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Multivariate Profiling of Physical Resilience in Older Adults After Total Knee Replacement Surgery

仿形(计算机编程) 多元统计 多元分析 弹性(材料科学) 医学 老年学 物理疗法 心理学 计算机科学 内科学 统计 数学 物理 热力学 操作系统
作者
Qian‐Li Xue,Thomas Laskow,Mallak Alzahrani,Ravi Varadhan,Jeremy Walston,Jennifer A. Schrack,Anne B. Newman,Frederick E. Sieber,Karen Bandeen‐Roche
出处
期刊:Cold Spring Harbor Laboratory - medRxiv
标识
DOI:10.1101/2024.10.03.24314863
摘要

IMPORTANCE As individuals age, they often face a variety of health challenges. Physical resilience indicates how well a person can cope with and recover from physical challenges, which is crucial for maintaining independence and quality of life in older age. OBJECTIVE To develop a multivariate phenotype of physical resilience based on individual recovery dynamics before and after a clinical stressor. DESIGN, SETTING, AND PARTICIPANTS This observational study included 112 individuals aged 60 and older who underwent elective total knee replacement for degenerative joint disease between December 2, 2019, and January 4, 2023. Physical function was assessed before surgery and at 1, 6, and 12 months post-surgery to characterize resilience trajectories. EXPOSURE Elective total knee replacement surgery for degenerative joint disease. MAIN OUTCOMES AND MEASURES A multivariate resilience phenotype was derived from physical function trajectories assessed using the Short Physical Performance Battery, the Pittsburgh Fatigability Scale-Physical Subscale, the KOOS Quality of Life, and the SF36-Physical Component Score. This phenotype was validated against surrogate markers (i.e., frailty, self-reported health) and determinants (e.g., the Charlson Comorbidity Index) of recovery potential (aka resilience capacity). RESULTS The study identified distinct resilience profiles across four measures: 4 profiles for the Short Physical Performance Battery and the KOOS Quality of Life, 3 each for the Pittsburgh Fatigability Scale-Physical Subscale and the SF36-Physical Component Score, showing varied baseline levels and/or change rates over 12 months. By combining and analyzing resilience profiles across measures, two distinct groups emerged: 35.7% classified as non-resilient and 64.3% as resilient. The non-resilient group had a higher prevalence of frailty (35.0% vs. 9.7%, p<0.01), poor or fair self-reported health (45.0% vs. 5.6%, p<0.01), and a moderate/severe comorbidity burden (Charlson Comorbidity Index >2; 27.5% vs. 11.1%, p=0.06). CONCLUSIONS AND RELEVANCE The distinct recovery trajectories observed after the surgery indicated varying resilience levels that were not fully explained by baseline status. This research underscores the importance of resilience in surgical recovery and could pave the way for better patient care by focusing on individual resilience capacities and shifting the focus from managing health conditions to promoting recovery and overall well-being.

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