Enrollment of Neonates in More Than One Clinical Trial
Bibliographic record
Abstract
Because the highest rates of morbidity and mortality in neonates are seen in those born at <32 weeks' gestation, this group has the most urgent need for novel therapies to improve survival and outcome. Legislative efforts in the United States and Europe have attempted to address this issue by requiring the study of drugs, biological and nutritional products, devices, and other therapies in this population through a combination of high-quality regulatory and clinical trials, quality improvement initiatives, and observational studies. Because there are relatively small numbers of very preterm neonates born each year in any 1 country or continent, and because a significant number of clinical trials are recruiting at any 1 time, a neonate may meet enrollment criteria for >1 clinical trial. Neonatal units that have the infrastructure and resources to engage in research frequently face the question of whether it is permissible to enroll a neonate in >1 trial. This article examines the pertinent scientific, ethical, regulatory, and industry issues that should be taken into account when considering enrolling neonates in multiple clinical studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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".