Emergency research without prior consent in the United States, Canada, European Union and United Kingdom: How regulatory differences affect study design and implementation in cardiac arrest trials
Bibliographic record
Abstract
Aim: A major barrier to performing cardiac arrest trials is the requirement for prospective informed consent, which is often infeasible during individual medical emergencies. In an effort to improve outcomes, some governments have adopted legislation permitting research without prior consent (RWPC) in these circumstances. We aimed to outline key differences between legislation in four Western locations and explore the effects of these differences on trial design and implementation in cardiac arrest research. Data sources: We performed a narrative review of RWPC legislation in the United States (US), Canada, the European Union (EU) and the United Kingdom (UK). Results: The primary criteria required to perform RWPC was similar across locations: the study must involve an individual medical emergency during which neither the prospective subject nor their authorized representative can provide informed consent. The US regulations were unique in their requirements for performing Community Consultation and Public Disclosure in the communities in which the research takes place. Another major difference was the requirement for consent for ongoing participation in Canada, the EU and the UK, while only notification of enrollment and the opportunity to discontinue participation are required in the US. Additionally, only Canada and the EU explicitly state that the subject or their representative may request withdrawal of their data. Conclusion: Regulations governing RWPC in the US, Canada, the EU and the UK have similar goals and protections for vulnerable populations during medical emergencies. Differences in the qualifying criteria and implementation procedures exist across locations and may affect study design.
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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 | 0.672 | 0.778 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".