Comparison of Consent Models in a Randomized Trial of Corticosteroids in Pediatric Septic Shock*
Bibliographic record
Abstract
OBJECTIVES: To describe the use of deferred and prior informed consent models in the context of a low additional risk to standard of care, placebo-controlled randomized controlled trial of corticosteroids in pediatric septic shock. DESIGN: An observational substudy of consent processes in a randomized controlled trial of hydrocortisone versus placebo. SETTING: Seven tertiary level PICUs in Canada. PATIENTS: Children newborn to 17 years inclusive admitted to PICU with suspected septic shock between July 2014 and March 2016. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Information on the number of families approached, consent rates obtained, and spontaneously volunteered reasons for nonparticipation were collected for both deferred and informed consent. The research ethics board of five of seven centers approved a deferred consent model; however, implementation criteria for use of this model varied across sites. The consent rate using deferred versus prior informed consent was significantly higher (83%; 35/42 vs 58%; 15/26; p = 0.02). The mean times from meeting inclusion criteria to randomization (1.8 ± 1.8 vs 3.6 ± 2.1 hr; p = 0.007) and study drug administration (3.4 ± 2.7 hr vs 4.8 ± 2.1 hr; p = 0.05) were significantly shorter with the use of deferred consent versus prior informed consent. No family member or research ethics board expressed concern following use of deferred consent. CONCLUSIONS: Deferred consent was acceptable in time-sensitive critical care research to most research ethics boards, families, and healthcare providers and resulted in higher consent rates and more efficient recruitment. Larger studies on deferred consent and consistency interpreting jurisdictional guidelines are needed to advance pediatric acute care.
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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 | 0.090 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".