Long-Term Exercise Therapy for Chronic Obstructive Lung Disease
Bibliographic record
Abstract
13 patients with chronic obstructive lung disease – 6 with emphysema (E) or emphysema + chronic bronchitis (EB), 7 with pure chronic bronchitis (B) – undertook during 1 year a progressive endurance training, 6 of the subjects continuing for a second year. The E patients were generally more disabled than the B patients, with less lean tissue, poorer muscular endurance, and CO2 retention during exercise. However, initial tolerance of submaximal aerobic work (65% of age-related normal) was comparable in E and B patients. Eight of the 13 patients noted symptomatic improvements over the first year of conditioning, with reductions of heart rate at a standard submaximal work load and gains of predicted aerobic power (8% in E, 15% in B). Larger improvements were usual in those who exercised faithfully. Gains over the year included increases of muscular endurance (B > E), a small reduction of oxygen debt, a diminution of air trapping and CO2 retention (E group), and a cessation of deterioration in lung volumes (B group). Symptomatic improvements reflect the support of an interested medical team, increases of muscle strength and gains of cardio-respiratory condition. Training breaks the vicious circle of dyspnoea, inactivity and worsening dyspnoea. The apparent arrest of declining lung volumes in B patients merits confirmation on a larger sample observed for a longer period
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".