Evidence map›Paper›PMID 29581385›Full record

ReviewJournal of investigative medicine : the official publication of the American Federation for Clinical Research2018

Advanced body composition assessment: from body mass index to body composition profiling.

Magnus Borga, Janne West, Jimmy D Bell, Nicholas C Harvey, Thobias Romu, Steven B Heymsfield, Olof Dahlqvist Leinhard

2 registry-linked trialsOpen access · hybridAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of investigative medicine : the official publication of the American Federation for Clinical Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 311 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
311citing papers in PubMed, 6 pooled it
22.9field-weighted citation impact, top 1% 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.

NCT05477277 narecruitingnot on this mapstarted 2022, after this paper: background citation

Adverse Outcomes and Mortality in Liver Transplant

TypeinterventionalSponsorMayo ClinicRan2022 to 2027Enrolled100ConditionsEnd Stage Liver DIsease, Sarcopenia, Sarcopenic Obesity, CirrhosisArmsMAsS
NCT06545435 recruitingnot on this mapstarted 2021, after this paper: background citation

Predicting Appendicular Lean and Fat Mass With Bioelectrical Impedance Analysis Among Adult Patients With Obesity.

TypeobservationalSponsorUniversity of Roma La SapienzaRan2021 to 2025Enrolled400ConditionsObesity
3 · Its place in the literature

Who cites it

311 citing papers in PubMed, 6 syntheses or guidelines pooled it, 589 citations in OpenAlex.

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251 more citing papers are in PubMed but not listed here.

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 4 institutions in 3 countries.

Magnus BorgaDepartment of Biomedical Engineering, Linköping University, Linköping, Sweden.ORCID 0000-0002-9267-2191
Janne WestCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Jimmy D BellResearch Centre for Optimal Health, University of Westminster, London, UK.
Nicholas C HarveyMRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK.
Thobias RomuDepartment of Biomedical Engineering, Linköping University, Linköping, Sweden.
Steven B HeymsfieldPennington Biomedical Research Center, Baton Rouge, Louisiana, USA.
Olof Dahlqvist LeinhardCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Linköping University · SEPennington Biomedical Research Center · USUniversity Hospital Southampton NHS Foundation Trust · GBUniversity of Westminster · GB

Funding

Arthritis Research UK 17702Arthritis Research UK 21231Department of Health HTA/10/33/04Medical Research Council G0400491Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MC_U147585819Medical Research Council MC_U147585824Medical Research Council MC_U147585827Medical Research Council MC_UP_A620_1014Medical Research Council MC_UU_12011/1Versus Arthritis 17702Versus Arthritis 21231
6 · The paper itself

Abstract

This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat, in combination with rapid scanning protocols and efficient image analysis tools, makes quantitative MRI a powerful tool for advanced body composition assessment.

Indexed as

Body CompositionBody Mass IndexAdipose TissueAdiposityHumansMagnetic Resonance Imagingbody compositionmagnetic resonance imaging

Identifiers

PMID29581385
PMCPMC5992366
OpenAlexW2793413123

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.