Association between autism spectrum disorder and diabetes: systematic review and meta-analysis
Bibliographic record
Abstract
There is mixed evidence on the link between autism spectrum disorder (ASD) and diabetes. We conducted the first systematic review/meta-analysis on their association. Based on a pre-registered protocol (PROSPERO: CRD42021261114), we searched Pubmed, Ovid, and Web of Science databases up to 6 December 2021, with no language/type of document restrictions. We assessed study quality using the Newcastle-Ottawa Scale (NOS). We included 24 studies (total: 3427,773 individuals; 237,529 with ASD and 92,832 with diabetes) in the systematic review and 20 in the meta-analysis (mean stars number on the NOS: 5.89/10). There was a significant association, albeit characterized by significant heterogeneity, when pooling unadjusted OR (1.535, 95% CI = 1.109-2.126), which remained significant when restricting the analysis to children and type 2 diabetes, but became non-significant when considering adjusted ORs (OR: 1.528, 95% CI = 0.954-2.448). No significant prospective association was found (n = 2) on diabetes predicting ASD (HR: 1.232, 0.826-11.837). Therefore, the association between ASD and diabetes is likely confounded by demographic and clinical factors that should be systematically investigated in future studies.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".