BronchUK: protocol for an observational cohort study and biobank in bronchiectasis
Bibliographic record
Abstract
Bronchiectasis has been a largely overlooked disease area in respiratory medicine. This is reflected by a shortage of large-scale studies and lack of approved therapies, in turn leading to a variation of treatment across centres. BronchUK (Bronchiectasis Observational Cohort and Biobank UK) is a multicentre, prospective, observational cohort study working collaboratively with the European Multicentre Bronchiectasis Audit and Research Collaboration project. The inclusion criteria for patients entering the study are a clinical history consistent with bronchiectasis and computed tomography demonstrating bronchiectasis. Main exclusion criteria are 1) patients unable to provide informed consent, 2) bronchiectasis due to known cystic fibrosis or where bronchiectasis is not the main or co-dominant respiratory disease, 3) age <18 years, and 4) prior lung transplantation for bronchiectasis. The study is aligned to standard UK National Health Service (NHS) practice with an aim to recruit a minimum of 1500 patients from across at least nine secondary care centres. Patient data collected at baseline includes demographics, aetiology testing, comorbidities, lung function, radiology, treatments, microbiology and quality of life. Patients are followed up annually for a maximum of 5 years and, where able, blood and/or sputa samples are collected and stored in a central biobank. BronchUK aims to collect robust longitudinal data that can be used for analysis into current NHS practice and patient outcomes, and to become an integral resource to better inform future interventional studies in bronchiectasis.
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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 | 0.045 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.105 | 0.024 |
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".