Responses to Written Notification during Out-of-hospital Care Trials Using Waiver of Informed Consent
Bibliographic record
Abstract
Background: Resuscitation research has been allowed to proceed using waiver of consent when compliance with guidelines is assured. In these circumstances, institutional review boards (IRBs) may request notification of enrolled patients. Objectives: To describe the notification process developed with IRB feedback and implemented in two out-of-hospital randomized controlled trials (RCTs) in a large urban setting. Methods: This was a descriptive review of two RCTs recruiting a total of 620 patients: the Out-of-hospital Cardiac Arrest Rectilinear Biphasic to Monophasic Damped Sine Defibrillation Waveforms with Advanced Life Support Intervention Trial (ORBIT), which compared rectilinear biphasic and monophasic damped sine waveform for out-of-hospital cardiac arrest, and the Prehospital Pacing versus Conventional Treatment Effectiveness Trial (PrePACE), which compared dopamine and transcutaneous pacing for unstable bradycardia. Results: The ORBIT study enrolled 538 patients. In 44 (8%) patients, contact information could not be obtained. Notification was attempted for 494 (92%) patients; 48 (10%) letters were returned to sender. Researchers were contacted by telephone regarding 37 (8%) subjects: 16 (43%) requested information, 14 (38%) responded positively, and one (3%) did not return follow-up calls. Overall, two (0.4%) were withdrawn from the study. The PrePACE study enrolled 82 subjects. Contact information was unavailable for one (1%). For the remaining 81 patients, four (5%) letters were returned to sender. Researchers were contacted regarding ten (13%) subjects: seven (70%) requested information, two (20%) responded positively, and one (10%) did not return follow-up calls. No patient was withdrawn from the study. Conclusions: Contact information may be difficult to obtain for up to 20% of out-of-hospital critical patients. In 8% to 13% of cases, patients or designates contacted researchers; most feedback was positive. Frequently, non-study-related information was requested, consuming significant resources. Using this method, fewer than 1% of patients were withdrawn from the studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".