Peripheral Muscle Wasting in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Peripheral muscle wasting is a common finding in advanced chronic obstructive pulmonary disease (COPD) and several other chronic diseases. Although muscle wasting has long been recognized by clinicians (1), its relevance to patients' outcome and management has been overlooked. There is a renewed interest in this problem in respiratory and other chronic diseases as recent advances in clinical research have confirmed the negative impact of muscle wasting on patient survival (2, 3). At the same time, exciting and innovative research in molecular biology is improving our understanding of how muscle mass is maintained (4, 5). Effective treatment for muscle wasting has yet to be developed, but there is now evidence, from animal and human studies, that muscle mass may he manipulated with success in wasting disorders (4). As a result of this research, new molecules specifically targeted at maintaining or increasing muscle mass in patients with COPD or other chronic conditions should become available in the future. In this pulmonary perspective, the clinical significance of muscle wasting associated with COPD will he briefly reviewed, taking into account the knowledge obtained from the study of other chronic diseases. Based upon new developments in molecular biology, possible mechanisms leading to muscle wasting and potential therapeutic strategies will be presented as well as suggestions for future research. It is not the scope of the present study to provide a complete review of the literature on peripheral muscle function in COPD, which can be found elsewhere (6, 7).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".