Multiple breath washout in bronchiectasis clinical trials: is it feasible?
Bibliographic record
Abstract
BACKGROUND: Evaluation of multiple breath washout (MBW) set-up including staff training, certification and central "over-reading" for data quality control is essential to determine the feasibility of MBW in future bronchiectasis studies. AIMS: To assess the outcomes of a MBW training, certification and central over-reading programme. METHODS: MBW training and certification was conducted in European sites collecting lung clearance index (LCI) data in the BronchUK Clinimetrics and/or i-BEST-1 studies. The blended training programme included the use of an eLearning tool and a 1-day face-to-face session. Sites submitted MBW data to trained central over-readers who determined validity and quality. RESULTS: Thirteen training days were delivered to 56 participants from 22 sites. Of 22 sites, 18 (82%) were MBW naïve. Participant knowledge and confidence increased significantly (p<0.001). By the end of the study recruitment, 15 of 22 sites (68%) had completed certification with a mean (range) time since training of 6.2 (3-14) months. In the BronchUK Clinimetrics study, 468 of 589 (79%) tests met the quality criteria following central over-reading, compared with 137 of 236 (58%) tests in the i-BEST-1 study. CONCLUSIONS: LCI is feasible in a bronchiectasis multicentre clinical trial setting; however, consideration of site experience in terms of training as well as assessment of skill drift and the need for re-training may be important to reduce time to certification and optimise data quality. Longer times to certification, a higher percentage of naïve sites and patients with worse lung function may have contributed to the lower success rate in the i-BEST-1 study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".