Maternal zinc deficiency and congenital anomalies in newborns
Bibliographic record
Abstract
BACKGROUND: Zinc deficiency in pregnant women is common, especially in the third trimester of pregnancy. The available data, however, on the association between zinc deficiency and congenital malformations in the Iranian population are insufficient. The aim of this study was therefore to determine whether maternal serum zinc deficiency is associated with major congenital malformations in newborns. METHODS: This descriptive, case-control study involved mothers of 80 neonates with congenital anomalies (study group) admitted to the Mofid Children's Hospital, Tehran, Iran. During the same period (2014 and 2015), serum zinc was measured in 80 mothers who had delivered normal newborns without congenital malformations (control group). RESULTS: Mothers with serum zinc deficiency had a more than sevenfold risk of malformations in the fetus compared with mothers with normal serum zinc (OR, 7.013; 95%CI: 2.716-18.110). Newborns with malformation weighing ≤2500 g were associated with lower maternal serum zinc compared with the control group (P = 0.006). CONCLUSIONS: There is an association between congenital malformation in newborns and maternal zinc deficiency.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".