Diabetic Retinopathy, Its Progression, and Incident Cardiovascular Events in the ACCORD Trial
Bibliographic record
Abstract
OBJECTIVE: Both the presence of diabetic retinopathy and its severity are significantly associated with future cardiovascular (CV) events. Whether its progression is also linked to incident CV outcomes hasn't been assessed. RESEARCH DESIGN AND METHODS: The relationship between retinopathy, its 4-year progression, and CV outcomes (CV death or nonfatal myocardial infarction or stroke) was analyzed in participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial who also participated in the ACCORD Eye Study. Retinopathy was classified as either none, mild, moderate, or severe, and worsening was classified as a <2-step, 2-3-step, or >3-step change (that included incident laser therapy or vitrectomy). RESULTS: Participants (n = 3,433) of mean age 61 years had baseline retinal photographs (seven stereoscopic fields). Compared with no retinopathy, the adjusted HRs (95% CI) for the CV outcome rose from 1.49 (1.12-1.97) for mild retinopathy to 2.35 (1.47-3.76) for severe retinopathy. A subset of 2,856 was evaluated for progression of diabetic retinopathy at 4 years. The hazard of the primary outcome increased by 38% (1.38 [1.10-1.74]) for every category of change in retinopathy severity. Additional adjustment for the baseline and follow-up levels of A1C, systolic blood pressure, and lipids either individually or together rendered the relationships between worsening and CV outcomes nonsignificant. CONCLUSIONS: Both the severity of retinopathy and its progression are determinants of incident CV outcomes. The retina may provide an anatomical index of the effect of metabolic and hemodynamic factors on future CV outcomes.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".