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Record W4283789196 · doi:10.3389/fnut.2022.925606

Prevalence of Sarcopenia in Patients With COVID-19: A Systematic Review and Meta-Analysis

2022· review· en· W4283789196 on OpenAlexaboutno aff
Ying Xu, Jiawen Xu, You Peng, Bing‐Long Wang, Chao Liu, Ching-Wen Chien, Tao‐Hsin Tung

Bibliographic record

VenueFrontiers in Nutrition · 2022
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSarcopeniaMeta-analysisMedicineCochrane LibraryMEDLINESystematic reviewObservational studyConfidence intervalPopulationCohort studyOdds ratioInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background It has been speculated that patients with sarcopenia are aggravated by the current novel coronavirus disease 2019 (COVID-19) epidemic. However, there is substantial uncertainty regarding the prevalence of sarcopenia in patients with COVID-19. Objectives The purpose of the study was to systematically evaluate the prevalence of sarcopenia in patients with COVID-19, including stratification by gender, study location, study population, study design, and diagnostic criteria. Design This is the systematic literature review and meta-analysis. Methods An electronic search was performed in MEDLINE/PubMed, Embase, Cochrane Library, and Web of Science and Scopus to identify observational studies reporting a prevalence estimate for sarcopenia in patients with COVID-19. Studies were reviewed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and a meta-analysis was performed. Risk of bias (RoB) was assessed using the Newcastle–Ottawa Scale (NOS) for cohort studies and Joanna Briggs Institute (JBI) manual for cross-sectional studies, and Stata 14.0 was used to perform meta-analyses. Results A total of 4,639 studies were initially identified. After removing the duplicates and applying the selection criteria, we reviewed 151 full-text studies. A total of 21 studies, including 5,407 patients, were eligible for inclusion in this review finally. The prevalence of sarcopenia in patients with COVID-19 in individual studies varied from 0.8 to 90.2%. The pooled prevalence of sarcopenia in COVID-19 was 48.0% (95% confidence interval, CI: 30.8 to 65.1%, I 2 = 99.68%, p = 0.000). We did not find any significant differences in the prevalence estimates between gender specificity (OR = 1.34; 95% CI = 0.80–2.26; p = 0.001). By sex, the prevalence was 42.5% (95% CI: 31.7 to 53.4%) in men and 35.7% (95% CI: 24.2 to 47.2%) in women. The prevalence estimates significantly varied based on population settings and different diagnostic criteria of sarcopenia. ICU patients (69.7, 95% CI: 51.7 to 85.2%) were more likely to suffer from sarcopenia compared to other population settings. Conclusion To our knowledge, this is the first meta-analysis reporting on the prevalence of sarcopenia in patients with COVID-19. Sarcopenia is frequently observed in patients with COVID-19, with varying prevalence across population settings. This study would be useful for clinicians to prompt the increasing awareness of identifying sarcopenia and developing interventions at patients with COVID-19 with high risk of sarcopenia. Further prospective longitudinal studies to define the association of sarcopenia and its prognostic outcomes in COVID-19 survivors are urgently needed to propose the most appropriate treatment strategies during their admission and discharge. Systematic Review Registration [ www.crd.york.ac.uk/prospero/ ], identifier [CRD42022300431].

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.704
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.379
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2022
Admission routes1
Has abstractyes

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