张海红,朱秀鸣,汪海娅.209例老年慢性心力衰竭患者远期预后的影响因素Logistic回归分析[J].老年医学与保健,2024,30(5):1296-1302 |
209例老年慢性心力衰竭患者远期预后的影响因素Logistic回归分析 |
Logistic regression analysis of influencing factors for long-term prognosis in 209 elderly patients with chronic heart failure |
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DOI:10.3969/j.issn.1008-8296.2024.05.017 |
中文关键词: 老年 慢性心力衰竭 远期预后 影响因素 NYHA心功能分级 预测模型 Logistic回归分析 |
英文关键词: elderly chronic heart failure long-term prognosis influencing factor NYHA cardiac function grade pre-diction model logistic regression analysis |
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中文摘要: |
目的 209例老年慢性心力衰竭患者远期预后的影响因素Logistic回归分析.方法 对2017年1月-2018年12月上海市浦东新区老年医院209例老年慢性心力衰竭患者作为研究对象进行研究,回顾性收集患者临床资料.比较所有患者临床资料、远期预后情况,采用Logistic回归分析法分析老年慢性心力衰竭患者远期预后不良的影响因素,建立预测模型,并绘制受试者工作特征(ROC)曲线分析预测模型对老年慢性心力衰竭患者远期预后不良的预测价值.结果 209例老年慢性心力衰竭患者,随访5年期间,70例患者死亡,发生率为33.49%(70/209).较预后良好组,预后不良组美国纽约心脏病协会(NYHA)心功能分级为Ⅳ级的患者占比、血清肌肉生长抑制素(MSTN)、肌肉环指蛋白-1(MuRF-1)、N-末端B型利钠肽原(NT-proBNP)、直接胆红素(DBIL)、间接胆红素(IBIL)、总胆红素(TBIL)水平均更高;左室射血分数(LVEF)则更低(P<0.05).Logistic回归分析结果显示,NYHA心功能分级为Ⅳ级、血清MSTN、MuRF-1、NT-proBNP、DBIL、IBIL、TBIL水平异常偏高均为老年慢性心力衰竭患者远期预后不良的影响因素,差异有统计学意义(OR=1.579,1.505,1.480,1.531,1.439,1.374,1.401,P<0.05).将上述因素纳入预测模型:Logit(P)=-8.122+NYHA心功能分级×0.457+血清MSTN水平×0.409+血清MuRF-1水平× 0.392+血清NT-proBNP水平× 0.426+血清DBIL水平×0.364+血清IBIL水平×0.318+血清TBIL水平×0.337+LVEF ×0.226.按照预测模型绘制预测老年慢性心力衰竭患者远期预后不良发生的ROC曲线,结果显示,当Logit(P)>7.635时,曲线下面积(AUC)为0.858,95%CI为0.803~0.902,x2为13.381,诊断敏感度为77.14%、特异度为79.14%.结论 老年慢性心力衰竭患者远期预后不良的影响因素主要为NYHA心功能分级为Ⅳ级、血清MSTN、MuRF-1、NT-proBNP、DBIL、IBIL、TBIL水平异常偏高,在影响因素基础上构建的预测模型具有良好的预测价值,临床可据此对高危人群应采取针对性的防治措施,以改善老年慢性心力衰竭患者远期预后. |
英文摘要: |
Objective To analyze the influencing factors for the long-term prognosis of 209 elderly patients with chronic heart failure by logistic regression.Methods 209 elderly patients with chronic heart failure treated in Geriatrics Hospital in Pu-dong New District from January 2017 to December 2018 were selected as the study subjects,and their clinical data were collect-ed retrospectively.The clinical data and long-term prognosis of all patients were compared.Logistic regression analysis was used to analyze the influencing factors for poor long-term prognosis in elderly patients with chronic heart failure,and then a pre-diction model was established.The receiver operating characteristic(ROC)curve was drawn to analyze the value of the model in predicting poor long-term prognosis in elderly patients with chronic heart failure.Results During 5-year follow-up,70 of 209 elderly patients with chronic heart failure died,with an incidence of 33.49%(70/209).Compared with the good progno-sis group,the proportion of patients with New York Heart Association(NYHA)grade cardiac function Ⅳ,and the levels of serum myostatin(MSTN),muscle ring finger protein-1(MuRF-1),N-terminal B-type natriuretic peptide(NT-proBNP),di-rect bilirubin(DBIL),indirect bilirubin(IB IL)and total bilirubin(TBIL)of the poor prognosis group were higher,but the left ventricular ejection fraction(LVEF)was lower(P<0.05).Logistic regression analysis showed that NYHA cardiac func-tion grade Ⅳ and abnormally high levels of serum MSTN,MuRF-1,NT-proBNP,DBIL,IBIL and TBIL were all influential factors for poor long-term prognosis in elderly patients with chronic heart failure,and the difference was statistically significant(OR=1.579,1.505,1.480,1.531,1.439,1.374,1.401,P<0.05).The above factors were included in the prediction model:Logit(P)=-8.122+NYHA cardiac function grade × 0.457+serum MSTN level × 0.409+serum MuRF-1 level × 0.392+serum NT-proBNP level ×0.426+serum DBIL level ×0.364+serum IBIL level ×0.318+serum TBIL Level ×0.337+LVEF ×0.226.The ROC curve for predicting poor long-term prognosis in elderly patients with chronic heart failure was drawn according to the predictive model.The results showed that when Logit(P)was>7.635,the area under the curve(AUC)was 0.858,95%CI was 0.803-0.902,x2 was 13.381,the diagnostic sensitivity was 77.14%,and the specificity was 79.14%.Conclusion The main influencing factors for poor long-term prognosis in elderly patients with chronic heart failure were NY-HA cardiac function grade Ⅳ and abnormally high levels of serum MSTN,MuRF-1,NT-proBNP,DBIL,IBIL and TBIL The predictive model constructed based on these influencing factors has good predictive value There fore,in clinical practice,targe-ted prevention and treatment measures should be taken for high-risk populations to improve the long-term prognosis of elderly patients with chronic heart failure. |
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