Software for the Diagnosis of Sarcopenia in Community-Dwelling Older Adults: Design and Validation Study

JMIR Med Inform. 2020 Apr 13;8(4):e13657. doi: 10.2196/13657.

Abstract

Background: The usual diagnosis of sarcopenia requires a dual-energy x-ray absorptiometry (DXA) exam, which has low accessibility in primary care for Latin American countries.

Objective: The aim of this study is to design and validate software for mobile devices (Android, IOS) and computers, based on an adapted version of the diagnostic algorithm of sarcopenia proposed by the European Working Group on Sarcopenia in Older People (EWGSOP).

Methods: Follow-up exams were conducted on 430 community-dwelling Chileans 60 years and older (mean 68.2 years, SD 4.9) participating in the IsaMayor and Alexandros cohorts designed to study sarcopenia and disability associated with obesity, respectively. All the participants from the cohorts were randomly selected from the registries of primary health care centers and, for this study, must have a DXA scan at baseline. The software (HTSMayor) was designed according to an adapted version of the algorithm proposed by the EWGSOP and was divided into four phases: longitudinal validation of diagnostic algorithm of sarcopenia, alpha version, beta version, and release version. The software estimates appendicular skeletal muscle mass (ASM) using an anthropometric equation or DXA measurements with Chilean cut-off points. The predictive validation of the algorithm was estimated, comparing functional limitations (at least one activity of daily living, two instrumental activities of daily living, or three mobility limitations), falls, and osteoporosis at follow-ups in patients with and without sarcopenia at baseline, using adjusted logistic models.

Results: After a median follow-up of 4.8 years (2078.4 person-years), 37 (9.9%) new cases of sarcopenia, out of the 374 patients without sarcopenia at baseline, were identified (incidence density rate=1.78 per 100 person-years). ASM estimated with the anthropometric equation showed both a high sensitivity and specificity as compared with those estimated by DXA measurements, yielding a concordance of 0.96. The diagnostic algorithm of sarcopenia considered in the software with the equation showed both a high sensitivity (82.1%) and specificity (94.9%) when compared with DXA (reference standard). Adults without sarcopenia (at baseline) showed better physical performance (after approximately 5 years) than adults with sarcopenia. Loss of functionality was greater in adults with sarcopenia (OR 5.0, 95% CI 2.2-11.4) than in adults without sarcopenia. In addition, the risks of falls (OR 2.2, 95% CI 1.1-4.3) and osteoporosis (OR 2.8, 95% CI 1.2-6.6) were higher in older persons with sarcopenia than those without sarcopenia. The measurements and results were completed for the beta and release tests with a mean time of 10 minutes and 11 minutes, respectively.

Conclusions: We developed and validated a software for the diagnosis of sarcopenia in older Chilean adults that can be used on a mobile device or a computer with good sensitivity and specificity, thus allowing for the development of programs for the prevention, delay, or reversal of this disease. To our knowledge, HTSMayor is the first software to diagnose sarcopenia.

International registered report identifier (irrid): RR2-10.2196/13657.

Keywords: elderly; mHealth; muscle; sarcopenia; software.