Evidence-based risk assessment and recommendations for physical activity clearance: respiratory disease<sup>1</sup>This paper is one of a selection of papers published in the Special Issue entitled Evidence-based risk assessment and recommendations for physical activity clearance, and has undergone the Journal’s usual peer-review process.
Bibliographic record
Abstract
The 2 most common respiratory diseases are chronic obstructive pulmonary disease (COPD) and asthma. Growing evidence supports the benefits of exercise for all patients with these diseases. Due to the etiology of COPD and the pathophysiology of asthma, there may be some additional risks of exercise for these patients, and hence accurate risk assessment and clearance is needed before patients start exercising. The purpose of this review was to evaluate the available literature regarding the risks of exercise for patients with respiratory disease and provide evidence-based recommendations to guide the screening process. A systematic review of 4 databases was performed. The literature was searched to identify adverse events specific to exercise. For COPD, 102 randomized controlled trials that involved an exercise intervention were included (n = 6938). No study directly assessed the risk of exercise, and only 15 commented on exercise-related adverse events. For asthma, 30 studies of mixed methodologies were included (n = 1278). One study directly assessed the risk of exercise, and 15 commented on exercise-related adverse events. No exercise-related fatalities were reported. The majority of adverse events in COPD patients were musculoskeletal or cardiovascular in nature. In asthma patients, exercise-induced bronchoconstriction and (or) asthma symptoms were the primary adverse events. There is no direct evidence regarding the risk of exercise for patients with COPD or asthma. However, based on the available literature, it would appear that with adequate screening and optimal medical therapy, the risk of exercise for these respiratory patients is low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.074 | 0.304 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".