Platelets for Neonatal Transfusion - Study 2: A Randomised Controlled Trial to Compare Two Different Platelet Count Thresholds for Prophylactic Platelet Transfusion to Preterm Neonates
Bibliographic record
Abstract
INTRODUCTION: Neonatal thrombocytopenia is a common and important clinical problem in preterm neonates. A trial assessing clinically relevant outcomes in relation to the different platelet count thresholds used to trigger transfusion has never been undertaken in preterm neonates with severe thrombocytopenia. OBJECTIVES: Platelets for Neonatal Transfusion - Study 2 (PlaNeT-2) aims to assess whether a higher prophylactic platelet transfusion threshold is superior to the lower thresholds in current standard practice in reducing the proportion of patients who have a major bleed or die up to study day 28. METHODS: PlaNeT-2 is a two-stage, randomised, parallel-group, superiority trial. PlaNet-2 compares clinical outcomes in preterm neonates (<34 weeks' gestation at birth) randomised to receive prophylactic platelet transfusions to maintain platelet counts at or above either 25 × 10(9)/l or 50 × 10(9)/l. The primary outcome measure is the proportion of patients who either die or experience a major bleed up to and including study day 28. A total of 660 infants will be randomised. RESULTS AND CONCLUSIONS: This trial will help define optimal platelet transfusion support for severely thrombocytopenic preterm neonates by evaluating the risks and benefits of two different prophylactic neonatal platelet transfusion thresholds.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".