A comparison of the baseline metabolic profiles between Diabetes Prevention Trial-Type 1 and TrialNet Natural History Study participants
Bibliographic record
Abstract
Sosenko JM, Mahon J, Rafkin L, Lachin JM, Krause-Steinrauf H, Krischer JP, Cuthbertson D, Palmer JP, Thompson C, Greenbaum CJ, Skyler JS, the Diabetes Prevention Trial-Type 1 and TrialNet Study Groups. A comparison of the baseline metabolic profiles between Diabetes Prevention Trial-Type 1 and TrialNet Natural History Study participants. Objective: We assessed whether differing autoantibody screening criteria for type 1 diabetes (T1D) prevention trials result in different baseline metabolic profiles of those who screen positive. Methods: Diabetes Prevention Trial-Type 1 (DPT-1) participants were screened for islet cell autoantibodies, whereas TrialNet Natural History Study (TNNHS) participants were screened for biochemical autoantibodies. In both studies, those determined to be autoantibody positive underwent baseline oral glucose tolerance tests (OGTTs) in which glucose and C-peptide were measured. Results: The percentage of those with an OGTT in the diabetic range was higher among the DPT-1 participants (10.0% of 956 vs. 6.4% of 645, p < 0.01). In a logistic regression analysis with adjustments for age and gender, the difference persisted (p < 0.01). Among those in the non-diabetic range (n = 860 for DPT-1 and n = 604 for the TNNHS), glucose levels were similar at all time points, except for higher fasting glucose levels in the TNNHS participants (p < 0.001). There was a higher percentage of impaired fasting glucose (IFG) in the TNNHS participants (10.9 vs. 6.7%, p < 0.01); however, with adjustments for age and gender, there was no longer a significant difference. There was no significant difference in the percentages with impaired glucose tolerance. C-peptide levels were much lower in the DPT-1 cohort at all OGTT time points (p < 0.001 for all). Discussion: Differing criteria for autoantibody screening can result in marked differences in the baseline metabolic profiles of prospective participants of T1D prevention trials.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".