COSCA (Core Outcome Set for Cardiac Arrest) in Adults: An Advisory Statement From the International Liaison Committee on Resuscitation
Bibliographic record
Abstract
Cardiac arrest effectiveness trials have traditionally reported outcomes that focus on survival. A lack of consistency in outcome reporting between trials limits the opportunities to pool results for meta-analysis. The COSCA initiative (Core Outcome Set for Cardiac Arrest), a partnership between patients, their partners, clinicians, research scientists, and the International Liaison Committee on Resuscitation, sought to develop a consensus core outcome set for cardiac arrest for effectiveness trials. Core outcome sets are primarily intended for large, randomised clinical effectiveness trials (sometimes referred to as pragmatic trials or phase III/IV trials) rather than for pilot or efficacy studies. A systematic review of the literature combined with qualitative interviews among cardiac arrest survivors was used to generate a list of potential outcome domains. This list was prioritised through a Delphi process, which involved clinicians, patients, and their relatives/partners. An international advisory panel narrowed these down to 3 core domains by debate that led to consensus. The writing group refined recommendations for when these outcomes should be measured and further characterised relevant measurement tools. Consensus emerged that a core outcome set for reporting on effectiveness studies of cardiac arrest (COSCA) in adults should include survival, neurological function, and health-related quality of life. This should be reported as survival status and modified Rankin scale score at hospital discharge, at 30 days, or both. Health-related quality of life should be measured with ≥1 tools from Health Utilities Index version 3, Short-Form 36-Item Health Survey, and EuroQol 5D-5L at 90 days and at periodic intervals up to 1 year after cardiac arrest, if resources allow. © 2018 European Resuscitation Council and American Heart Association, Inc. Published by Elsevier B.V. All rights reserved.
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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 | 0.500 | 0.499 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.014 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.012 | 0.014 |
| Research integrity | 0.030 | 0.050 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".