Gender and birth weight as risk factors for anastomotic stricture after esophageal atresia repair: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Anastomotic stricture (AS) is the most frequently occurring complication that occurs after esophageal atresia (EA) repair. Nevertheless, the pathogenesis remains primarily unknown and there is inadequate knowledge regarding the risk factors for AS. Therefore, a systematic review of the literature and a meta-analysis was performed to investigate whether gender and birth weight were risk factors for the development of AS following EA repair. METHODS: The main outcome measure was the occurrence of AS. Forest plots with odds ratios (OR) and 95% confidence intervals (CI) were generated for the outcomes. Quality assessment was performed using the Newcastle-Ottawa scale. RESULTS: Six studies with a total of 495 patients were included; 59% males, and 37 and 63% of the patients weighed < 2500 g and ≥ 2500 g, respectively. Male gender (OR, 0.96; 95% CI, 0.66-1.40; p = 0.82) and birth weight < 2500 g (OR, 0.74; 95% CI, 0.47-1.15; p = 0.18) did not increase the risk of AS. The majority of the included studies were retrospective cohort studies and the overall risk of bias was considered to be low to moderate. CONCLUSION: Neither gender nor birth weight appear to have an impact on the risk of AS development following EA repair.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.021 |
| Bibliometrics | 0.005 | 0.006 |
| 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".