Evidence map›Paper›PMID 40735822›Full record

ArticleJournal of cachexia, sarcopenia and muscle2025

Reference Data and Predictors of HR-pQCT-Derived Muscle Density and Its Prediction of Physical Performance.

Stuart J Warden, Ziyue Liu, Robyn K Fuchs, Lilly G Davisson, Keith G Avin, Erik A Imel, Kenneth Lim, Sharon M Moe, Rachel K Surowiec

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

9 authors.

Stuart J WardenDepartment of Physical Therapy, School of Health and Human Sciences, Indiana University Indianapolis, Indianapolis, Indiana, USA.ORCID 0000-0002-6415-4936
Ziyue LiuIndiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0009-0008-8312-6608
Robyn K FuchsIndiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0001-6227-729X
Lilly G DavissonDepartment of Physical Therapy, School of Health and Human Sciences, Indiana University Indianapolis, Indianapolis, Indiana, USA.
Keith G AvinDepartment of Physical Therapy, School of Health and Human Sciences, Indiana University Indianapolis, Indianapolis, Indiana, USA.ORCID 0000-0001-9426-7862
Erik A ImelIndiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0002-7284-3467
Kenneth LimDivision of Nephrology and Hypertension, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0001-7178-2183
Sharon M MoeIndiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0003-3562-9725
Rachel K SurowiecIndiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0001-7614-4412

Funding

Indiana Clinical and Translational Sciences InstituteUM1TR004402 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI Sharon M Moe, Sarah Elizabeth Wiehe · 2023 to 2026
$21.6M
Resource CoreP30AR072581 · NIAMS · INDIANA UNIVERSITY INDIANAPOLIS · PI Sharon M Moe · 2017 to 2026
$8.3M
Redefining cardiovascular risk assessment in dialysis patients (ROCK-D) studyR01HL166747 · NHLBI · INDIANA UNIVERSITY INDIANAPOLIS · PI Kenneth Lim · 2023 to 2026
$3.0M
Sarcopenia: computable phenotypes and clinical outcomes.R01AR077273 · NIAMS · INDIANA UNIVERSITY INDIANAPOLIS · PI IMEL, ERIK ALLEN · 2020 to 2022
$577k
Indiana Clinical Translational Science Award/Institute NCATS UM1TR004402NCATS NIH HHS UM1 TR004402NHLBI NIH HHS R01 HL166747NIAMS NIH HHS P30 AR072581NIAMS NIH HHS R01 AR077273
6 · The paper itself

Abstract

backgroundThere is increasing awareness of a role for muscle composition in sarcopenia and cachexia. Computed tomography (CT)-based measures of muscle density (MusD) are commonly used to indicate composition, with a decrease in MusD reflecting an increase in muscle fat infiltration. The current study explored predictors of MusD acquired using high-resolution peripheral quantitative computed tomography (HR-pQCT) and whether MusD predicted physical performance. In addition, reference data for MusD were generated and applied.

methodsHR-pQCT scans performed in 1662 adults (aged 18-80 years) at 30% of bone length proximal from the distal end of the radius and tibia were analysed for forearm and leg MusD, respectively. Predictors of MusD were explored, and it was investigated whether MusD predicted physical performance. Centile curves were fit to the MusD data using the LMS approach to generate reference data, and a calculator was developed to enable computation of subject-specific standardised outcomes. The utility of the calculator was explored in validation cohorts of female collegiate-level athletes (n = 50) and individuals with chronic kidney disease (CKD) (n = 50).

resultsForearm and leg MusD were predicted by whole-body percent fat, sex and age. Forearm and leg MusD were 0.46 (~1.9%) and 0.60 mgHA/cm

conclusionsHR-pQCT acquired MusD provides a novel indicator of muscle composition which predicts physical function independent of muscle quantity (i.e., ALM/height

Indexed as

Muscle, SkeletalPhysical Functional PerformanceTomography, X-Ray ComputedAdolescentAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedYoung Adultcachexiacomputed tomographymuscle densitymuscle qualitynormative datasarcopenia

Identifiers

PMID40735822
PMCPMC12308218

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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.