Necrotizing enterocolitis and mortality after transfusion of <scp>ABO non‐identical</scp> blood
Bibliographic record
Abstract
BACKGROUND: The relationship between ABO non-identical transfusion and the outcomes of necrotizing enterocolitis (NEC), and all-cause mortality in very-low birth weight (VLBW) neonates receiving red blood cell transfusion is unknown. STUDY DESIGN AND METHODS: A retrospective multicenter cohort study was conducted in VLBW neonates in neonatal intensive care units between 2004 and 2016. VLBW (≤1500 grams) neonates were followed until discharge or in-hospital death. The primary exposure was ABO group. Secondary exposures included platelet count, plasma transfusions, and maternal ABO group. Outcome measures were NEC (defined as Bell stage ≥ 2) and all-cause mortality. Time-dependent Cox regression models with competing risks were used to investigate factors associated with NEC and mortality. RESULTS: Thousand and sixteen neonates were included with 10.8% developing NEC (n = 110) and 14.1% mortality (n = 143). Platelet count (hazard ratio [HR] = 0.995; 95% confidence interval [CI]: 0.922-0.998) and number of plasma transfusions (HR = 2.908; 95% CI:1.265-6.682) were associated with NEC, while ABO group (non-O vs. O) was not (HR = 0.761; 95% CI: 0.393-1.471). Higher all-cause mortality occurred in neonates without NEC who were non-O compared with O (HR = 17.5; 95% CI: 1.784-171.692), but not in neonates with NEC (HR = 1.112; 95% CI: 0.142-8.841). Plasma transfusion was associated with increased mortality in both groups. DISCUSSION: ABO non-identical transfusion was not associated with NEC or mortality in neonates with NEC. It was associated with increased mortality in neonates without NEC. As many neonatal intensive care units transfuse only O group blood as routine practice, future trials are needed to investigate the association between this practice and neonatal mortality.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".