Evidence map›Paper›PMID 42111843›Full record

ArticleFrontiers in nutrition2026

Novel prediction equations for appendicular skeletal muscle mass in hemodialysis patients: referenced against bioelectrical impedance analysis.

Xinyu Wang, Lijuan Chen, Wenjing Yu, Dan Qiao, Li Li, Jian Wang, Bin Zhang, Zhiying Ang, Zhuqing Li, Ying Shen and 3 more

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
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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

13 authors.

Xinyu Wang *Department of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Lijuan Chen *Department of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Wenjing Yu *Department of Nephrology, The First People's Hospital of Yunnan Province, School of Medicine, Kunming University of Science and Technology, Kunming, China.
Dan Qiao *Department of Nephrology, The First People's Hospital of Yunnan Province, School of Medicine, Kunming University of Science and Technology, Kunming, China.
Li LiDepartment of Nephrology, The First People's Hospital of Yunnan Province, School of Medicine, Kunming University of Science and Technology, Kunming, China.
Jian WangDepartment of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Bin ZhangDepartment of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Zhiying AngDepartment of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Zhuqing LiDepartment of General Practice, Huaning People's Hospital, Yuxi, China.
Ying ShenDepartment of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Fei ChenDepartment of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Yingchun MaDepartment of Nephrology, Beijing Boai Hospital, China Rehabilitation Research Center; School of Rehabilitation Medicine, Capital Medical University, Beijing, China.
Qinyuan DengDepartment of Nephrology, Yunnan Province Spinal Cord Disease Clinical Medical Center, The First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate assessment of appendicular skeletal muscle mass (ASM) is essential in clinical practice and research involving patients undergoing hemodialysis (HD). However, ASM prediction equations developed in the general population may be inappropriate for HD patients because of dialysis-related alterations in body composition and hydration status. Objective: To evaluate the performance of existing anthropometric ASM prediction equations in HD patients and to develop dialysis-specific equations tailored to this population. Methods: In this cross-sectional study, 111 patients receiving maintenance hemodialysis were enrolled. ASM was measured using multi-frequency bioelectrical impedance analysis (BIA) under standardized post-dialysis conditions. The performance of three previously published equations, namely the height-weight (HW), limb-length-circumference (LC), and height-circumference (HC) models, was assessed. New dialysis-specific equations were developed using anthropometric variables through linear regression. Agreement was evaluated using Bland-Altman analysis, and internal validation was performed using cross-validation and bootstrap resampling. Results: Existing equations demonstrated limited agreement with BIA-measured ASM, showing substantial systematic bias and wide limits of agreement. Two dialysis-specific equations were developed: an advanced HW model (adjusted R Conclusion: ASM prediction equations derived from the general population have limited applicability in patients undergoing maintenance hemodialysis. Dialysis-specific anthropometric calibration improves agreement with reference ASM, with the HH equation providing a practical and reliable tool for muscle mass assessment in this population.

Indexed as

appendicular skeletal muscle massbioelectrical impedance analysishemodialysisprediction equationssarcopenia

Identifiers

PMID42111843
PMCPMC13149067

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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.