| 高血压合并心力衰竭预测模型的构建及验证 |
| 投稿时间：2024-08-21 修订日期：2024-12-01 点此下载全文 |
| 引用本文：吴梦媛,杜子琛,李娇,魏丽萍.高血压合并心力衰竭预测模型的构建及验证[J].医学研究杂志,2025,54(4):77-83 |
| DOI：
10.11969/j.issn.1673-548X.2025.04.015 |
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| 基金项目:天津市科技计划项目(面上项目)(23JCYBJC01470)；天津市卫生健康科技项目(TJWJ2022QN037)；天津市人民医院重点课题(2023YJZD003) |
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| 中文摘要:目的 构建高血压患者发生心力衰竭(heart failure,HF)的预测模型,用列线图展示,并验证其效能。方法 采用回顾性研究方法收集2019年1月～2021年12月在天津市人民医院心脏内科就诊的1500例高血压患者临床数据,数据集按照7∶3的比例分为训练集(n=1050)和验证集(n=450),将训练集分为HF组(n=144)和非HF组(n=906)。对训练集的数据采用单因素Logistic回归、最小绝对值收缩和选择算子(least absolute shrinkage and selection operator,LASSO)回归及多因素Logistic回归的方法来筛选HF发生的危险因素,构建风险预测模型,通过R语言制作列线图,分别采用受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under the curve,AUC)、校准曲线、Hosmer-Lemeshow拟合优度检验、决策曲线分析(decision curve analysis,DCA)评价模型的区分度、校准度和临床适用性。结果 研究发现,年龄、冠心病史、尿酸(uric acid,UA)、红细胞分布宽度(red blood cell distribution width,RDW)、尿素氮/白蛋白(blood urea nitrogen to albumin ratio,BAR)和中性粒细胞/淋巴细胞(neutrophil-to-lymphocyte ratio,NLR)是高血压患者发生HF的独立预测因子(P<0.05),用这6个指标构建风险预测模型,结果显示训练集AUC为0.864(95% CI:0.831～0.896),Hosmer-Lemeshow检验χ2=10.29,P=0.25；验证集AUC为0.842(95% CI:0.794～0.891),Hosmer-Lemeshow检验χ2=10.48,P=0.23。DCA曲线均显示该预测模型可为患者带来临床净收益。结论 本研究构建了针对高血压患者发生HF的风险预测模型,并用列线图直观展示,有助于早期识别HF高危患者,为早期防治和改善预后提供依据。 |
| 中文关键词:高血压 心力衰竭 预测模型 列线图 |
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| Development and Validation of a Predictive Model for Heart Failure in the People with Hypertension. |
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| Abstract:Objective To establish and validate a risk model for predicting heart failure(HF) in patients with hypertension. Methods The clinical data of 1500 patients with hypertension in Department of Cardiology of Tianjin Union Medical Center from January 2019 to December 2021 were retrospectively collected. The dataset was randomly partitioned into a training set (n=1050) and a validation set (n=450) at a ratio of 7∶3. Then, the patients of training set were segmented into heart failure group(n=144) or non-heart failure group(n=906). The univariate Logistic regression, least absolute shrinkage and selection operator (LASSO) regression model and multivariate Logistic regression analysis were used for screening the risk factors and developing model. The R software was used to construct a nomogram. The discrimination ability of the model was determined by the area under the receiver operating characteristic curve (AUC), the calibration degree was evaluated by the calibration plot and Hosmer-Lemeshow goodness-of-fit test. Decision curve analysis (DCA) was performed to assess the clinical utility. Results This study showed that age, coronary heart disease, uric acid (UA), red blood cell distribution width (RDW),blood urea nitrogen/albumin ratio (BAR) and neutrophil to lymphocyte ratio (NLR) are independent predictors of the development of HF in patients with hypertension. A predictive model was constructed using the above six predictive factors. In the training set, the model had an AUC value of 0.864(95% CI:0.831-0.896), Hosmer-Lemeshow goodness of fit test showedχ2=10.29, P=0.25. In the validation set, the AUC value was 0.842(95% CI:0.794-0.891), Hosmer-Lemeshow goodness of fit test showedχ2=10.48, P=0.23. The clinical decision analysis also showed that the nomogram model had a better clinical performance and could bring net clinical benefits to the patients. Conclusion This study successfully constructs a predictive model for the risk of HF in adults with hypertension and it can effectively identify patients at high risk of HF and formulate targeted intervention measures, thereby providing a basis for performing early prevention and treatment and improving prognosis. |
| keywords:Hypertension Heart failure Predictive model Nomogram |
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