The Association Between Gestational Age and Type 1 Diabetes Mellitus in Children and Adolescents: A Systematic Review and Network Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: With genetics thought to explain a portion of the overall risk of type 1 diabetes mellitus (T1DM), environmental risk factors in early life have been proposed. Previous studies on the incidence of T1DM in children or adolescents by gestational age at birth have yielded inconsistent results. OBJECTIVES: To clarify the association between gestational age at birth and T1DM in childhood/adolescence and to offer evidence-based support for the prevention or screening of T1DM. DATA SOURCES: PubMed, Embase, Web of Science, and the Cochrane Library were searched from the inception of the databases to February 7, 2024. STUDY SELECTION AND DATA EXTRACTION: Data were extracted using a standardised form created a priori, and quality was assessed using the Newcastle-Ottawa Scale (NOS). SYNTHESIS: Due to the diversity of gestational age groups in the original studies, a Bayesian network meta-analysis was performed to discuss the association of different gestational ages with the risk of T1DM in childhood/adolescence. RESULTS: A total of 13 studies on children/adolescents with T1DM were included. Compared with the gestational age of 39-40 weeks, gestational ages of < 37 weeks (odds ratio [OR] 1.35, 95% credible interval [CrI] 1.19, 1.53), 33-36 weeks (OR 1.19, 95% CrI 1.11, 1.27), and 37-38 weeks (OR 1.26, 95% CrI 1.21, 1.30) were correlated with an increased risk of T1DM, whereas gestational ages of < 32 weeks (OR 0.61, 95% CrI 0.43, 0.88) and < 33 weeks (OR 0.72, 95% CrI 0.59, 0.87) were correlated with a lower risk. CONCLUSIONS: A higher risk of T1DM was observed in infants born early term or preterm compared to full-term infants. However, the results of this network meta-analysis indicate that extremely or very preterm infants were less likely to develop T1DM. Further studies are needed to validate this in the future.
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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 | 0.016 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.008 | 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 | 0.002 |
| 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".