Zika Virus‐Related Birth Defects and Neurological Complications: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Zika virus (ZIKV) is a virus transmitted by arthropods that exhibits considerable pathogenicity, resulting in a significant health and economic impact worldwide. A rise in congenital anomalies has been noted in kids born to mothers who have infections during pregnancy, alongside a rise in neurological symptoms in adults. In this study, we reassessed the data on brain abnormalities in maternal infection with ZIKV during pregnancy through a systematic review and meta-analysis. A thorough search was carried out in the PubMed, Scopus, Web of Science and Embase databases to extract pertinent published data up to November, 2024. In this meta-analysis, 14 studies with 912 individuals were incorporated. Subgroup analyses, depending on the maternal age, gestational age at detection of brain abnormalities, the time of ZIKV diagnosis, type of sample and birth weight at delivery, were performed. Critical appraisal was completed using the Newcastle-Ottawa Scale (NOS) tools. In this analysis, we identified 14 studies that reported brain abnormalities in newborn infants with ZIKV-infected pregnant women, of which 58% studies were from Brazil. The overall birth defect with brain abnormalities was found to be (1.94 [95% CI: 1.3-2.7], P = 0.00). Of the most common brain abnormalities, microcephaly (OR: 2.7 [95% CI 1.5-4.7], P = 0.00), ventriculomegaly (OR: 1.7 [95% CI 0.91-3.3], P = 0.09) and corpus callosal anomaly (OR: 1.8 [95% CI 1.02-3.3], P = 0.04) had highest the risk in children with ZIKV-infected pregnant women. No publication bias was found when applying the Begg's rank correlation and Egger's linear regression tests (P = 1 and P = 0.44, respectively). subgroups of maternal age ≥ 30 years and gestational week of ZIKV diagnosis ≥ 25 weeks are important in zika-associated birth defects. This systematic review and meta-analysis evidenced a high risk of brain defects in ZIKV-infected pregnant women. Maternal age and gestational week of ZIKV diagnosis may modify this risk.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".