Evidence map›Paper›PMID 28983090›Full record

ReviewExperimental & molecular medicine2017

Muscle fatigue: general understanding and treatment.

Jing-Jing Wan, Zhen Qin, Peng-Yuan Wang, Yang Sun, Xia Liu

Registry-linked trialAbstract readReview
In one paragraph

Review in Experimental & molecular medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05813613 (Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training In Healthy And Post COVID19 Subjects), which is not on this map. Cited by 260 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
260citing papers in PubMed, 4 pooled it
–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.

NCT05813613 completednot on this mapstarted 2023, after this paper: background citation

Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training In Healthy And Post COVID19 Subjects

TypeobservationalSponsorBeirut Arab UniversityRan2023 to 2023Enrolled90ConditionsFatigueArmsSquatting with the aid of Kynapsis Virtual Training apparatus.
3 · Its place in the literature

Who cites it

260 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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200 more citing papers are in PubMed but not listed here.

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

5 authors.

Jing-Jing WanDepartment of Pharmacology, School of Pharmacy, Second Military Medical University, Shanghai, China.
Zhen QinDepartment of Pharmacology, School of Pharmacy, Second Military Medical University, Shanghai, China.
Peng-Yuan WangDepartment of Pharmacology, School of Pharmacy, Second Military Medical University, Shanghai, China.
Yang SunDepartment of Pharmacology, School of Pharmacy, Second Military Medical University, Shanghai, China.
Xia LiuDepartment of Pharmacology, School of Pharmacy, Second Military Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Muscle fatigue is a common complaint in clinical practice. In humans, muscle fatigue can be defined as exercise-induced decrease in the ability to produce force. Here, to provide a general understanding and describe potential therapies for muscle fatigue, we summarize studies on muscle fatigue, including topics such as the sequence of events observed during force production, in vivo fatigue-site evaluation techniques, diagnostic markers and non-specific but effective treatments.

Indexed as

Muscle ContractionMuscle FatigueAnimalsBiomarkersCombined Modality TherapyElectromyographyEnergy MetabolismEvoked Potentials, MotorHumansMuscle, SkeletalOxidative StressBiomarkers

Identifiers

PMID28983090
PMCPMC5668469

What OpenQuestion holds

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Registered trials

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.