Differences in maternal–newborn ABO blood groups and risk of serious infant infection
Bibliographic record
Abstract
BACKGROUND: During pregnancy, various maternal IgG antibodies are transferred to the developing fetus, some of which may protect the newborn against infection. If a mother and her fetus have different A, B or O (ABO) blood groups, then transferred maternal antibodies may plausibly protect the infant against infection. AIM: To determine if maternal-newborn ABO blood group incongruence vs. congruence is associated with a lower risk of serious infection in the infant. DESIGN: Retrospective population-based cohort. METHODS: We used linked patient-level datasets for all singleton hospital livebirths from 2008 to 2022 in Ontario, Canada, with known maternal and newborn ABO blood groups. We used a dichotomous exposure state, either ABO blood group congruent (N = 114 507) or incongruent (N = 43 074). The main outcome of interest was the risk of serious infant infection within 27 days, and from 28 to 365 days, after birth. Cox proportional hazard models generated hazard ratios and 95% confidence intervals, and were adjusted for maternal age, world region of origin, residential income quintile and gestational age at birth. RESULTS: Relative to maternal-newborn congruency, incongruent ABO blood group was associated with an adjusted hazard ratio of 0.88 (95% CI: 0.80-0.97) for serious neonatal infection within 27 days of birth, and 0.93 (95% CI: 0.90-0.96) for serious infection between 28 and 365 days after birth. CONCLUSIONS: Maternal-newborn ABO incongruence may be associated with a lower relative risk of a serious infant infection within 27 days, and from 28 to 365 days, after birth.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".