Prevalence of Congenital Hypothyroidism in Iranian Neonates: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background Congenital hypothyroidism, characterized by insufficient thyroid hormone production at birth, significantly impacts neonatal growth and development.This deficiency can impair neonatal growth and development.This study aimed to estimate the prevalence of congenital hypothyroidism in Iranian neonates through a systematic review and meta-analysis.Methods A systematic search was conducted in PubMed, Scopus, Web of Science, Science Direct, SID, and Magiran up to January 2025 to identify relevant studies.Manual searches of key review articles and primary studies were also performed.Only studies published in Persian or English were included.The Newcastle-Ottawa Scale checklist was used to assess the risk of bias in the selected studies.Data were analyzed using Comprehensive Meta-Analysis software (version 3). ResultsThirty-nine studies, comprising 3,124,702 neonates, were included in the analysis.The meta-analysis showed a congenital hypothyroidism prevalence of 2 per 1000 live births (95% CI: 0.002-0.003;p < 0.05).The prevalence was 3 per 1000 live births in both males (95% CI: 0.002-0.004;p < 0.05) and females (95% CI: 0.002-0.004;p < 0.05).No significant publication bias was observed (p > 0.05). ConclusionThe elevated prevalence of congenital hypothyroidism in Iran highlights the necessity for enhanced screening programs, early diagnostic protocols, intervention, and allocation of necessary resources are essential for the effective management of congenital hypothyroidism prevalence.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".