Evidence map›Paper›PMID 36788294›Full record

ArticleScientific reports2023

Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models.

Cassidy McCarthy, Grant M Tinsley, Anja Bosy-Westphal, Manfred J Müller, John Shepherd, Dympna Gallagher, Steven B Heymsfield

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
7.2field-weighted citation impact, top 2% 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.

  1. Pooled it
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  6. Article
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  9. Leveraging Multiomic Signatures to Predict Body Composition.Advances in nutrition (Bethesda, Md.) · 2026
    Review
  10. Article
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  12. Article
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  15. The relationship between muscle mass and low back pain: a cross-sectional study.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 2 countries.

Cassidy McCarthyPennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road, Baton Rouge, LA, 70808, USA.
Grant M TinsleyDepartment of Kinesiology and Sport Management, Texas Tech University, Lubbock, USA.
Anja Bosy-WestphalDepartment of Human Nutrition and Food Science, Christian-Albrecht's-University of Kiel, Kiel, Germany.
Manfred J MüllerDepartment of Human Nutrition and Food Science, Christian-Albrecht's-University of Kiel, Kiel, Germany.
John ShepherdUniversity of Hawaii Cancer Center, Honolulu, HI, USA.
Dympna GallagherDepartment of Medicine, College of Physicians and Surgeons, New York Obesity Research Center, Columbia University, New York, NY, USA.
Steven B HeymsfieldPennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road, Baton Rouge, LA, 70808, USA. steven.heymsfield@pbrc.edu.
Kiel University · DEPennington Biomedical Research Center · USColumbia University · USTexas Tech University · USUniversity of Hawaiʻi at Mānoa · US

Funding

Research BaseP30DK072476 · NIDDK · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI Sujoy Ghosh · 2005 to 2026
$26.5M
Optical Body Composition and Health AssessmentR01DK109008 · NIDDK · UNIVERSITY OF HAWAII AT MANOA · PI HEYMSFIELD, STEVEN, SHEPHERD, JOHN ALAN · 2016 to 2020
$3.2M
NIDDK NIH HHS P30 DK072476NIH HHS P30DK072476NIH HHS R01DK109008
6 · The paper itself

Abstract

Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R

Indexed as

Magnetic Resonance ImagingSarcopeniaAbsorptiometry, PhotonAdultBody CompositionHumansMuscle, SkeletalWhole Body Imaging

Identifiers

PMID36788294
PMCPMC9929067
OpenAlexW4320727074

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.