Evidence map›Paper›PMID 33195482›Full record

ReviewFrontiers in cardiovascular medicine2020

Current Studies and Future Directions of Exercise Therapy for Muscle Atrophy Induced by Heart Failure.

Qi Liu, Juan Gao, Jiali Deng, Junjie Xiao

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Genome Editing to Abrogate Muscle Atrophy.Advances in experimental medicine and biology · 2023
    Review
  2. Article
  3. Non-coding RNA basis of muscle atrophy.Molecular therapy. Nucleic acids · 2021
    Review
  4. Review
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

4 authors at 1 institution in 1 country.

Qi LiuCardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, School of Life Science, Shanghai University, Shanghai, China.
Juan GaoSchool of Medicine, Shanghai University, Shanghai, China.
Jiali DengCardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, School of Life Science, Shanghai University, Shanghai, China.
Junjie XiaoCardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, School of Life Science, Shanghai University, Shanghai, China.
Shanghai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Muscle atrophy is a common complication of heart failure. At present, there is no specific treatment to reverse the course of muscle atrophy. Exercise training, due to the safety and easy operation, is a recommended therapy for muscle atrophy induced by heart failure. However, the patients with muscle atrophy are weak in mobility and may not be able to train for a long time. Therefore, it is necessary to explore novel targets of exercise protection for muscle atrophy, so as to improve the quality of life and survival rate of patients with muscular atrophy induced by heart failure. This article aims to review latest studies, summarize the evidence and limitations, and provide a glimpse into the future of exercise for the treatment of muscle atrophy induced by heart failure. We wish to highlight some important findings about the essential roles of exercise sensors in muscle atrophy induced by heart failure, which might be helpful for searching potential therapeutic targets for muscle wasting induced by heart failure.

Indexed as

atrophyexercisemuscletargetstherapy

Identifiers

PMID33195482
PMCPMC7644508
OpenAlexW3093928608

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.