Protocol for establishing a core outcome set for evaluation in studies of pulmonary exacerbations in people with cystic fibrosis
Bibliographic record
Abstract
INTRODUCTION: Pulmonary exacerbations are associated with increased morbidity and mortality in people with cystic fibrosis (CF). There is no consensus about which outcomes should be evaluated in studies of pulmonary exacerbations or how these outcomes should be measured. Outcomes of importance to people with lived experience of the disease are frequently omitted or inconsistently reported in studies, which limits the value of such studies for informing practice and policy. To better standardise outcome reporting and measurement, we aim to develop a core outcome set for studies of pulmonary exacerbations in people with CF (COS-PEX) and consensus recommendations for measurement of core outcomes. METHODS AND ANALYSIS: Preliminary work for development of COS-PEX has been reported, including (1) systematic reviews of outcomes and methods for measurement reported in existing studies of pulmonary exacerbations; (2) workshops with people affected by CF within Australia; and (3) a Bayesian knowledge expert elicitation workshop with health professionals to ascertain outcomes of importance. Here we describe a protocol for the additional stages required for COS-PEX development and consensus methods for measurement of core outcomes. These include (1) an international two-round online Delphi survey and (2) consensus workshops to review and endorse the proposed COS-PEX and to agree with methods for measurement. ETHICS AND DISSEMINATION: National mutual ethics scheme approval has been provided by the Child and Adolescent Health Service Human Research Ethics Committee (RGS 4926). Results will be disseminated via consumer and research networks and peer-reviewed publications. This study is registered with the Core Outcome Measures in Effectiveness Trials database.
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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 | 0.258 | 0.275 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.107 | 0.036 |
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; the direct Gemma label and the distilled Codex classifier 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".