Thyroid Function and the Risk of Prediabetes and Type 2 Diabetes
Bibliographic record
Abstract
CONTEXT: Thyroid hormones are important regulators of glucose metabolism, and studies investigating the association between thyroid function and type 2 diabetes incidence have shown conflicting results. OBJECTIVE: We aimed to combine the evidence from prospective studies addressing the association between thyroid function and type 2 diabetes risk. METHODS: We systematically searched in Embase, Medline (Ovid), Web of Science, Cochrane, and Google Scholar for prospective studies assessing the association of thyroid function and incident type 2 diabetes. Data extraction was performed using a standardized protocol by 2 independent reviewers. We assessed study quality using the Newcastle-Ottawa Scale and pooled hazard ratios (HRs) and 95% CI using random-effects models. RESULTS: From the 4574 publications identified, 7 met our inclusion criteria and were included in the qualitative synthesis. Six publications were included in the meta-analysis. Studies assessed hypothyroidism (6 studies), hyperthyroidism (5 studies), thyrotropin (TSH) in the reference range (4 studies), and free thyroxine (FT4) in the reference range (3 studies) in relation to incident type 2 diabetes. The pooled HR for the risk of type 2 diabetes was 1.26 (95% CI, 1.05-1.52) for hypothyroidism, 1.16 (95% CI, 0.90-1.49) for hyperthyroidism, 1.06 (95% CI, 0.96-1.17) for TSH in the reference range, and 0.95 (95% CI, 0.91-0.98) for FT4 in the reference range. CONCLUSION: Current evidence suggests an increased type 2 diabetes risk in people with hypothyroidism and lower FT4 levels in the reference range. Further population-based studies are needed to address this association given the limited evidence.
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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 | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".