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 |
Aparece en las colecciones: | Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
2023_Montemurro A_Validity of an iPhone App to Detect Prefrailty and Sarcopenia Syndromes in Community-Dwelling Older Adults-The protocol.pdf | 810,39 kB | Adobe PDF | ![]() Visualizar/Abrir |
Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons