Relationships Between the Cumulative Incidences of Long-term Complications in Type 1 Diabetes: The DCCT/EDIC Study
Bibliographic record
Abstract
OBJECTIVE: To describe the relationships between the cumulative incidences of long-term complications in individuals with type 1 diabetes (T1D) and assess whether observed associations are independent of age, duration of diabetes, and glycemic levels. METHODS: Proliferative diabetic retinopathy (PDR), clinically significant macular edema (CSME), reduced estimated glomerular filtration rate (eGFR), amputations, cardiovascular disease (CVD), and mortality were assessed in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study over ∼30 years. RESEARCH DESIGN AND RESULTS: The cumulative incidence of complications ranged from 3% (amputations) to 37% (CSME). There were large differences in the cumulative incidence of PDR between participants with versus without prior CSME (66% vs. 15%), reduced eGFR (59% vs. 29%), and amputation (68% vs. 32%); reduced eGFR with or without prior PDR (25% vs. 9%), amputation (48% vs. 13%), and CVD (30% vs. 11%); CVD with or without prior reduced eGFR (37% vs. 14%) and amputation (50% vs. 16%); and mortality with or without prior reduced eGFR (22% vs. 9%), amputation (35% vs. 8%), and CVD (25% vs. 8%). Adjusted for age, duration of T1D, and mean updated HbA1c, the complications and associations with higher risk included PDR with CSME (hazard ratio [HR] 1.88; 95% CI 1.42, 2.50), reduced eGFR (HR 1.41; 95% CI 1.01, 1.97), and CVD (HR 1.43; 95% CI 1.06, 1.92); CSME with higher risk of PDR (HR 3.94; 95% CI 3.18 4.89), reduced eGFR (HR 1.49; 95% CI 1.10, 2.01), and CVD (HR 1.35; 95% CI 1.03, 1.78); reduced eGFR with higher risk of CVD (HR 2.09; 95% CI 1.44, 3.03), and death (HR 3.40; 95% CI 2.35, 4.92); amputation(s) with death (HR 2.97; 95% CI 1.70, 2.90); and CVD with reduced eGFR (HR 1.59; 95% CI 1.08, 2.34) and death (HR 1.95; 95% CI 1.32, 2.90). CONCLUSIONS: Long-term micro- and macrovascular complications and mortality are highly correlated. Age, diabetes duration, and glycemic levels do not completely explain these associations.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".