Prevalence of sarcopenia in patients with COPD through different musculature measurements: An updated meta-analysis and meta-regression
Bibliographic record
Abstract
Aim: Chronic obstructive pulmonary disease (COPD) patients vary widely in terms of the prevalence of sarcopenia, which is partially attributed to differences in diagnostic criteria and disease severity. There are several different musculature measurements that are used to quantify sarcopenia. This study included published literature for meta-analysis to assess the sarcopenia prevalence in COPD patients and correlate the disease with the clinical characteristics of such patients. Methods: A comprehensive review of the English and Chinese literature on sarcopenia prevalence in COPD patients was conducted using electronic databases such as China National Knowledge Infrastructure (CNKI), Web of Science, Cochrane Library, EMBASE, PubMed, and Wanfang. Two researchers analyzed the studies for Newcastle-Ottawa Scale. The software Stata 11.0 was employed for the analysis of the acquired data. The standard mean differences method was utilized for the estimation and quantification of the effect size. Furthermore, a fixed- or random-effects model was employed for conducting a combined analysis. Results: In total, 56 studies were included as per the specific inclusion criteria. The resulting data of the assessed COPD patients in this research indicated a 27% prevalence of sarcopenia. Further analysis of subgroups was executed per disease severity, ethnicity, diagnostic criteria, gender, and age. Per these findings, increased disease severity elevated the prevalence of sarcopenia. The Latin American and Caucasian populations indicated an increased prevalence of sarcopenia. In addition, the prevalence of sarcopenia was related to diagnostic criteria and definition. Male COPD patients had a higher prevalence of sarcopenia than female COPD patients. COPD patients with an average age greater than 65 had a slightly higher prevalence of sarcopenia. COPD patients with comorbid sarcopenia had poorer pulmonary function, activity tolerance, and clinical symptoms than patients with COPD alone. Conclusion: Sarcopenia prevalence is high (27%) in COPD patients. In addition, these patients had worse pulmonary function and activity tolerance compared to patients without sarcopenia. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=367422, identifier CRD42022367422.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.064 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".