Evidence map›Paper›PMID 32414332›Full record

ArticleBMC cardiovascular disorders2020

Association between inflammation and skeletal muscle proteolysis, skeletal mass and strength in elderly heart failure patients and their prognostic implications.

Masayuki Koshikawa, Masahide Harada, Shunsuke Noyama, Ken Kiyono, Yuji Motoike, Yoshihiro Nomura, Asuka Nishimura, Hideo Izawa, Eiichi Watanabe, Yukio Ozaki

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

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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

10 authors at 3 institutions in 1 country.

Masayuki KoshikawaDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
Masahide HaradaDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
Shunsuke NoyamaDivision of Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.
Ken KiyonoDivision of Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.
Yuji MotoikeDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
Yoshihiro NomuraDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
Asuka NishimuraDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
Hideo IzawaDepartment of Cardiology, Fujita Health University School of Medicine, Bantane Hospital, Nagoya, Japan.
Eiichi WatanabeDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan. enwatan@fujita-hu.ac.jp.ORCID 0000-0002-2375-2323
Yukio OzakiDepartment of Cardiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
Fujita Health University Hospital · JPThe University of Osaka · JPFujita Health University · JP

Funding

Japan Society for the Promotion of Science 17K09533Suzuken Memorial Foundation 2013
6 · The paper itself

Abstract

backgroundInflammation and skeletal muscle wasting often coexist in elderly populations, but few studies have examined their relationship in elderly heart failure (HF) patients. This study examined the relationship between inflammation and increased skeletal muscle proteolysis, reduced skeletal mass and strength, and their prognostic implications in elderly HF patients (> 65 years) using a random forest approach.

methodsWe prospectively enrolled consecutive elderly HF patients (n = 78) and age- and sex-matched control subjects (n = 83). We measured the interleukin (IL)-6, C-reactive protein (CRP), and B-type natriuretic peptide (BNP) levels, lower limb muscle mass and strength, and 6-min walk distance. The amount of muscle proteolysis was determined by urinary 3-methylhystidine, normalized by creatinine (3-MH/Cr). The composite endpoint was defined as all-cause death or hospitalizations due to worsening HF.

resultsCompared to controls, elderly HF patients had a significantly higher IL-6, CRP, BNP, and 3-MH/Cr, and exhibited a reduced lower limb muscle mass and strength. A correlation analysis demonstrated significant positive correlations between the inflammatory cytokine levels and 3-MH/Cr and BNP, and negative correlations with the lower limb muscle mass and strength, and 6-min walk distance. During a median follow-up of 2.4-years, 24 patients reached the endpoint. A random forest model revealed that inflammatory cytokines, skeletal muscle wasting, and the BNP had greater effects on the risk prediction. The algorithm achieved an area under the receiver operating characteristic curve of 0.887 (95% CI, 0.772-1.000).

conclusionThis study provided evidence of the association between inflammation and increased skeletal muscle proteolysis, reduced skeletal mass and strength, and their prognostic roles in elderly HF patients.

Indexed as

Frail ElderlyMuscle StrengthAgedAged, 80 and overAge FactorsBiomarkersCase-Control StudiesExercise ToleranceFemaleFrailtyHeart FailureHospitalizationHumansInflammationInflammation MediatorsMaleBiomarkersInflammation MediatorsElderlyFrailtyMortalitySarcopenia

Identifiers

PMID32414332
PMCPMC7229573
OpenAlexW3025677325

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.