Evidence map›Paper›PMID 37479618›Full record

ArticleAcademic radiology2024

Association of CT-Derived Skeletal Muscle and Adipose Tissue Metrics with Frailty in Older Adults.

Paul M Bunch, Joseph Rigdon, Muhammad Khalid Khan Niazi, Ryan T Barnard, Robert D Boutin, Denise K Houston, Leon Lenchik

Open access · greenAbstract read
In one paragraph

Article in Academic radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 5 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Paul M BunchDepartment of Radiology, Wake Forest University School of Medicine, Medical Center Boulevard,Winston-Salem, NC 27157 (P.M.B., L.L.). Electronic address: paul.m.bunch@gmail.com.
Joseph RigdonDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Boulevard,Winston-Salem, North Carolina (J.R., R.T.B.).
Muhammad Khalid Khan NiaziCenter for Biomedical Informatics, Wake Forest University School of Medicine, Medical Center Boulevard,Winston-Salem, North Carolina (M.K.K.N.).
Ryan T BarnardDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Boulevard,Winston-Salem, North Carolina (J.R., R.T.B.).
Robert D BoutinDepartment of Radiology, Stanford University School of Medicine, Stanford, California (R.D.B.).
Denise K HoustonDepartment of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Medical Center Boulevard,Winston-Salem, North Carolina (D.K.H.).
Leon LenchikDepartment of Radiology, Wake Forest University School of Medicine, Medical Center Boulevard,Winston-Salem, NC 27157 (P.M.B., L.L.).
Wake Forest University · USStanford University · US

Funding

Wake Forest Claude D. Pepper OAIC - RenewalP30AG021332 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Jamie Nicole Justice · 2002 to 2026
$36.4M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
NCATS NIH HHS UL1 TR001420NIA NIH HHS P30 AG021332
6 · The paper itself

Abstract

RATIONALE AND

objectivesTools are needed for frailty screening of older adults. Opportunistic analysis of body composition could play a role. We aim to determine whether computed tomography (CT)-derived measurements of muscle and adipose tissue are associated with frailty. MATERIALS AND

methodsOutpatients aged ≥ 55 years consecutively imaged with contrast-enhanced abdominopelvic CT over a 3-month interval were included. Frailty was determined from the electronic health record using a previously validated electronic frailty index (eFI). CT images at the level of the L3 vertebra were automatically segmented to derive muscle metrics (skeletal muscle area [SMA], skeletal muscle density [SMD], intermuscular adipose tissue [IMAT]) and adipose tissue metrics (visceral adipose tissue [VAT], subcutaneous adipose tissue [SAT]). Distributions of demographic and CT-derived variables were compared between sexes. Sex-specific associations of muscle and adipose tissue metrics with eFI were characterized by linear regressions adjusted for age, race, ethnicity, duration between imaging and eFI measurements, and imaging parameters.

resultsThe cohort comprised 886 patients (449 women, 437 men, mean age 67.9 years), of whom 382 (43%) met the criteria for pre-frailty (ie, 0.10 < eFI ≤ 0.21) and 138 (16%) for frailty (eFI > 0.21). In men, 1 standard deviation changes in SMD (β = -0.01, 95% confidence interval [CI], -0.02 to -0.001, P = .02) and VAT area (β = 0.008, 95% CI, 0.0005-0.02, P = .04), but not SMA, IMAT, or SAT, were associated with higher frailty. In women, none of the CT-derived muscle or adipose tissue metrics were associated with frailty.

conclusionWe observed a positive association between frailty and CT-derived biomarkers of myosteatosis and visceral adiposity in a sex-dependent manner.

Indexed as

FrailtyAdipose TissueAgedBody CompositionFemaleHumansMaleMuscle, SkeletalTomography, X-Ray ComputedAdipose tissueAgingBody compositionFrailtyMyopeniaMyosteatosisSarcopenia

Identifiers

PMID37479618
PMCPMC10796847
OpenAlexW4384936469

What OpenQuestion holds

Textmetadata
LicenceTDM
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.