Transfusion Practices in 12 Neonatal Networks: Are We Closer to Adopting a Restrictive Transfusion Approach?
Bibliographic record
Abstract
Introduction: Recent evidence suggests a restrictive approach toward blood transfusions for management of preterm infants. Objective was to survey blood transfusion practises in preterm neonates <29 weeks' gestation among 12 population-based neonatal networks participating in the International Network for Evaluating Outcomes in Neonates (iNeo). METHODS: An online survey based on 2023 practices was sent to 608 neonatal intensive care units (NICUs): Australia/New Zealand (30), Brazil (20), Canada (32), Finland (5), France (70), Israel (26), Japan (292), Poland (56), Spain (55), Sweden (9), Switzerland (9), and Tuscany, Italy (4). Transfusion thresholds in 4 different scenarios were surveyed: (a) infants invasively ventilated within first 7 postnatal days, (b) infants invasively ventilated after 7 days, (c) stable infants on noninvasive respiratory support, and (d) stable infants requiring no respiratory support. RESULTS: A total of 382 NICUs (63%) responded. Transfusion practices varied within networks and between countries. For invasively ventilated infants, the transfusion threshold during first 7 days after birth was a hematocrit <underline>≤</underline>35% in 79% of NICUs, and at an age ≥8 days, the transfusion threshold was a hematocrit <underline>≤</underline>30% in 68% of NICUs. For stable infants on noninvasive ventilation, the transfusion threshold was a hematocrit <underline>≤</underline>30% in 80%, and in those without respiratory support, the transfusion threshold was a hematocrit of <underline>≤</underline>25% in 68% of NICUs. CONCLUSIONS: Variations exist in blood transfusion practises between countries and within networks. A restrictive transfusion approach based on recent recommendations has been adopted by more than two-thirds of NICUs. Additional research is needed to evaluate whether practices align with intentions and how they impact outcomes. .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".