Circulating Inflammatory Markers and the Risk of Vascular Complications and Mortality in People With Type 2 Diabetes and Cardiovascular Disease or Risk Factors: The ADVANCE Study
Bibliographic record
Abstract
C-reactive protein (CRP), fibrinogen, and interleukin-6 (IL-6) are associated with cardiovascular disease (CVD) and death in general populations. However, studies of these factors in type 2 diabetes are limited. We studied their associations with the risk of major macrovascular events, microvascular complications, and mortality in patients with type 2 diabetes who participated in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) Study. Plasma CRP, fibrinogen, and IL-6 levels were determined in a case-cohort study (n = 3,865) nested within the 11,140 men and women with type 2 diabetes and baseline CVD or risk factors in the ADVANCE Study. All three biomarkers of inflammation were associated with an increased risk of macrovascular events and death in analyses adjusted for age, sex, and treatment groups. After further adjustment, only IL-6 was an independent predictor of macrovascular events (hazard ratio per SD increase 1.37 [95% CI 1.24-1.51]) and death (1.35 [1.23-1.49]). IL-6 significantly improved the prediction of macrovascular events and death. After adjustment, none of the markers predicted microvascular complications. We conclude that IL-6 levels, but not CRP or fibrinogen levels, add significantly to the prediction of macrovascular events and mortality in individuals with type 2 diabetes who have baseline CVD or risk factors.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| 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".