双感官障碍人群心血管疾病风险的预测模型:基于CHARLS的分析

doi:10.6040/j.issn.1673-3770.0.2024.638

摘要/Abstract

摘要： 目的基于中国健康与退休纵向研究(china health and retirement longitudinal study, CHARLS)数据库的资料,建立双感官障碍人群发生心血管疾病(cardiovascular disease, CVD)的预测模型。方法纳入来自CHARLS的2011年队列中 ≥45 岁,发生双感官障碍且无CVD为基线人群,2013年、2015年、2018年及2020年随访的CVD情况作为结局变量。应用LASSO回归和Logistic回归筛选模型中最佳预测因子,构建预测模型。随后,将研究人群以75%到25%的比例随机分为训练集和验证集。通过 ROC 曲线、校准曲线和决策曲线分析评估预测性能。结果共纳入5 866名双感官障碍参与者,CVD发生率为16%(938/5 866)。Lasso回归和多因素Logistic回归筛选年龄、性别、睡眠时长、血脂异常、肾病、腰围、体质量指数(body mass index, BMI)和糖尿病作为预测因素构建预测模型,公式为:0.027 40×年龄-0.052 52×性别-0.073 61×睡眠时长+0.153 26×BMI-0.372 05×血脂异常-0.057 37×糖尿病-0.252 30×肾病-0.014 67×腰围。该模型的AUC值在训练集中为0.729,验证集中为0.692。结论本研究构建成功一个用于评估双感官障碍人群发生CVD的风险预测模型。

关键词: 感官障碍, 心血管疾病, 影响因素, 预测模型

Abstract: Objective To establish a prediction model of cardiovascular disease(CVD)in people with dual sensory impairment based on the data of CHARLS database. Methods A cohort from China Longitudinal Study on Health and Retirement(CHARLS)in 2011 was included. The baseline population was people over 45 years of age with dual sensory impairment and no CVD, and the follow-up CVD in 2013, 2015, 2018 and 2020 was used as the outcome variable. LASSO regression and Logistic regression were used to screen the best predictors in the model, and a prediction model was constructed. Then, the research population was randomly divided into training set and verification set at the ratio of 75% to 25%. The prediction performance is evaluated by ROC curve, calibration curve and decision curve analysis. Results A total of 5866 participants with double sensory impairment were included, and the incidence of CVD was 16%(938/5866). Lasso regression and multivariate logistic regression selected age, sex, sleep duration, dyslipidemia, nephropathy, waist circumference, BMI and diabetes as predictors to build a prediction model, and the formula was: 0.027 40×age-0.052 52×gender-0.073 61×sleep duration+0.153 26×BMI-0.372 05×dyslipidemia -0.057 37×diabetes -0.252 30×nephropathy-0.014 67×waist circumference. The AUC value of the model was 0.729 in the training set and 0.692 in the verification set. Conclusion In this study, a prediction model was established to evaluate the risk of CVD in people with double sensory impairment.

Key words: Sensory impairment, Cardiovascular disease, Influencing factor, Prediction model

中图分类号:

R543

吕勇,冯云. 双感官障碍人群心血管疾病风险的预测模型:基于CHARLS的分析[J]. 山东大学耳鼻喉眼学报, 2025, 39(3): 122-128.

LYU Yong, FENG Yun. Prediction model of cardiovascular disease risk in people with dual sensory impairment: analysis based on CHARLS[J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2025, 39(3): 122-128.

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