Current Understanding of Transfusion-associated Necrotizing Enterocolitis: Review of Clinical and Experimental Studies and a Call for More Definitive Evidence
Bibliographic record
Abstract
Introduction: The association between red blood cell (RBC) transfusions and necrotizing enterocolitis (NEC), so-called transfusion-associated NEC (ta-NEC), was first described in 1987. However, further work is needed to confirm a causal relationship, elucidate underlying mechanisms, and develop possible strategies for prevention. We performed an extensive literature search in the databases PubMed, EMBASE, and Scopus. Areas covered: Although multiple retrospective human studies have strongly suggested an association between blood transfusions and subsequent occurrence of NEC, meta-analyses of randomized controlled trials (RCTs) testing RBC transfusion thresholds or the use of recombinant erythropoiesis-stimulating growth factors did not confirm an association of anemia with ta-NEC. These conflicting data necessitated the development of an animal model to elucidate mechanisms and causal factors. Data from this recent mouse model of ta-NEC highlighted the importance of sequential exposure to severe anemia followed by transfusion for development of ta-NEC. Expert opinion: This review summarizes current human and experimental data, highlights open questions, and suggests avenues for further research aimed at preventing ta-NEC in preterm infants. Further studies are required to delineate whether there is a tipping point, in terms of the level and duration of anemia, and to develop an effective strategy for blood management and the quality of RBC transfusions.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".