Core Outcomes in Ventilation Trials (COVenT): protocol for a core outcome set using a Delphi survey with a nested randomised trial and observational cohort study
Bibliographic record
Abstract
BACKGROUND: Among clinical trials of interventions that aim to modify time spent on mechanical ventilation for critically ill patients there is considerable inconsistency in chosen outcomes and how they are measured. The Core Outcomes in Ventilation Trials (COVenT) study aims to develop a set of core outcomes for use in future ventilation trials in mechanically ventilated adults and children. METHODS/DESIGN: We will use a mixed methods approach that incorporates a randomised trial nested within a Delphi study and a consensus meeting. Additionally, we will conduct an observational cohort study to evaluate uptake of the core outcome set in published studies at 5 and 10 years following core outcome set publication. The three-round online Delphi study will use a list of outcomes that have been reported previously in a review of ventilation trials. The Delphi panel will include a range of stakeholder groups including patient support groups. The panel will be randomised to one of three feedback methods to assess the impact of the feedback mechanism on subsequent ranking of outcomes. A final consensus meeting will be held with stakeholder representatives to review outcomes. DISCUSSION: The COVenT study aims to develop a core outcome set for ventilation trials in critical care, explore the best Delphi feedback mechanism for achieving consensus and determine if participation increases use of the core outcome set in the long term.
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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 | 0.321 | 0.239 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.040 | 0.010 |
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".