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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Internal Medicine Jo...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Internal Medicine Journal
Article . 2017 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Association between obesity with low muscle mass and dialysis mortality

Authors: Hung‐Chieh Wu; Shih‐Fen Tseng; Wei‐Jie Wang; Hsin‐Jen Chen; Lin‐Chien Lee;

Association between obesity with low muscle mass and dialysis mortality

Abstract

AbstractBackground/AimTo examine the association between body composition and dialysis mortality.MethodsAdult patients who underwent haemodialysis in Taoyuan General Hospital from 2012 to 2016 were enrolled. We reviewed their baseline characteristics and followed up their treatment over 5 years after dialysis. Patients with body mass index >25 kg/m2 were defined as obese. High or low muscle mass were classified by skeletal muscle mass index (SMMI) based on consensus from Chinese population. All age‐matched subjects were classified into four groups: (A) optimal; (B) obesity; (C) low muscle mass; and (D) obesity with low muscle mass. Adjusted hazard ratios for mortality and cumulative survival curves were evaluated by Cox proportional hazard model and Kaplan–Meier method. The discriminative power of SMMI was calculated according to the area under the curve and the receiver operating characteristic curve.ResultsFrom a total of 176 age‐matched patients, the incidence rates of mortality for different groups were 3.7, 7.8, 10.3 and 16.5 per 1000 person‐months. After adjusting for continuous variables, SMMI was independently associated with mortality. The difference between groups A and D was more significant in women than in men after multivariate adjustment (adjusted hazard ratios: 7.465 vs 1.682) (P = 0.035 and 0.553). The discriminative power of SMMI to predict 5‐year mortality was 0.700 for men and 0.750 for women, and the best cut‐off values were 11.1 and 8.4 kg/m2ConclusionsLow muscle mass was associated with dialysis mortality. Obesity with low muscle mass was a predictor for dialysis mortality in women.

Keywords

Adult, Aged, 80 and over, Male, Middle Aged, Cohort Studies, Renal Dialysis, Risk Factors, Body Composition, Humans, Female, Obesity, Mortality, Muscle, Skeletal, Aged, Follow-Up Studies, Retrospective Studies

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Average
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