Neira Alvarez, MartaHuertas Hoyas, ElisabethNovak, RobertSipols, Ana ElizabethGarcía-Villamil-Neira, GuillermoRodríguez-Sánchez, M. CristinaJ. Del-Ama, AntonioRuiz Ruiz, LuisaGarcía De Villa, SaraR. Jiménez-Ruiz, Antonio2024-11-072024-11-072024-08-01Neira Álvarez, M.; Huertas-Hoyas, E.; Novak, R.; Sipols, A.E.; García-Villamil-Neira, G.; Rodríguez-Sánchez, M.C.; Del-Ama, A.J.; Ruiz-Ruiz, L.; De Villa, S.G.; Jiménez-Ruiz, A.R. Stratification of Older Adults According to Frailty Status and Falls Using Gait Parameters Explored Using an Inertial System. Appl. Sci. 2024, 14, 6704. https://doi.org/10.3390/app141567042076-3417https://hdl.handle.net/10115/41229The World Health Organization advocates for health initiatives focused on the early detection of frailty and falls. Objectives: 1—To compare clinical characteristics, functional performance, and gait parameters (measured with the G-STRIDE inertial sensor) among different frailty groups in older adults with and without falls. 2—To identify variables that differentiate participants based on frailty status and fall history. 3—To assess the sensitivity, specificity, and accuracy of a model that classifies participants according to frailty and fall status. Methods: This observational, multicenter case-control study recruited adults over 70 years old with and without falls from two outpatient clinics and three nursing homes between September 2021 and March 2022. Clinical variables and gait parameters were collected using the G-STRIDE sensor, and Random Forest regression was used for participant stratification. Results: A total of 163 participants, with a mean age of 82.6 ± 6.2 years, of whom 118 (72%) were women, were included. Significant differences were observed in all gait parameters (both traditional and G-STRIDE evaluations). A hierarchy of factors contributed to the risk of frailty and falls. The confusion matrix and performance metrics showed high accuracy in participant classification. Conclusions: Gait parameters, especially those measured by G-STRIDE, are valuable in stratifying individuals based on frailty status and falls. These results highlight the importance of gait analysis in early intervention strategies. ChatGPT puede cometer errores. Considera verificar la información importante. ? ChatGPT dice: The World Health Organization advocates for health initiatives focused on the early detection of frailty and falls. Objectives: 1—To compare clinical characteristics, functional performance, and gait parameters (measured with the G-STRIDE inertial sensor) among different frailty groups in older adults with and without falls. 2—To identify variables that differentiate participants based on frailty status and fall history. 3—To assess the sensitivity, specificity, and accuracy of a model that classifies participants according to frailty and fall status. Methods: This observational, multicenter case-control study recruited adults over 70 years old with and without falls from two outpatient clinics and three nursing homes between September 2021 and March 2022. Clinical variables and gait parameters were collected using the G-STRIDE sensor, and Random Forest regression was used for participant stratification. Results: A total of 163 participants, with a mean age of 82.6 ± 6.2 years, of whom 118 (72%) were women, were included. Significant differences were observed in all gait parameters (both traditional and G-STRIDE evaluations). A hierarchy of factors contributed to the risk of frailty and falls. The confusion matrix and performance metrics showed high accuracy in participant classification. Conclusions: Gait parameters, especially those measured by G-STRIDE, are valuable in stratifying individuals based on frailty status and falls. These results highlight the importance of gait analysis in early intervention strategies.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.engAttribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/gait analysisinertial sensorsearly detectionfallsfrailtyinfo:eu-repo/semantics/article10.3390/app14156704info:eu-repo/semantics/openAccess