Spotlight on Consent: Lessons from the SPOTLIGHT Trial for Acute Intracerebral Hemorrhage
Bibliographic record
Abstract
Abstract Background SPOTLIGHT was a Canadian multicentre, placebo-controlled, randomized trial of emergency treatment with recombinant Factor VIIa for patients with acute intracerebral hemorrhage that enrolled a subset of eligible patients via deferral of consent. We investigated attitudes towards deferral of consent among participants and their legally-authorized representatives (LARs). Methods All participants or LARs approached for enrolment in SPOTLIGHT were invited to complete an 11-item questionnaire within the first 4 days of enrolment, and again at 90 days. Results Eight out of 50 participants in SPOTLIGHT (16%) were enrolled via deferral of consent. Ten LARs for participants (20%) completed the initial survey and 6 completed the 90 day follow-up survey. Ninety percent of respondents agreed with the process of deferral of consent both in principle and specifically for the SPOTLIGHT trial. Participants were more likely to support deferral of consent for low-risk or time-sensitive interventions, or in situations with no alternative treatment options. Conclusions The majority of respondents were supportive of using deferral of consent to enrol participants into SPOTLIGHT and acute stroke trials.
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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 | 0.120 | 0.235 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".