Evidence map›Paper›PMID 36769296›Full record

ReviewInternational journal of molecular sciences2023

Prevalence and Mechanisms of Skeletal Muscle Atrophy in Metabolic Conditions.

Lauren Jun, Megan Robinson, Thangiah Geetha, Tom L Broderick, Jeganathan Ramesh Babu

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 1 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.

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

56 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Context-dependent roles of 11β-HSD1 in bone and skeletal muscle diseases.American journal of translational research · 2026
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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

5 authors.

Lauren JunDepartment of Nutritional Sciences, Auburn University, Auburn, AL 36849, USA.ORCID 0000-0002-1341-8831
Megan RobinsonDepartment of Nutritional Sciences, Auburn University, Auburn, AL 36849, USA.ORCID 0000-0002-5882-6994
Thangiah GeethaDepartment of Nutritional Sciences, Auburn University, Auburn, AL 36849, USA.ORCID 0000-0001-6358-0012
Tom L BroderickDepartment of Physiology, Laboratory of Diabetes and Exercise Metabolism, College of Graduate Studies, Midwestern University, Glendale, AZ 85308, USA.
Jeganathan Ramesh BabuDepartment of Nutritional Sciences, Auburn University, Auburn, AL 36849, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle atrophy is prevalent in a myriad of pathological conditions, such as diabetes, denervation, long-term immobility, malnutrition, sarcopenia, obesity, Alzheimer's disease, and cachexia. This is a critically important topic that has significance in the health of the current society, particularly older adults. The most damaging effect of muscle atrophy is the decreased quality of life from functional disability, increased risk of fractures, decreased basal metabolic rate, and reduced bone mineral density. Most skeletal muscle in humans contains slow oxidative, fast oxidative, and fast glycolytic muscle fiber types. Depending on the pathological condition, either oxidative or glycolytic muscle type may be affected to a greater extent. This review article discusses the prevalence of skeletal muscle atrophy and several mechanisms, with an emphasis on high-fat, high-sugar diet patterns, obesity, and diabetes, but including other conditions such as sarcopenia, Alzheimer's disease, cancer cachexia, and heart failure.

Indexed as

Alzheimer DiseaseDiabetes MellitusSarcopeniaAgedCachexiaHumansMuscle, SkeletalMuscular AtrophyObesityPrevalenceQuality of LifeAlzheimer’s diseasediabetesmuscle atrophyobesitysarcopeniaskeletal muscle

Identifiers

PMID36769296
PMCPMC9917738

What OpenQuestion holds

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LicenceCC BY
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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.