Evidence map›Paper›PMID 38658443›Full record

ArticleClinical and experimental nephrology2024

Dialysis Duration, Time Interaction, and Visceral Fat Accumulation: A 6-Year Posttransplantation Study.

Hiroki Fukuhara, Hayato Nishida, Satoshi Takai, Takaaki Nawano, Tomohiro Takehara, Yuki Takai, Takafui Narisawa, Hidenori Kanno, Mayu Yagi, Atsushi Yamagishi and 2 more

Abstract read
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In one paragraph

Article in Clinical and experimental nephrology, 2024. 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
0.7field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Psoas Muscle Index, Systemic Inflammation, and Liver Fibrosis in MAFLD: A Case-Control Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025
    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

12 authors at 1 institution in 1 country.

Hiroki FukuharaDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan. hiroki_fukuhara@yahoo.co.jp.ORCID http://orcid.org/0000-0002-6332-9845
Hayato NishidaDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Satoshi TakaiDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Takaaki NawanoDepartment of Cardiology, Pulmonology, and Nephrology, Faculty of Medicine, Yamagata University, Yamagata, Japan.
Tomohiro TakeharaDepartment of Cardiology, Pulmonology, and Nephrology, Faculty of Medicine, Yamagata University, Yamagata, Japan.
Yuki TakaiDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Takafui NarisawaDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Hidenori KannoDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Mayu YagiDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Atsushi YamagishiDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Sei NaitoDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Norihiko TsuchiyaDepartment of Urology, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
Yamagata University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKidney transplantation (KT) leads to body composition change, particularly increasing the fat mass. However, limited researches have focused on the long-term follow-up of these changes and factors influencing body composition after KT.

methodsThis study evaluated body composition in 31 adult KT recipients, measuring body mass index (BMI), the psoas muscle mass index (PMI) representing muscle mass, visceral and subcutaneous adipose tissue (VAT and SAT) representing fat mass, and skeletal muscle radiodensity (SMR) representing muscle quality before KT and at 2, 4, and 6 years posttransplantation using computed tomography. Linear mixed models (LMM) analyzed temporal changes and contributing factors, while growth curve models assessed influence of these factors on body composition changes posttransplantation.

resultsFollowing KT, BMI, and PMI remained stable, while SAT increased significantly, revealing a 1.30-fold increase from baseline 2 years after transplantation. Similarly, a substantial increase in VAT was observed, with a 1.47-fold increase from baseline 2 years after transplantation with a further 1.75-fold increase 6 years after transplantation. In contrast, SMR decreased with a 0.86-fold decrease from baseline after 2 years. VAT increase was significantly influenced by the interaction between posttransplantation and dialysis duration. Growth curve models confirmed this interaction effect persistently influenced VAT increase posttransplantation.

conclusionsThe study revealed that KT promoted significant alterations in body composition characterized by increase in the VAT and SAT and a decline in SMR. Notably, dialysis duration and its interaction with posttransplantation duration emerged as significant factors influencing VAT increase.

Indexed as

Intra-Abdominal FatKidney TransplantationRenal DialysisAdiposityAdultAgedBody CompositionBody Mass IndexFemaleHumansMaleMiddle AgedMuscle, SkeletalSubcutaneous FatTime FactorsTomography, X-Ray ComputedBody composition changeDialysis durationKidney transplantationTime interactionVisceral adipose tissue

Identifiers

PMID38658443
OpenAlexW4395069196

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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.