Global Prevalence of Duodenal Atresia in Trisomy 21: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Duodenal atresia is one of significant causes of neonatal intestinal obstruction. It often co-occurs with Down syndrome. This study is conducted to estimate the global prevalence of duodenal atresia in Down syndrome patients and to investigate associated factors. METHODS: Conducting a systematic review with meta-analysis of 18 eligible studies reporting duodenal atresia prevalence in pediatric Down syndrome patients. Study quality is assessed using the Newcastle-Ottawa Scale. The subgroup analysis on region, study quality, publication year, and design is addressed. Gender-specific prevalence rates are examined. RESULTS: The pooled prevalence of duodenal atresia in Down syndrome is 3.0%, with significant heterogeneity. The Middle East reports a higher prevalence of 6.0%, while Latin America, India, and Canada exhibit a lower prevalence of 1.0%. High-quality studies demonstrate 2% prevalence, while moderate-quality studies report 4.0%. Gender analysis indicates a similar incidence for females and males at 3.0%. Prevalence varies with study design: case-control studies report 4.0%, cross-sectional studies report 2.0%, and prospective cohort studies report 2.0%. CONCLUSIONS: Duodenal atresia is common in Down syndrome patients, affecting 3.0% of the patients worldwide. Regional variations exist, necessitating further investigation. Gender does not significantly impact prevalence. This study highlights the need for region-specific research to enhance clinical decision-making for individuals with Down syndrome and duodenal atresia.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.032 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".