Update on the detection of frailty in older adults: a multicenter cohort machine learning-based study protocol.

IF 3.9 3区 医学 Q2 CELL BIOLOGY
Aging-Us Pub Date : 2025-05-21 DOI:10.18632/aging.206254
Samuel Fernández-Carnero, Oliver Martínez-Pozas, Daniel Pecos-Martín, Armando Pardo-Gómez, Juan Nicolás Cuenca-Zaldívar, Eleuterio A Sánchez-Romero
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Abstract

Background: This study aims to investigate the relationship between muscle activation variables assessed via ultrasound and the comprehensive assessment of geriatric patients, as well as to analyze ultrasound images to determine their correlation with morbimortality factors in frail patients.

Methods: The present cohort study will be conducted in 500 older adults diagnosed with frailty. A multicenter study will be conducted among the day care centers and nursing homes. This will be achieved through the evaluation of frail older adults via instrumental and functional tests, along with specific ultrasound images to study sarcopenia and nutrition, followed by a detailed analysis of the correlation between all collected variables.

Discussion: This study aims to investigate the correlation between ultrasound-assessed muscle activation variables and the overall health of geriatric patients. It addresses the limitations of previous research by including a large sample size of 500 patients and measuring various muscle parameters beyond thickness. Additionally, it aims to analyze ultrasound images to identify markers associated with higher risk of complications in frail patients. The study involves frail older adults undergoing functional tests and specific ultrasound examinations. A comprehensive analysis of functional, ultrasound, and nutritional variables will be conducted to understand their correlation with overall health and risk of complications in frail older patients.

Trial registration: The study was approved by the Research Ethics Committee of the Hospital Universitario Puerta de Hierro, Madrid, Spain (Act nº 18/2023). In addition, the study was registered with https://clinicaltrials.gov/ (NCT06218121).

老年人虚弱检测的最新进展:基于机器学习的多中心队列研究方案。
背景:本研究旨在探讨超声评估的肌肉激活变量与老年患者综合评估的关系,并分析超声图像以确定其与虚弱患者病死率因素的相关性。方法:本队列研究将在500名被诊断为虚弱的老年人中进行。一项多中心研究将在日托中心和疗养院进行。这将通过仪器和功能测试对虚弱的老年人进行评估,同时使用特定的超声图像来研究肌肉减少症和营养,然后详细分析所有收集到的变量之间的相关性。讨论:本研究旨在探讨超声评估的肌肉激活变量与老年患者整体健康状况之间的相关性。它解决了以往研究的局限性,包括500名患者的大样本量,并测量了厚度以外的各种肌肉参数。此外,它旨在分析超声图像,以确定与体弱患者并发症高风险相关的标志物。这项研究涉及体弱多病的老年人,他们接受了功能测试和特定的超声波检查。将对功能、超声和营养变量进行综合分析,以了解它们与体弱老年患者整体健康状况和并发症风险的相关性。试验注册:该研究已获得西班牙马德里耶罗门大学医院研究伦理委员会的批准(第18/2023号法案)。此外,本研究已在https://clinicaltrials.gov/注册(NCT06218121)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Aging-Us
Aging-Us CELL BIOLOGY-
CiteScore
10.00
自引率
0.00%
发文量
595
审稿时长
6-12 weeks
期刊介绍: Information not localized
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