Effect of Glycemic Exposure on the Risk of Microvascular Complications in the Diabetes Control and Complications Trial—Revisited
Bibliographic record
Abstract
OBJECTIVE: The Diabetes Control and Complications Trial (Diabetes 44:968-983, 1995) presented statistical models suggesting that subjects with similar A1C levels had a higher risk of retinopathy progression in the conventional treatment group than in the intensive treatment group. That analysis has been cited to support the hypothesis that specific patterns of glucose variation, in particular postprandial hyperglycemia, contribute uniquely to an increased risk of microvascular complications above and beyond that explained by the A1C level. RESEARCH DESIGN AND METHODS: We performed statistical evaluations of these models and additional analyses to assess whether the original analyses were flawed. RESULTS: Statistically, we show that the original results are an artifact of the assumptions of the statistical model used. Additional analyses show that virtually all (96%) of the beneficial effect of intensive versus conventional therapy on progression of retinopathy is explained by the reductions in the mean A1C levels, similarly for other outcomes. Furthermore, subjects within the intensive and conventional treatment groups with similar A1C levels over time have similar risks of retinopathy progression, especially after adjusting for factors in which they differ. CONCLUSIONS: A1C explains virtually all of the difference in risk of complications between the intensive and conventional groups, and a given A1C level has similar effects within the two treatment groups. While other components of hyperglycemia, such as glucose variation, may contribute to the risk of complications, such factors can only explain a small part of the differences in risk between intensive and conventional therapy over time.
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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 | 0.034 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| 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".