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

Author:

Neira Álvarez Marta1ORCID,Huertas-Hoyas Elisabet2ORCID,Novak Robert3ORCID,Sipols Ana Elizabeth3ORCID,García-Villamil-Neira Guillermo4,Rodríguez-Sánchez M. Cristina5ORCID,Del-Ama Antonio J.5ORCID,Ruiz-Ruiz Luisa46ORCID,De Villa Sara García7ORCID,Jiménez-Ruiz Antonio R.4ORCID

Affiliation:

1. Department of Geriatrics, Foundation for Research and Biomedical Innovation of the Infanta Sofía University Hospital (FIIB HUIS), 28055 Madrid, Spain

2. Physical Therapy, Occupational Therapy, Rehabilitation, and Physical Medicine Department, Rey Juan Carlos University, 28922 Madrid, Spain

3. Department of Applied Mathematics, Materials Science and Engineering and Electronic Technology, Rey Juan Carlos University, 28933 Madrid, Spain

4. Centre for Automation and Robotics, Spanish National Research Council (CSIC-UPM,) Arganda del Rey, 28500 Madrid, Spain

5. School of Experimental Sciences and Technology, Rey Juan Carlos University, 28933 Madrid, Spain

6. Politécnica Superior School, Electronics Department, Alcalá University, 28805 Madrid, Spain

7. Department of Signal Theory and Communications, Rey Juan Carlos University, 28942 Fuenlabrada, Spain

Abstract

Background: The World 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.

Funder

G-STRIDE de la Convocatoria Fundación Mapfre

MCIU/AEI/FEDER, UE

laboratories SENIALAB (Laboratorio de sistemas de navegación sensorial y de sistemas de monitorización) of the REDLABU of the Universidad Rey Juan Carlos and CAR-CSIC

Publisher

MDPI AG

Reference48 articles.

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2. Global ageing: Successes, challenges and opportunities;Mitchell;Br. J. Hosp. Med.,2020

3. Fried, L.P., Tangen, C.M., Walston, J., Newman, A.B., Hirsch, C., Gottdiener, J., Seeman, T., Tracy, R., Kop, W.J., and Burke, G. (2021). Frailty in older adults: Evidence for a phenotype. J. Gerontol. A Biol. Sci. Med. Sci.

4. Falls in older people: Epidemiology, risk factors and strategies for prevention;Rubenstein;Age Ageing,2006

5. Falls and Fall Injuries Among Adults Aged ≥65 Years—United States. 2014;Bergen;MMWR Morb. Mortal. Wkly. Rep.,2016

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