Why and How Limb Muscle Mass and Function Should Be Measured in Patients with Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Impaired limb muscle function is a common occurrence in patients with chronic obstructive pulmonary disease (COPD), and it negatively influences exercise tolerance, quality of life, and even survival. Assessment of limb muscle mass and function in COPD is highly encouraged; it should include the quadriceps muscle, but other lower and upper limb muscles may also be evaluated to provide valuable information. Quantification of muscle mass as well as assessment of muscle strength and endurance are suggested. Bioelectrical impedance and dual-energy X-ray absorption can be realistically used in the clinical environment to monitor body composition. Although sophisticated computerized dynamometers provide the most accurate assessment, simple exercise and testing equipment are valid alternatives and they should help in implementing limb muscle function assessment in clinical settings. Isometric measurements, using strain-gauges or hand-held dynamometers, should be favored for their simplicity, availability, and quality of information provided. This perspective provides a rationale for the evaluation of limb muscle mass and function in COPD in routine clinical practice. In addition, measurement techniques used to assess limb muscle mass, strength, endurance, and fatigue in various clinical settings are discussed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".