Evidence map›Paper›PMID 30775558›Full record

ArticleOsteoporosis and sarcopenia2018

Correlation between muscle mass, nutritional status and physical performance of elderly people.

Thiago Neves, Carlos Alexandre Fett, Eduardo Ferriolli, Milene Giovana Crespilho Souza, Adilson Domingos Dos Reis Filho, Marcela Bomfim Martin Lopes, Neusa Maria Carraro Martins, Waléria Christiane Rezende Fett

Abstract read
In one paragraph

Article in Osteoporosis and sarcopenia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Observational
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  13. Muscle Wasting and Sarcopenia in Heart Failure-The Current State of Science.International journal of molecular sciences · 2020
    Review
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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

8 authors.

Thiago NevesDepartment of Physical Education, University of the State of Mato Grosso, Diamantino, MT, Brazil.
Carlos Alexandre FettDepartment of Physical Education, Nucleus of Studies in Physical Fitness, Computers, Metabolism, and Sports and Health, Federal University of Mato Grosso, Cuiabá, MT, Brazil.
Eduardo FerriolliDepartment of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.
Milene Giovana Crespilho SouzaDepartment of Physical Education, Nucleus of Studies in Physical Fitness, Computers, Metabolism, and Sports and Health, Federal University of Mato Grosso, Cuiabá, MT, Brazil.
Adilson Domingos Dos Reis FilhoDepartment of Physical Education, Physical Education College, IPE Faculty of Technology, Cuiabá, MT, Brazil.
Marcela Bomfim Martin LopesDepartment of Physical Education, Physical Education College, IPE Faculty of Technology, Cuiabá, MT, Brazil.
Neusa Maria Carraro MartinsDepartment of Physical Education, Nucleus of Studies in Physical Fitness, Computers, Metabolism, and Sports and Health, Federal University of Mato Grosso, Cuiabá, MT, Brazil.
Waléria Christiane Rezende FettDepartment of Physical Education, Nucleus of Studies in Physical Fitness, Computers, Metabolism, and Sports and Health, Federal University of Mato Grosso, Cuiabá, MT, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study evaluated the relationship between the skeletal muscle mass (SMM), obtained by predictive equations, and the body composition, nutritional aspects, functionality and physical performance in elderly people.

methodsThe sample consisted of adults aged 65 years or over from the cross-sectional study of the Brazilian Elderly Frailty Study Network, in Cuiabá, Mato Grosso State, Brazil. The anthropometric parameters, instrumental activities of daily living (IADL), Short Physical Performance Battery (SPPB), and handgrip strength (HGS) were evaluated. The SMM was estimated by 2 predictive anthropometric equations.

resultsBoth SMM equations correlated with age, anthropometric indices, SPPB, IADL, and HGS. However, only HGS and neck circumference strongly correlated in both equations, being higher in SMM II.

conclusionsIt seems that both equations are sensitive to obtain the SMM, contributing to the diagnosis of sarcopenia, nutritional status, and a physical performance condition.

Indexed as

ElderlyFunctionalityMuscle massStrength

Identifiers

PMID30775558
PMCPMC6372823

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.