Increasing plasma glucose before the development of type 1 diabetes—the <scp>TRIGR</scp> study
Bibliographic record
Abstract
OBJECTIVE: The β-cell stress hypothesis suggests that increased insulin demand contributes to the development of type 1 diabetes. In the TRIGR trial we set out to assess the profile of plasma glucose and HbA1c before the diagnosis of clinical diabetes compared to nondiabetic children. RESEARCH DESIGN AND METHODS: A cohort of children (N = 2159) with an affected first-degree relative and increased HLA risk were recruited 2002-2007 and followed until 2017. To study the relationship between plasma glucose/HbA1c and the development of autoantibodies or clinical disease Kaplan-Meir curves were developed. Mixed models were constructed for plasma glucose and HbA1c separately. RESULTS: A family history of type 2 diabetes was related to an increase in plasma glucose (p < 0.001). An increase in glucose from the previous sample predicted clinical diabetes (p < 0.001) but not autoantibodies. An increase of HbA1c of 20% or 30% from the previous sample predicted the development of any autoantibody (p < 0.003 resp <0.001) and the development of diabetes (p < 0.002 resp <0.001. Participants without autoantibodies had lower HbA1c (mean 5.18%, STD 0.24; mean 33.08 mmol/mol, STD 2.85) than those who progressed to clinical disease (5.31%, 0.42; 34.46 mmol/mol, 4.68; p < 0.001) but higher than those who developed any autoantibody (5.10%, 0.30; 32.21 mmol/mol, 3.49; p < 0.001), or multiple autoantibodies (5.11%, 0.35; 32.26 mmol/mol, 3.92; p < 0.003). CONCLUSIONS: A pronounced increase in plasma glucose and HbA1c precedes development of clinical diabetes, while the association between plasma glucose or HbA1c and development of autoantibodies is complex. Increased insulin demand may contribute to development of type 1 diabetes.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".