Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081, BT, Amsterdam, The Netherlands.
Laboratory of Clinical Epidemiology, InCHIANTI Study Group, LHTC Local Health Tuscany Center, Firenze, Italy.
BMC Geriatr. 2019 Jun 27;19(1):179. doi: 10.1186/s12877-019-1192-1.
Identifying those people at increased risk of early functional decline in activities of daily living (ADL) is essential for initiating preventive interventions. The aim of this study is to develop and validate a clinical prediction model for onset of functional decline in ADL in three years of follow-up in older people of 65-75 years old.
Four population-based cohort studies were pooled for the analysis: ActiFE-ULM (Germany), ELSA (United Kingdom), InCHIANTI (Italy), LASA (Netherlands). Included participants were 65-75 years old at baseline and reported no limitations in functional ability in ADL at baseline. Functional decline was assessed with two items on basic ADL and three items on instrumental ADL. Participants who reported at least some limitations at three-year follow-up on any of the five items were classified as experiencing functional decline. Multiple logistic regression analysis was used to develop a prediction model, with subsequent bootstrapping for optimism-correction. We applied internal-external cross-validation by alternating the data from the four cohort studies to assess the discrimination and calibration across the cohorts.
Two thousand five hundred sixty community-dwelling people were included in the analyses (mean age 69.7 ± 3.0 years old, 47.4% female) of whom 572 (22.3%) reported functional decline at three-year follow-up. The final prediction model included 10 out of 22 predictors: age, handgrip strength, gait speed, five-repeated chair stands time (non-linear association), body mass index, cardiovascular disease, diabetes, chronic obstructive pulmonary disease, arthritis, and depressive symptoms. The optimism-corrected model showed good discrimination with a C statistic of 0.72. The calibration intercept was 0.06 and the calibration slope was 1.05. Internal-external cross-validation showed consistent performance of the model across the four cohorts.
Based on pooled cohort data analyses we were able to show that the onset of functional decline in ADL in three years in older people aged 65-75 years can be predicted by specific physical performance measures, age, body mass index, presence of depressive symptoms, and chronic conditions. The prediction model showed good discrimination and calibration, which remained stable across the four cohorts, supporting external validity of our findings.
识别那些日常生活活动(ADL)功能早期下降风险较高的人群对于启动预防干预至关重要。本研究旨在为 65-75 岁老年人制定并验证一个可预测三年内 ADL 功能下降的临床预测模型。
本分析纳入了四项基于人群的队列研究:ActiFE-ULM(德国)、ELSA(英国)、InCHIANTI(意大利)和 LASA(荷兰)。纳入的研究对象在基线时年龄为 65-75 岁,且在基线时报告 ADL 无功能障碍。功能下降通过两项基本 ADL 项目和三项工具性 ADL 项目进行评估。在三年随访时,任何五项项目中至少有一项报告存在功能障碍的参与者被归类为经历功能下降。采用多因素逻辑回归分析建立预测模型,随后采用自举法进行乐观性校正。我们通过交替使用四个队列研究的数据进行内部-外部交叉验证,以评估跨队列的区分度和校准度。
本研究共纳入了 2560 名居住在社区的参与者(平均年龄 69.7±3.0 岁,47.4%为女性),其中 572 名(22.3%)在三年随访时报告存在功能下降。最终的预测模型纳入了 22 个预测因素中的 10 个:年龄、握力、步速、五次椅站时间(非线性关联)、体重指数、心血管疾病、糖尿病、慢性阻塞性肺疾病、关节炎和抑郁症状。经乐观性校正后的模型具有良好的区分度,C 统计值为 0.72。校准截距为 0.06,校准斜率为 1.05。内部-外部交叉验证表明,该模型在四个队列中的表现一致。
基于队列研究数据的分析,我们发现 65-75 岁老年人三年内 ADL 功能下降的发生可以通过特定的身体表现测量、年龄、体重指数、抑郁症状和慢性疾病来预测。该预测模型具有良好的区分度和校准度,在四个队列中均表现稳定,支持研究结果的外部有效性。