Total effect of gestational hypertension on neonatal iron deficiency in very-preterm infants.
Bibliographic record
Abstract
Abstract Background: Gestational hypertension (GH) is a major risk factor for adverse maternal and perinatal morbidity and outcomes, including placental dysfunction, preterm birth, and fetal growth restriction. Maternal GH is thought to disrupt placental perfusion, potentially reducing placental blood flow and nutrient transfer to the fetus. Moreover, elevated maternal hepcidin reported in pre-eclampsia and some hypertensive pregnancies could impair placental iron transfer in hypertensive pregnancies leading to neonatal iron deficiency and heightened risks of anemia-related developmental impairment. Prior research has highlighted the role of maternal anemia and iron status in neonatal health, but limited studies have explored the specific impact of GH on neonatal iron metabolism. Given the robust pool of evidence highlighting the long-term negative consequences of iron deficiency (ID) during development, it is imperative to identify and address potential sources of ID where possible. This study aims to evaluate whether maternal GH is independently associated with lower neonatal iron status (assessed by serum ferritin) at NICU discharge in very preterm infants. Methods: Guided by a directed acyclic graph, we estimated the total effect of GH on ID using multivariable logistic regression. Covariates entered a priori consisted of maternal anemia, body-mass index, age, smoking during pregnancy, twin gestation, and infant sex. These variables were chosen for their potential to influence both maternal blood pressure and neonatal iron status. Gestational age and birthweight were intentionally omitted to avoid adjustment for post-exposure mediators. Missing data were addressed with 20-fold multiple imputation. Results are reported as adjusted odds ratios (aOR) with 95 % confidence intervals (CI). This analysis drew from a retrospective population-based cohort of very preterm infants (< 32 weeks gestation) born at the IWK Health Centre between 2005 and 2018 to mothers residing in Nova Scotia. Infants with major congenital malformations, chromosomal anomalies, or death before discharge were excluded. Unit protocol provided elemental iron prophylaxis at 2–4 mg/kg/day beginning at 2–4 weeks of age, with dose increases (up to 6 mg/kg/day) guided by serum ferritin (SF) checks every 2–4 weeks. ID at discharge was defined as SF < 50 µg/L. Antenatal and neonatal variables were abstracted from electronic and paper records. Results:Of 262 very-preterm infants, 82 (31.3 %) were iron-deficient at NICU discharge despite supplementation. GH affected 45 (17.2%) of mothers. Iron-deficiency occurred in 48.9% (n = 22/45) of GH-exposed vs 27.6% (n = 60/217) of non-exposed infants (crude OR = 2.50; 95% CI 1.30 – 4.84; p < 0.05). After multiple imputation and adjustment for maternal anemia, body-mass index, age, cigarette use during pregnancy, twin gestation, and neonatal sex, GH remained the only independent predictor of discharge iron-deficiency (aOR = 2.28; 95 % CI 1.13 – 4.62; p < 0.05). No other covariate reached statistical significance. Model diagnostics indicated good fit and no serious collinearity (Hosmer–Lemeshow p = 0.68; all variance-inflation factors < 2). Conclusion: Gestational hypertension markedly increases the risk of iron deficiency in very-preterm infants at NICU discharge, even under standardized iron-supplementation protocols. These findings support the hypothesis that in utero factors linked to GH can diminish the efficacy of standardized post-natal iron therapy. Furthermore, these results could justify closer monitoring or tailored iron dosing for GH-exposed infants, pending prospective studies. Moreover, the present findings underscore the importance of optimizing maternal cardiovascular and hematologic health during pregnancy.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".