Evidence map›Paper›PMID 32281942›Full record

ArticleJMIR medical informatics2020

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

Lydia Lera, Bárbara Angel, Carlos Márquez, Rodrigo Saguez, Cecilia Albala

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  7. Challenges in the Management of Sarcopenia in the Primary Care Setting: A Scoping Review.International journal of environmental research and public health · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Lydia LeraPublic Health Nutrition Unit, Institute of Nutrition and Food Technology, University of Chile, Santiago de Chile, Chile.ORCID https://orcid.org/0000-0001-7470-2433
Bárbara AngelPublic Health Nutrition Unit, Institute of Nutrition and Food Technology, University of Chile, Santiago de Chile, Chile.ORCID https://orcid.org/0000-0001-8773-5904
Carlos MárquezPublic Health Nutrition Unit, Institute of Nutrition and Food Technology, University of Chile, Santiago de Chile, Chile.ORCID https://orcid.org/0000-0002-8166-8605
Rodrigo SaguezPublic Health Nutrition Unit, Institute of Nutrition and Food Technology, University of Chile, Santiago de Chile, Chile.ORCID https://orcid.org/0000-0003-2428-7942
Cecilia AlbalaPublic Health Nutrition Unit, Institute of Nutrition and Food Technology, University of Chile, Santiago de Chile, Chile.ORCID https://orcid.org/0000-0002-6135-334X
University of Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

objectiveThe 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).

methodsFollow-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.

resultsAfter 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.

conclusionsWe 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.

Indexed as

elderlymHealthmusclesarcopeniasoftware

Identifiers

PMID32281942
PMCPMC7186874
OpenAlexW3000754034

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.