Department of Neurology, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Nursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
BMC Geriatr. 2024 Sep 7;24(1):742. doi: 10.1186/s12877-024-05320-7.
To analyze the influential factors of frailty in elderly patients with coronary heart disease (CHD), develop a nomogram-based risk prediction model for this population, and validate its predictive performance.
A total of 592 elderly patients with CHD were conveniently selected and enrolled from 3 tertiary hospitals, 5 secondary hospitals, and 3 community health service centers in China between October 2022 and January 2023. Data collection involved the use of the general information questionnaire, the Frail scale, and the instrumental ability of daily living assessment scale. And the patients were categorized into two groups based on frailty, and χ test as well as logistic regression analysis were used to identify and determine the influencing factors of frailty. The nomograph prediction model for elderly patients with CHD was developed using R software (version 4.2.2). The Hosmer-Lemeshow test and the area under the receiver operating characteristic (ROC) curve were employed to assess the predictive performance of the model. Additionally, the Bootstrap resampling method was utilized to validate the model and generate the calibration curve of the prediction model.
The prevalence of frailty in elderly patients with CHD was 30.07%. The multiple factor analysis revealed that poor health status (OR = 28.169)/general health status (OR = 18.120), age (OR = 1.046), social activities (OR = 0.673), impaired instrumental ability of daily living (OR = 2.384) were independent risk factors for frailty (all P < 0.05). The area under the ROC curve of the nomograph prediction model was 0.847 (95% CI: 0.809 ~ 0.878, P < 0.001), with a sensitivity of 0.801, and specificity of 0.793; the Hosmer- Lemeshow χ value was 12.646 (P = 0.125). The model validation results indicated that the C value of 0.839(95% CI: 0.802 ~ 0.879) and Brier score of 0.139, demonstrating good consistency between predicted and actual values.
The prevalence of frailty is high among elderly patients with CHD, and it is influenced by various factors such as health status, age, lack of social participation, and impaired ability of daily life. These factors have certain predictive value for identifying frailty early and intervention in elderly patients with CHD.
分析老年冠心病（CHD）患者衰弱的影响因素，为该人群构建基于列线图的风险预测模型，并验证其预测性能。
2022 年 10 月至 2023 年 1 月，方便选取中国 3 家三级医院、5 家二级医院和 3 家社区卫生服务中心的 592 例老年 CHD 患者进行研究。使用一般信息问卷、衰弱量表和日常生活能力评估量表收集数据，并根据衰弱情况将患者分为两组，采用 χ 检验和 logistic 回归分析确定衰弱的影响因素。使用 R 软件（版本 4.2.2）构建老年 CHD 患者列线图预测模型。采用 Hosmer-Lemeshow 检验和受试者工作特征（ROC）曲线下面积评估模型的预测性能。此外，还采用 Bootstrap 重采样方法验证模型并生成预测模型的校准曲线。
老年 CHD 患者衰弱的患病率为 30.07%。多因素分析显示，健康状况差（OR=28.169）/一般健康状况（OR=18.120）、年龄（OR=1.046）、社会活动（OR=0.673）、日常生活能力受损（OR=2.384）是衰弱的独立危险因素（均 P<0.05）。列线图预测模型的 ROC 曲线下面积为 0.847（95%CI：0.8090.878，P<0.001），灵敏度为 0.801，特异度为 0.793；Hosmer-Lemeshow χ 值为 12.646（P=0.125）。模型验证结果表明，C 值为 0.839（95%CI：0.8020.879）和 Brier 评分 0.139，表明预测值与实际值之间具有良好的一致性。
老年 CHD 患者衰弱的患病率较高，受健康状况、年龄、缺乏社会参与和日常生活能力受损等多种因素影响。这些因素对早期识别和干预老年 CHD 患者的衰弱具有一定的预测价值。
