regression/Nomogram model/influencing factors分类
医药卫生引用本文复制引用
赵思玉,高渊博,冯松涛,陶艾彬..慢性心力衰竭急性发作患者利尿剂抵抗危险因素分析及预测模型构建[J].江苏大学学报（医学版）,2025,35(5):429-436,8.基金项目
国家自然科学基金资助项目(88197817) （88197817）
