Seasonal Variation of Congenital Diaphragmatic Hernia: A Review of the Literature and Database Report from the United States and Canada
Bibliographic record
Abstract
Abstract Introduction The etiology of congenital diaphragmatic hernia (CDH) remains unknown and only 10 to 30% of patients have a genetic cause. Seasonal variation is known to contribute to the development of some congenital anomalies. Our aim was to investigate whether CDH births have seasonal variation. Materials and Methods A literature review was conducted for CDH and seasonality. Moreover, data from the CDH International Patient Registry Database were collected for infants with due dates between 2008 and 2014. Due dates were used to determine seasonal distribution of births. Birth rates per month in the United States and Canada were extracted from publicly available databases. Data were analyzed using analysis of variance and contingency tables. Results First, the literature review revealed 11 articles, of which 3 were eligible for inclusion. These studies reported conflicting results on seasonality of CDH. Second, we extracted due dates from the CDH International Patient Registry Database (1,259 patients) and found that there were fewer due dates in winter months (12.1 ± 4 patients/month) than in summer (16.7 ± 6 patients/month; p = 0.011) and fall months (16.3 ± 5 patients/month; p = 0.022). Although this trend was similar to that of all births in the United States and Canada, a lower incidence was observed in winter for CDH infants (20.2%) than for the general population (24.1%, p = 0.0012). CDH survival rate did not vary by season. Conclusion This study provides evidence for a seasonal variation of CDH births. No causative link was established between CDH development and seasonality. Population-based studies with a focus on exposome data are needed to explain seasonal variation in CDH.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.039 | 0.066 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".