Performance of HbA1c as an Early Diagnostic Indicator of Type 1 Diabetes in Children and Youth
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate HbA(1c) as an alternative criterion for impaired glucose tolerance (IGT) or type 1 diabetes (T1D) in high-risk subjects <21 years of age. RESEARCH DESIGN AND METHODS: Subjects <21 years of age who participated in the prospective DPT-1, TEDDY, TRIGR, and Type 1 Diabetes TrialNet Natural History (TrialNet) studies and had an HbA(1c) within 90 days of an OGTT with a 2-h plasma glucose (2-hPG) measure were included. An OGTT of 140-199 mg/dL defined IGT, and an OGTT with 2-hPG ≥200 mg/dL or fasting plasma glucose ≥126 mg/dL defined diabetes. HbA(1c) ≥5.7% defined IGT, and HbA(1c) ≥ 6.5% defined diabetes. Receiver-operating characteristic curve analysis was used to assess diagnostic accuracy of HbA(1c) compared with OGTT. RESULTS: There were 587 subjects from DPT-1, 884 from TrialNet, 91 from TEDDY, and 420 from TRIGR. As an indicator for IGT, HbA(1c) sensitivity was very low across the studies (8-42%), and specificity was variable (64-95%). With HbA(1c) ≥6.5% threshold used for T1D diagnosis, the sensitivity was very low and specificity was high (sensitivity and specificity: DPT-1 24 and 98%, TrialNet 28 and 99%, TEDDY 34 and 98%, and TRIGR 33 and 99%, respectively). The positive predictive value of HbA(1c) ≥6.5% for the development of T1D was variable (50-94%) across the four studies. CONCLUSIONS: HbA(1c) ≥6.5% is a specific but not sensitive early indicator for T1D in high-risk subjects <21 years of age diagnosed by OGTT or asymptomatic hyperglycemia. Redefining the HbA(1c) threshold is recommended if used as an alternative criterion in diagnosing T1D.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".