Por favor, use este identificador para citar o enlazar este ítem: https://doi.org/10.3390/s22166010

Título: Validity of an iPhone App to detect Prefrailty and Sarcopenia Syndromes in community-dwelling older adults: the protocol for a diagnostic accuracy study
Fecha de publicación: 11-ago-2022
Editorial: MDPI
Cita bibliográfica: Sensors, 2022, Vol. 22 (16) :
ISSN: Electronic: 1424-8220
Palabras clave: Aging
Sit to stand
Frail
Sarcopenia
Functional capacity
Muscle power
Chair rise
Smartphone
Resumen: Prefrailty and sarcopenia in combination are more predictive of mortality than either condition alone. Early detection of these syndromes determines the prognosis of health-related adverse events since both conditions can be reversed through appropriate interventions. Nowadays, there is a lack of cheap, portable, rapid, and easy-to-use tools for detecting prefrailty and sarcopenia in combination. The aim of this study is to validate an iPhone App to detect prefrailty and sarcopenia syndromes in community-dwelling older adults. A diagnostic test accuracy study will include at least 400 participants aged 60 or over without cognitive impairment and physical disability recruited from elderly social centers of Murcia (Spain). Sit-to-stand muscle power measured through a slow-motion video analysis mobile application will be considered as the index test in combination with muscle mass (calf circumference or upper mid-arm circumference). Frailty syndrome (Fried’s Phenotype) and sarcopenia (EWGSOP2) will both be considered as reference standards. Sensibility, specificity, positive and negative predictive values and likelihood ratios will be calculated as well as the area under the curve of the receiver operating characteristic. This mobile application will add the benefit for screening large populations in short time periods within a field-based setting, where space and technology are often constrained (NCT05148351).
Autor/es principal/es: Montemurro, Alessio
Ruiz Cárdenas, Juan D.
Martínez García, María del Mar
Rodríguez Juan, Juan José
Versión del editor: https://www.mdpi.com/1424-8220/22/16/6010
URI: http://hdl.handle.net/10201/149799
DOI: https://doi.org/10.3390/s22166010
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 10
Derechos: info:eu-repo/semantics/openAccess
Atribución 4.0 Internacional
Descripción: © 2022 by the authors. This manuscript version is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by/4.0/ This document is the Published Manuscript version of a Published Work that appeared in final form in Sensors. To access the final edited and published work see https://doi.org/10.3390/s22166010
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