Stratification of Older Adults According to Frailty Status and Falls Using Gait Parameters Explored Using an Inertial System

Background: TheWorld Health Organization recommends health initiatives focused on the early detection of frailty and falls. Objectives: 1—To compare clinical characteristics, functional performance and gait parameters (estimated with the G-STRIDE inertial sensor) between different frailty groups in...

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Detalles Bibliográficos
Autores: Neira Álvarez, Marta, Huertas-Hoyas, Elisabet, Novak, Robert, Sipols, Ana Elizabeth, García-Villamil, Guillermo, Rodríguez Sánchez, María Cristina, Del-Ama, Antonio J., Ruiz-Ruiz, Luisa, García-de-Villa, Sara, Jiménez Ruiz, Antonio R.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/365164
Acceso en línea:http://hdl.handle.net/10261/365164
Access Level:acceso abierto
Palabra clave:Gait analysis
Inertial sensors
Early detection
Falls
Frailty
Descripción
Sumario:Background: TheWorld Health Organization recommends health initiatives focused on the early detection of frailty and falls. Objectives: 1—To compare clinical characteristics, functional performance and gait parameters (estimated with the G-STRIDE inertial sensor) between different frailty groups in older adults with and without falls. 2—To identify variables that stratify participants according to frailty status and falls. 3—To verify the sensitivity, specificity and accuracy of the model that stratifies participants according to frailty status and falls. Methods: Observational, multicenter case-control study. Participants, adults over 70 years with and without falls were recruited from two outpatient clinics and three nursing homes from September 2021 to March 2022. Clinical variables and gait parameters were gathered using the G-STRIDE inertial sensor. Random Forest regression was applied to stratify participants. Results: 163 participants with a mean age of 82.6 ± 6.2 years, of which 118 (72%) were women, were included. Significant differences were found in all gait parameters (both conventional assessment and G-STRIDE evaluation). A hierarchy of factors contributed to the risk of frailty and falls. The confusion matrix and the performance metrics demonstrated high accuracy in classifying participants. Conclusions: Gait parameters, particularly those assessed by G-STRIDE, are effective in stratifying individuals by frailty status and falls. These findings underscore the importance of gait analysis in early intervention strategies