Predicting Short-Term Risk of Cardiovascular Events in the Elderly Population: A Retrospective Study in Shanghai, China.

IF 3.7 3区 医学 Q2 GERIATRICS & GERONTOLOGY
Clinical Interventions in Aging Pub Date : 2025-06-12 eCollection Date: 2025-01-01 DOI:10.2147/CIA.S519546
Wenqing Zhu, Shuoyuan Tan, Zhitong Zhou, Miaomiao Zhao, Yingquan Wang, Qi Li, Yang Zheng, Jianwei Shi
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Abstract

Introduction: Cardiovascular diseases (CVD) represents a leading cause of morbidity and mortality worldwide, including China. Accurate prediction of CVD risk and implementation of preventive measures are critical. This study aimed to develop a short-term risk prediction model for CVD events among individuals aged ≥60 years in Shanghai, China.

Methods: Stratified random sampling recruited elderly individuals. Retrospective data (2016-2022) were analyzed using Lasso-Cox regression, followed by a multivariable Cox regression model. The risk scoring was visualized through a nomogram, and the model performance was assessed using calibration plots and receiver operating characteristic curves.

Results: A total of 9,636 individuals aged ≥60 years were included. The Lasso-Cox regression analysis showed male gender (HR=1.482), older age (HR=1.035), higher body mass index (HR=1.015), lower high-density lipoprotein cholesterol (HR=0.992), higher systolic blood pressure (HR=1.009), lower diastolic blood pressure (HR=0.982), higher fasting plasma glucose (HR=1.068), hypertension (HR=1.904), diabetes (HR=1.128), and lipid-lowering medication (HR=1.384) were related to higher CVD risk. The C-index in the training and validation data was 0.642 and 0.623, respectively. Calibration plots indicated good agreement between predicted and actual probabilities.

Conclusion: This short-term predictive model for CVD events among the elderly population exhibits good accuracy but moderate discriminative ability. More studies are warranted to investigate predictors (gender, high-density lipoprotein cholesterol, systolic blood pressure, diastolic blood pressure, hypertension, and lipid-lowering medication) of CVD incidence for the development of preventive measures.

预测老年人心血管事件的短期风险:一项来自中国上海的回顾性研究
导读:心血管疾病(CVD)是包括中国在内的世界范围内发病率和死亡率的主要原因。准确预测心血管疾病风险和实施预防措施至关重要。本研究旨在建立中国上海年龄≥60岁人群心血管疾病事件的短期风险预测模型。方法:分层随机抽样招募老年个体。采用Lasso-Cox回归分析2016-2022年的回顾性数据,并建立多变量Cox回归模型。风险评分通过nomogram可视化,模型性能通过标定图和受试者工作特征曲线进行评估。结果:共纳入9636例年龄≥60岁的个体。Lasso-Cox回归分析显示,男性(HR=1.482)、年龄较大(HR=1.035)、体重指数较高(HR=1.015)、高密度脂蛋白胆固醇较低(HR=0.992)、收缩压较高(HR=1.009)、舒张压较低(HR=0.982)、空腹血糖较高(HR=1.068)、高血压(HR=1.904)、糖尿病(HR=1.128)、降脂药物(HR=1.384)与心血管疾病风险升高相关。训练数据和验证数据的c指数分别为0.642和0.623。校正图显示预测概率与实际概率吻合良好。结论:该老年人群心血管疾病事件的短期预测模型具有较好的准确性,但判别能力较弱。需要更多的研究来调查CVD发病率的预测因素(性别、高密度脂蛋白胆固醇、收缩压、舒张压、高血压和降脂药物),以制定预防措施。
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来源期刊
Clinical Interventions in Aging
Clinical Interventions in Aging GERIATRICS & GERONTOLOGY-
CiteScore
6.80
自引率
2.80%
发文量
193
审稿时长
6-12 weeks
期刊介绍: Clinical Interventions in Aging, is an online, peer reviewed, open access journal focusing on concise rapid reporting of original research and reviews in aging. Special attention will be given to papers reporting on actual or potential clinical applications leading to improved prevention or treatment of disease or a greater understanding of pathological processes that result from maladaptive changes in the body associated with aging. This journal is directed at a wide array of scientists, engineers, pharmacists, pharmacologists and clinical specialists wishing to maintain an up to date knowledge of this exciting and emerging field.
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