<p>Measuring and monitoring skeletal muscle function in COPD: current perspectives</p>
Bibliographic record
Abstract
Skeletal muscle dysfunction is an important systemic consequence of chronic obstructive pulmonary disease (COPD) that worsens the natural cause of the disease. Up to a third of all people with COPD express some form of impairment which encompasses reductions in strength and endurance, as well as an increased fatigability. Considering this complexity, no single test could be used to measure and monitor all aspects of the impaired skeletal muscle function within the COPD population, resulting in a wide range of available tests and measurement techniques. The aim of the current review is to highlight current and new perspectives relevant to skeletal muscle function measurements within the COPD population in order to provide guidance for researchers as well as for clinicians. First of all, standardized and clinically feasible measurement protocols, as well as normative values and predictive equations across the spectrum of impaired function in COPD, are needed before assessment of skeletal muscle function can become a reality in clinical praxis. This should minimally target the quadriceps muscle; however, depending on the objective of measurements, eg, to determine upper limb muscle function or walking capacity, other muscles could also be tested. Furthermore, even though muscle strength measurements are important, current evidence suggests that other aspects, such as the endurance and power capacity of the muscle, should also be considered. Moreover, although static (isometric) measurements have been favored, dynamic measurements of skeletal muscle function should not be neglected as they, in a larger extent than static measurements, are related to tasks of daily living. Lastly, the often modest relationships between functional tests and skeletal muscle function measurements indicate that they evaluate different constructs and thus cannot replace one another. Therefore, for accurate measurements of skeletal muscle function in people with COPD, specific and formal measurements should still be prioritized.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".