Treatment guided by cerebral oximetry in mechanically ventilated newborns: a statistical analysis plan for step one of the SafeBoosC-IIIv randomised clinical trial
Bibliographic record
Abstract
BACKGROUND: Newborns requiring invasive mechanical ventilation are at high risk of neurodevelopmental impairment, prolonged hospitalisation, and increased mortality. Treatment guided by cerebral oximetry monitoring has been proposed to reduce morbidity and mortality. METHODS: The SafeBoosC-IIIv trial is a multicentre, parallel-group, randomised clinical trial. The trial will be conducted in two steps. This is a statistical analysis plan for step one. The objective of step one is to assess whether treatment guided by cerebral oximetry monitoring, compared with usual care, increases the number of hospital-free days in newborns receiving invasive mechanical ventilation. Inclusion criteria are gestational age ≥ 28 + 0 weeks, postnatal age less than 28 days, expected to receive invasive mechanical ventilation (intubation) for at least 24 h, and a cerebral oximeter available so monitoring can be started within 6 h after initiation of invasive mechanical ventilation. Exclusion criteria are suspicion of or confirmed brain injury or congenital heart malformation likely to require surgery. A total of 1610 participants will be randomised 1:1 to treatment guided by cerebral oximetry monitoring or usual care. The primary outcome will be hospital-free days within 90 days of randomisation, which will be analysed with the van Elteren test stratified by 'centre'. This statistical analysis plan provides a detailed description of the planned analyses, including methods for handling missing data and assessing statistical assumptions. Analyses will follow the intention-to-treat principle and will be performed independently by two statisticians. CONCLUSION: This statistical analysis plan describes the planned statistical analyses in detail for step one of the SafeBoosC-IIIv trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT05907317. First submitted on 8 June 2023, https://clinicaltrials.gov/study/NCT05907317 .
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".