Colchicine and diabetes in patients with chronic coronary artery disease: insights from the LoDoCo2 randomized controlled trial
Bibliographic record
Abstract
Introduction Despite optimal treatment, patients with chronic coronary artery disease (CAD) and diabetes mellitus (DM) are at high risk of cardiovascular events, emphasizing the need for new treatment options. The Low-Dose Colchicine 2 (LoDoCo2) trial demonstrated that colchicine reduces cardiovascular risk in patients with chronic CAD. This analysis determines the efficacy of colchicine in patients with chronic CAD and DM as well as the effect of colchicine on the development of new-onset type 2 diabetes mellitus (T2DM). Methods The LoDoCo2 trial randomized 5,522 patients to placebo or colchicine 0.5 mg once daily, with a median follow-up of 28.6 months. The primary composite endpoint was cardiovascular death, spontaneous myocardial infarction, ischemic stroke, or ischemia-driven revascularization. The effect of its treatment in patients with and without DM was evaluated by including an interaction term in the model. Results A total of 1,007 participants (18.2%) had T2DM at baseline. The adjusted hazard ratio (HR) [(95% confidence interval (CI)] for the primary endpoint in the T2DM group was 1.52 (1.15–2.01, p < 0.01) compared with the group without T2DM. The HR for the treatment effect on the primary endpoint was 0.87 (0.61–1.25) in participants with T2DM and 0.64 (0.51–0.80) in participants without diabetes (pinteraction = 0.14). The incidence of new-onset T2DM was 1.5% (34 out of 2,270) in the colchicine group and 2.2% (49 out of 2,245) in the placebo group (p = 0.10). Discussion In conclusion, based on the current evidence, the beneficial effects of colchicine on cardiovascular endpoints are consistent regardless of DM status. The potential benefits of colchicine in preventing new-onset DM need further investigation. These findings are only hypothesis-generating and require larger prospective trials to confirm the results.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".