Area‐under‐the‐HbA<sub>1c</sub>‐curve above the normal range and the prediction of microvascular outcomes: an analysis of data from the Diabetes Control and Complications Trial
Bibliographic record
Abstract
AIMS: In the Diabetes Control and Complications Trial, mean updated HbA(1c) accounted for most of the differential risk of microvascular complications between intensive and conventional insulin therapy. We hypothesized, however, that a more precise measure of chronic hyperglycaemic exposure may be the incremental area-under-the-HbA(1c)-curve above the Diabetes Control and Complications Trial-standardized normal range for HbA(1c) (iAUC(HbA1c>norm)). METHODS: Using the Principal Diabetes Control and Complications Trial data set, we compared the following three measures of chronic glycaemic exposure for their capacity to predict retinopathy, nephropathy and neuropathy during the Diabetes Control and Complications Trial: mean updated HbA(1c), iAUC(HbA1c>norm), and total area-under-the-HbA(1c)-curve (tAUC(HbA1c)). For each outcome, models using each of these three glycaemic measures were compared in the following three ways: hazard or odds ratio, χ(2) statistic, and Akaike information criterion. RESULTS: The three glycaemic measures did not differ in their prediction of neuropathy. iAUC(HbA1c>norm) was modestly superior to mean updated HbA(1c) for predicting nephropathy (χ(2) P = 0.017, Akaike P = 0.032). In contrast, for predicting retinopathy, both iAUC(HbA1c>norm) (χ(2) P = 0.0005, Akaike P = 0.0005) and tAUC(HbA1c) (χ(2) P = 0.004, Akaike P = 0.004) were significantly better than mean updated HbA(1c). Varying its HbA(1c) threshold incrementally between 37 and 53 mmol/mol (5.5-7.0%), inclusive, did not improve the prediction of retinopathy by iAUC(HbA1c>threshold) beyond that of tAUC(HbA1c,) consistent with the concept of a continuous relationship between glycaemia and retinopathy, with no glycaemic threshold. CONCLUSIONS: Both iAUC(HbA1c>norm) and tAUC(HbA1c) were superior to mean updated HbA(1c) for predicting retinopathy. Optimal assessment of chronic glycaemic exposure as a determinant of retinopathic risk may require consideration of both the degree of hyperglycaemia and its duration.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".