Evidence map›Paper›PMID 36801962›Full record

ArticleEuropean journal of clinical nutrition2023

Prediction of whole body composition utilizing cross-sectional abdominal imaging in pediatrics.

Rebecca J Deyell, Sunil Desai, Andrea Gallivan, Alecia Lim, Michael B Sawyer, Steven B Heymsfield, Wei Shen, Vickie E Baracos

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of clinical nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 28% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
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 at 4 institutions in 2 countries.

Rebecca J DeyellDivision of Hematology, Oncology & Bone Marrow Transplant, Department of Pediatrics, British Columbia Children's Hospital and Research Institute, University of British Columbia, Vancouver, BC, Canada. rdeyell@cw.bc.ca.ORCID 0000-0003-3315-4383
Sunil DesaiDivision of iHOPE, Department of Pediatrics, Stollery Children's Hospital, University of Alberta, Edmonton, AB, Canada.
Andrea GallivanDepartment of Oncology, University of Alberta, Edmonton, AB, Canada.
Alecia LimDivision of Hematology, Oncology & Bone Marrow Transplant, Department of Pediatrics, British Columbia Children's Hospital and Research Institute, University of British Columbia, Vancouver, BC, Canada.
Michael B SawyerDepartment of Oncology, University of Alberta, Edmonton, AB, Canada.
Steven B HeymsfieldPennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA.ORCID 0000-0003-1127-9425
Wei ShenDivision of Pediatric Gastroenterology, Hepatology and Nutrition, Columbia University Irving Medical Center, New York, NY, USA.
Vickie E BaracosDepartment of Oncology, University of Alberta, Edmonton, AB, Canada.ORCID 0000-0002-9609-1001
University of Alberta · CAUniversity of British Columbia · CAColumbia University Irving Medical Center · USPennington Biomedical Research Center · US

Funding

RESEARCH TRAININGP30DK026687 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI Anthony W Ferrante, DYMPNA GALLAGHER · 1986 to 2026
$33.0M
WEIGHT LOSS--BONE &SKELETAL MUSCLE HOMEOSTASIS IN NIDDMP01DK042618 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI GALLAGHER, DYMPNA · 1990 to 2005
$7.8M
TARGETED GENE DELIVERY &EXPRESSION IN HEPATOCYTESR01DK042182 · NIDDK · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI WU, GEORGE Y · 1990 to 2005
$1.6M
Central Obesity and Health Risk: Optimal MRI Measurement & Location in ChildrenR21DK073720 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI SHEN, WEI · 2006 to 2010
$399k
NIDDK NIH HHS P01 DK042618NIDDK NIH HHS P30 DK026687NIDDK NIH HHS R01 DK042182NIDDK NIH HHS R21 DK073720
6 · The paper itself

Abstract

backgroundAlthough body composition is an important determinant of pediatric health outcomes, we lack tools to routinely assess it in clinical practice. We define models to predict whole-body skeletal muscle and fat composition, as measured by dual X-ray absorptiometry (DXA) or whole-body magnetic resonance imaging (MRI), in pediatric oncology and healthy pediatric cohorts, respectively.

methodsPediatric oncology patients (≥5 to ≤18 years) undergoing an abdominal CT were prospectively recruited for a concurrent study DXA scan. Cross-sectional areas of skeletal muscle and total adipose tissue at each lumbar vertebral level (L1-L5) were quantified and optimal linear regression models were defined. Whole body and cross-sectional MRI data from a previously recruited cohort of healthy children (≥5 to ≤18 years) was analyzed separately.

resultsEighty pediatric oncology patients (57% male; age range 5.1-18.4 y) were included. Cross-sectional areas of skeletal muscle and total adipose tissue at lumbar vertebral levels (L1-L5) were correlated with whole-body lean soft tissue mass (LSTM) (R

conclusionRegression models can predict whole-body skeletal muscle and fat in pediatric patients utilizing cross-sectional abdominal images.

Indexed as

Magnetic Resonance ImagingNeoplasmsAbsorptiometry, PhotonAdipose TissueAdolescentBody CompositionChildChild, PreschoolCohort StudiesFemaleHumansMaleMuscle, SkeletalWhole Body Imaging

Identifiers

PMID36801962
PMCPMC12199707
OpenAlexW4321226912

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.