Evidence map›Paper›PMID 31057002›Full record

Observational studyRenal failure2019

Evaluation of body composition monitoring for assessment of nutritional status in hemodialysis patients.

Haifen Zhang, Xingjuan Tao, Ling Shi, Na Jiang, Yan Yang

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Renal failure, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

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

13 citing papers in PubMed, 1 synthesis or guideline 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

5 authors.

Haifen Zhanga Department of Nephrology , Renji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China.
Xingjuan Taob School of Nursing , Shanghai Jiao Tong University , Shanghai , China.ORCID http://orcid.org/0000-0002-7954-1760
Ling Shia Department of Nephrology , Renji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China.
Na Jianga Department of Nephrology , Renji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China.
Yan Yanga Department of Nephrology , Renji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBody composition monitoring is the only clinically available method for distinguishing among the three body components. This study aimed to determine the relationship between body composition and all-cause mortality in Chinese hemodialysis patients and examine whether the lean tissue index (LTI) derived from body composition monitoring can accurately diagnose malnourished patients.

methodsHemodialysis patients (n = 123) with nutritional and body composition assessment records in 2015 were examined. Body composition was assessed using a body composition monitor machine.

resultsFifty-seven patients (46.3%) had low LTI (LTI less than the 10th percentile of the respective normal distribution). Significant differences in the fat tissue index (FTI) were observed, with the low LTI group having a higher FTI (10.8 kg/m

conclusionsLTI is a predictor of mortality, and its predictive power was not affected when FTI, SGA, and hydration status were included in the multivariate analysis. However, SGA may not be adequate to identify patients at a risk of death among Chinese hemodialysis patients.

Indexed as

Nutrition AssessmentAgedBody CompositionFemaleHumansKaplan-Meier EstimateKidney Failure, ChronicMaleMalnutritionMiddle AgedMultivariate AnalysisNutritional StatusPredictive Value of TestsPrognosisRenal DialysisRetrospective StudiesBioimpedancebody compositionend-stage renal diseaselean tissue massnutrition assessment

Identifiers

PMID31057002
PMCPMC6508072

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Registered trials

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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.