Coenrollment in a Randomized Trial of High-Frequency Oscillation
Bibliographic record
Abstract
OBJECTIVE: Enrollment of individual patients into more than one study has been poorly evaluated. The objective of this study was to describe the characteristics of patients, researchers and centers involved in coenrollment, studies precluding coenrollment, and the prevalence, patterns, predictors, and outcomes of coenrollment in a randomized clinical trial. DESIGN, SETTING, METHODS: We conducted an observational study nested within the OSCILLation for Acute Respiratory Distress Syndrome Treated Early Trial, which compared high-frequency oscillatory ventilation to conventional ventilation. We collected patient, center, and study data on coenrollment in randomized patients. Multilevel regression examined factors independently associated with coenrollment, considering clustering within centers. We examined the effect of coenrollment on safety and the trial outcome. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Overall, 127 of 548 randomized patients (23.2%) were coenrolled in 25 unique studies. Coenrollment was reported in 17 of 39 centers (43.6%). Patients were most commonly coenrolled in one additional randomized clinical trial (76; 59.8%). Coenrollment was less likely in older patients (odds ratio, 0.87; 95% CI, 0.76-0.997), and in ICUs with greater than 26 beds (odds ratio, 0.56; 95% CI, 0.34-0.94), and more likely by investigators with more than 11 years of experience (odds ratio, 1.73; 95% CI, 1.06-2.82), by research coordinators with more than 8 years of experience (odds ratio, 1.87; 95% CI, 1.11-3.18) and in Canada (odds ratio, 4.66; 95% CI, 1.43-15.15). Serious adverse events were similar between coenrolled high-frequency oscillatory ventilation and control patients. Coenrollment did not modify the treatment effect of high-frequency oscillatory ventilation on hospital mortality. CONCLUSIONS: Coenrollment occurred in 23% of patients, commonly in younger patients, in smaller centers with more research infrastructure, and in Canada. Coenrollment did not influence patient safety or trial results.
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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 | 0.113 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".