Evidence map›Paper›PMID 34930665›Full record

ArticleJournal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation2022

Longitudinal Assessment of Body Composition and Its Association With Survival Among Participants of the ACTIVE/ADIPOSE Study.

Cynthia Delgado, Janet M Chiang, Piyawan Kittiskulnam, Anoop Sheshadri, Barbara Grimes, Mark Segal, George A Kaysen, Kirsten L Johansen

Open access · greenAbstract read
In one paragraph

Article in Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
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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

8 authors at 5 institutions in 2 countries.

Cynthia DelgadoDivision of Nephrology, University of California, San Francisco and Nephrology Section, San Francisco VA Medical Center, San Francisco, California, USA. Electronic address: cynthia.delgado@ucsf.edu.
Janet M ChiangDivision of Endocrinology, University of California, San Francisco and San Francisco VA Medical Center, San Francisco, California, USA.
Piyawan KittiskulnamDivision of Nephrology, Chulalongkorn University, Bangkok, Thailand.
Anoop SheshadriDivision of Nephrology, University of California, San Francisco and Nephrology Section, San Francisco VA Medical Center, San Francisco, California, USA.
Barbara GrimesDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco California, USA.
Mark SegalDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco California, USA.
George A KaysenDepartment of Medicine, Division of Nephrology, University of California, Davis, Davis, California, USA; Department of Biochemistry and Molecular Medicine University of California, Davis, Davis, California, USA.
Kirsten L JohansenDepartment of Medicine, Division of Nephrology, Hennepin Healthcare, Minneapolis, Minnesota, USA; Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA.
University of California, San Francisco · USSan Francisco VA Medical Center · USChulalongkorn University · THUniversity of California, Davis · USUniversity of Minnesota · US

Funding

Predictors and outcomes of frailty in dialysis patientsR01DK107269 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHANSEN, KIRSTEN L. · 2016 to 2019
$1.8M
Prevalence and Impact of Frailty among Dialysis PatientsK24DK085153 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHANSEN, KIRSTEN L. · 2010 to 2021
$1.5M
The Effects of Frailty on Chronic Kidney DiseaseIK2CX000527 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI DELGADO, CYNTHIA · 2012 to 2016
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CSRD VA IK2 CX000527NIDDK NIH HHS K24 DK085153NIDDK NIH HHS R01 DK107269
6 · The paper itself

Abstract

objectivesThe importance of muscle wasting as a predictor of mortality in the hemodialysis population is not clear. Lack of association of muscle mass with survival in some studies could be related to reliance on single measures or to incorporation of excess extracellular water (ECW) into estimates of muscle mass. We examined changes in body composition over a 2-year period and the association of body composition with survival. DESIGN AND

methodsWe analyzed data from 325 adults receiving hemodialysis in the Bay Area. We estimated ECW, intracellular water (ICW), and fat mass by whole-body bioimpedance spectroscopy (BIS) at 0, 12, and 24 months from enrollment. We used linear mixed modeling to examine changes in body mass index and BIS-derived estimates of body composition and Cox modeling with BIS-derived estimates as time-varying independent variables to examine associations between body composition and survival in multivariable analyses.

resultsBody mass index declined over time. Considering individual components of body composition, ICW declined (-0.09 kg/m

conclusionsICW declined over 2 years in this cohort, whereas fat mass and ECW remained relatively stable. Higher ICW was associated with better survival, but higher fat mass was not. Higher ECW was associated with worse survival. These results suggest that muscle mass may predict survival among patients on hemodialysis.

Indexed as

Adipose TissueBody CompositionAdultBody Mass IndexBody WaterElectric ImpedanceHumansWaterWaterBody CompositionHemodialysisObesity ParadoxSurvival

Identifiers

PMID34930665
PMCPMC12888881
OpenAlexW4200044875

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.