Glucose Excursions Between States of Glycemia With Progression to Type 1 Diabetes in the Diabetes Prevention Trial–Type 1 (DPT-1)
Bibliographic record
Abstract
OBJECTIVE: We characterized fluctuations between states of glycemia in progressors to type 1 diabetes and studied whether those fluctuations are related to the early C-peptide response to oral glucose. RESEARCH DESIGN AND METHODS: Oral glucose tolerance tests (OGTTs) from differing states of glycemia were compared within individuals for glucose and C-peptide. Dysglycemic OGTTs (DYSOGTTs) were compared with normal OGTTs (NLOGTT), while transient diabetic OGTTs (TDOGTTs) were compared with subsequent nondiabetic OGTTs and with OGTTs performed at diagnosis. RESULTS: Of 135 progressors with four or more OGTTs, 30 (22%) went from NLOGTTs to DYSOGTTs at least twice. Area under the curve (AUC) glucose values from the second NLOGTT were higher (P < 0.001) than values from the first NLOGTT. Among 98 progressors whose DYSOGTTs and NLOGTTs were synchronized for the time before diagnosis, despite higher glucose levels (P < 0.01 at all time points) in the DYSOGTTs, 30- to 0-min C-peptide difference values changed little. Likewise, 30- to 0-min C-peptide difference values did not differ between TDOGTTs and subsequent (within 3 months) nondiabetic OGTTs in 55 progressors. In contrast, as glucose levels increased overall from the first to last OGTTs before diagnosis (P < 0.001 at every time point, n = 207), 30- to 0-min C-peptide difference values decreased (P < 0.001). CONCLUSIONS: Glucose levels fluctuate widely as they gradually increase overall with progression to type 1 diabetes. As glucose levels increase, the early C-peptide response declines. In contrast, glucose fluctuations are not related to the early C-peptide response. This suggests that changes in insulin sensitivity underlie the glucose fluctuations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".