Selective prophylactic solvent-detergent plasma and cryoprecipitate transfusion to prevent intraventricular hemorrhage in extreme preterm infants: A case-historical control
Bibliographic record
Abstract
BACKGROUND: Contradictory evidence exists whether a prophylactic coagulation factor transfusion in the first hours of life (HOL) prevents intraventricular hemorrhage (IVH) in extreme preterm infants (EPI, <28 weeks gestation). We aimed to determine whether selective prophylactic solvent-detergent plasma and cryoprecipitate transfusion within 12 hours of life (SP-SDP/Cryoprecipitate-T) could prevent IVH in EPI. METHOD: This is a retrospective analysis, case-historical control, of prospectively collected data from a pre-existing electronic neonatal database at a Saudi tertiary neonatal intensive care unit. We compared the IVH rate in EPI born in the first 4 years (Jan 2010-Dec 2013) of the SP-SDP/Cryoprecipitate-T period with that of EPI born during the last 4 years (Jan 2006-Dec 2009) of the rescue SDP/Cryoprecipitate-T period. RESULTS: The IVH rate was lower in the SP compared to the rescue- SDP/Cryoprecipitate-T period (30.8% versus 51.2%, odds ratio 0.42, 95% confidence interval 0.21, 0.88, p = 0.02). This difference remained significant after controlling for six other IVH risk factors. CONCLUSIONS: Early SP-SDP/Cryoprecipitate-T may reduce the IVH rate in EPI. A large multicenter clinical trial is required for confirm the short and long-term benefit and risk of this intervention. Until then, early SP-SDP/Cryoprecipitate-T may be considered by an institution with a persistently high IVH rate.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".