Effects of a Partially Supervised Conditioning Program in Cystic Fibrosis: An International Multicenter, Randomized Controlled Trial (ACTIVATE-CF)
Bibliographic record
Abstract
Abstract Rationale The long-term effects of vigorous physical activity (PA) on lung function in cystic fibrosis are unclear. Objectives To evaluate effects of a 12-month partially supervised PA intervention using motivational feedback. Methods In a parallel-arm multicenter randomized controlled trial (ACTIVATE-CF), relatively inactive patients aged at least 12 years were randomly assigned (1:1 ratio) to an intervention group or control group. The intervention group consented to add 3 hours of vigorous PA per week, whereas the control group was asked not to change their PA behavior. Primary endpoint was change in percent predicted FEV1 (ΔFEV1) at 6 months. Secondary endpoints included PA, exercise capacity, exercise motives, time to first exacerbation and exacerbation rates, quality of life, anxiety, depression, stress, and blood glucose control. Data were analyzed using mixed linear models. Measurements and Main Results A total of 117 patients (40% of target sample size) were randomized to an intervention (n = 60) or control group (n = 57). After 6 months, ΔFEV1 was significantly higher in the control group compared with the intervention group (2.70% predicted [95% confidence interval, 0.13–5.26]; P = 0.04). The intervention group reported increased vigorous PA compared with the control group at each study visit, had higher exercise capacity at 6 and 12 months, and higher PA at 12 months. No effects were seen in other secondary outcomes. Conclusions ACTIVATE-CF increased vigorous PA and exercise capacity, with effects carried over for the subsequent 6 months, but resulted in better FEV1 in the control group.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".