Adverse effects of red blood cell transfusions in neonates: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Controversy exists regarding the contribution of blood transfusions to a range of adverse clinical outcomes in neonates. The aim of our systematic review was to identify the broader literature on harmful effects and associations potentially attributable to red blood cell (RBC) transfusions. STUDY DESIGN AND METHODS: A comprehensive search of MEDLINE (PubMed) and EMBASE was undertaken. Eligible studies included both randomized controlled trials (RCTs) and nonrandomized studies examining the effects of small volume (10-20 mL/kg) RBC transfusions on neonates. Primary outcomes of interest were mortality, chronic lung disease, retinopathy of prematurity, necrotizing enterocolitis, and intraventricular hemorrhage. Two independent authors conducted a review of abstracts and then of full-text article reviews as well as data extraction and quality assessments. RESULTS: Sixty-one studies were eligible for inclusion, including 16 (26%) randomized studies. The majority of studies were nonrandomized (n = 45; 74%), which included 32 observational studies with and 13 studies without a comparator group. There was no evidence that rates of mortality differed between restrictive and liberal strategies for transfusion (eight RCTs: risk ratio, 1.24; 95% confidence interval, 0.89-1.672, heterogeneity = 0%) or for necrotizing enterocolitis (five RCTs: risk ratio, 1.45; 95% confidence interval, 0.91-2.33; heterogeneity = 0%). A liberal strategy also was not superior to restrictive transfusion practice in the pooled randomized studies for rates of retinopathy of prematurity, chronic lung disease, or intraventricular hemorrhage. CONCLUSIONS: Statistically significant differences in a range of harmful outcomes between neonates exposed to restrictive and liberal RBC transfusion practice were not found. However, the risks of bias identified in many studies and the lack of consistent reporting and definitions of events limits our conclusions.
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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 | 0.018 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.031 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".