Evidence map›Paper›PMID 36235728›Full record

Observational studyNutrients2022

The Impact of Volume Overload on the Longitudinal Change of Adipose and Lean Tissue Mass in Incident Chinese Peritoneal Dialysis Patients.

Jack Kit-Chung Ng, Gordon Chun-Kau Chan, Kevin Ka-Ho Kam, Na Tian, Win Hlaing Than, Phyllis Mei-Shan Cheng, Man-Ching Law, Wing-Fai Pang, Cheuk-Chun Szeto, Philip Kam-Tao Li

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. 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

10 authors at 3 institutions in 2 countries.

Jack Kit-Chung NgCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0002-9549-9611
Gordon Chun-Kau ChanCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0003-4681-7326
Kevin Ka-Ho KamDivision of Cardiology, Department of Medicine & Therapeutics, Prince of Wales Hospital, Hong Kong 999077, China.
Na TianDepartment of Nephrology, General Hospital of Ningxia Medical University, Yinchuan 750004, China.
Win Hlaing ThanCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0002-6048-6490
Phyllis Mei-Shan ChengCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.
Man-Ching LawCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.
Wing-Fai PangCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.
Cheuk-Chun SzetoCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.
Philip Kam-Tao LiCarol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0001-9879-8388
Chinese University of Hong Kong · HKNingxia Medical University · CNPrince of Wales Hospital · CN

Funding

Chinese University of Hong Kong 6901031 and 7101215Hong Kong Society of Nephrology Research Grant 2018
6 · The paper itself

Abstract

Patients treated with peritoneal dialysis (PD) experience complex body composition changes that are not adequately reflected by traditional anthropometric parameters. While lean and adipose tissue mass can be readily assessed by bioimpedance spectroscopy (BIS), there is concern about the potential confounding effect of volume overload on these measurements. This study aimed to assess the influence of fluid status (by echocardiography) on body composition parameters measured by BIS and to describe the longitudinal changes in adipose and lean tissue mass. We conducted a prospective observational study in a tertiary hospital. Incident Chinese PD patients underwent baseline echocardiography and repeated BIS measurements at baseline and 12 months later. Among 101 PD patients, lean tissue index (LTI) or fat tissue index (FTI) was not associated with echocardiographic parameters that reflected left ventricular filling pressure (surrogate of volume status). Sixty-eight patients with repeated BIS had a significant increase in body weight and FTI, while LTI remained similar. Gains in fat mass were significantly associated with muscle wasting (beta = −0.71, p < 0.0001). Moreover, progressive fluid accumulation independently predicted decrease in FTI (beta = −0.35, p < 0.0001) but not LTI. Body composition assessments by BIS were not affected by fluid status and should be considered as part of comprehensive nutrition assessment in PD patients.

Indexed as

Peritoneal DialysisWater-Electrolyte ImbalanceAdipose TissueBody CompositionChinaElectric ImpedanceHumansadipose tissuebioimpedancebody compositionechocardiographymuscle wastingperitoneal dialysisvolume overload

Identifiers

PMID36235728
PMCPMC9571726
OpenAlexW4303962431

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.