Nanna Michael G, Wojdyla Daniel, Peterson Eric D, Navar Ann Marie, Williamson Jeff D, Colantonio Lisandro D, Wang Stephen Y, Jamil Yasser, Bertoni Alain G, Nahid Musarrat, Damluji Abdulla A, Goyal Parag, Chaudhry Sarwat I, Gill Thomas M, Alexander Karen P
Section of Cardiovascular Medicine, Yale School of Medicine New Haven CT USA.
Duke Clinical Research Institute Durham NC USA.
J Am Heart Assoc. 2025 Jun 3;14(11):e038949. doi: 10.1161/JAHA.124.038949. Epub 2025 May 22.
Guidelines emphasize using atherosclerotic cardiovascular disease (ASCVD) risk prediction models for treatment decisions, but risk of cognitive impairment is an equally important concern in older adults. Current ASCVD risk prediction models were derived in younger adults and do not include holistic measures of health or predict cognitive impairment.
We utilized data from the Framingham, Framingham Offspring, CHS (Cardiovascular Health Study), and ARIC (Atherosclerosis Risk in Communities) cohorts to derive and validate 2 Selective Functional Prediction models to estimate an older person's (aged ≥75 years) risk within 5 years of developing incident: (1) cognitive impairment; and (2) ASCVD, while accounting for the competing risk of death. Variable selection, including functional status, was based on the least absolute shrinkage and selection operator method. The cognitive impairment (N=3466) and ASCVD (N=4403) model populations were split into derivation and validation cohorts with external validation, then performed in MESA (Multi-Ethnic Study of Atherosclerosis).
In the derivation and external validation cohorts (median age, 79 years), 579 (16.7%) and 67 (15.3%) participants developed incident cognitive impairment, respectively; 748 (17.0%) and 80 (8.4%), respectively, experienced an ASCVD event. The cognitive impairment model (baseline Mini-Mental State Examination (MMSE), atrial fibrillation, antidepressant use, mobility impairment, and dependence for grocery shopping) had good discrimination in the internal and external validation cohorts (C index 0.75 and 0.73, respectively). The ASCVD model (employment status, MMSE, aspirin, lipid-lowering medications, blood pressure medications, systolic blood pressure, general health status, high-density lipoprotein cholesterol, triglycerides, creatinine, and mobility impairment) had satisfactory discrimination (C index 0.67) on internal validation and outperformed the pooled cohort equations, but had modest discrimination (C index 0.59) on external validation. Although both models were well calibrated in the internal validation cohorts, they overpredicted risk in the external validation cohort.
Accurate prediction of an older person's risk of developing cognitive impairment is possible, but predicting future ASCVD events remains more challenging.
指南强调使用动脉粥样硬化性心血管疾病（ASCVD）风险预测模型来指导治疗决策，但认知功能障碍风险在老年人中同样是一个重要问题。目前的ASCVD风险预测模型是基于年轻人的数据得出的，未纳入整体健康指标，也无法预测认知功能障碍。
我们利用弗雷明汉、弗雷明汉后代、心血管健康研究（CHS）和社区动脉粥样硬化风险研究（ARIC）队列的数据，推导并验证了2种选择性功能预测模型，以估计老年人（年龄≥75岁）在5年内发生以下事件的风险：（1）认知功能障碍；（2）ASCVD，同时考虑死亡的竞争风险。变量选择（包括功能状态）基于最小绝对收缩和选择算子方法。认知功能障碍模型组（N = 3466）和ASCVD模型组（N = 4403）被分为推导队列和验证队列，并进行外部验证，然后在多族裔动脉粥样硬化研究（MESA）中实施。
在推导队列和外部验证队列（中位年龄79岁）中，分别有579名（16.7%）和67名（15.3%）参与者发生了新发认知功能障碍；分别有748名（17.0%）和80名（8.4%）经历了ASCVD事件。认知功能障碍模型（基线简易精神状态检查表（MMSE）、心房颤动、使用抗抑郁药、行动不便以及购物依赖）在内部和外部验证队列中具有良好的区分度（C指数分别为0.75和0.73）。ASCVD模型（就业状况、MMSE、阿司匹林、降脂药物、血压药物、收缩压、总体健康状况、高密度脂蛋白胆固醇、甘油三酯、肌酐和行动不便）在内部验证中具有令人满意的区分度（C指数0.67），优于合并队列方程，但在外部验证中的区分度一般（C指数0.59）。尽管两个模型在内部验证队列中校准良好，但在外部验证队列中均高估了风险。
准确预测老年人发生认知功能障碍的风险是可能的，但预测未来ASCVD事件仍然更具挑战性。
