DYSGLYCEMIA TO TYPE 1 DIABETES: EVALUATING THE ASSOCIATION OF RISK FACTORS WITH DISEASE PROGRESSION
Bibliographic record
Abstract
BACKGROUND: Type 1 diabetes (T1D) has long been recognized as an autoimmune disorder, likely stimulated by environmental factors and immune dysregulation in individuals with an increased genetic susceptibility. Accelerated beta cell function loss precedes disease detection, indicating a need to identify high-risk individuals prior to diagnosis. While parameters such as number of autoantibodies against beta cells, age, body-mass index, and measures of insulin and glucose response have been shown to be predictive of T1D, prediction of the timing of diagnosis remains challenging. OBJECTIVES: To evaluate the association between risk factors for T1D and the rate of progression from an abnormal oral glucose tolerance test (OGTT) to the development of T1D. DESIGN/METHODS: Data from a prospective cohort study (n = 1127), Type 1 Diabetes TrialNet, was employed to perform a multivariate Cox regression using a forward stepwise approach to identify variables that increased risk of T1D. Cut points that defined high and low risk sub-populations based on identified variables of interest were selected through recursive partitioning analysis. C-statistics and life tables were then used to explore model discrimination and time from first abnormal OGTT to T1D. RESULTS: While there was some variability between study sub-groups (all ages, < 18 years, and > 18 years), ICA or ICA 512 positivity, DPTRS (Diabetes Prevention Trial-Type 1 Risk Score), number of antibodies, Index60 (metabolic index), and HbA1c were identified as being significant T1D risk factors. In the all ages group, DPTRS < 7 and <= 2 antibodies identified a lower risk population with slower progression to T1D compared to those with DPTRS > 7 and >= 3 antibodies (model C-statistic = 0.63). In the < 18 years group, DPTRS > 8 and HbA1c > 5.4 defined a faster progressing population (model C-statistic = 0.69). In the > 18 years group, ICA positivity and Index60 >= 1 identified a population at higher risk of progression to T1D (model C-statistic = 0.66). CONCLUSION: Several T1D risk factors predict the rate of progression from dysglycemia to T1D onset. These may be used to identify individuals at a higher risk for disease development and may help inform efforts aimed at T1D prevention.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".