Cardiovascular Benefit of Colchicine in Relation to Baseline Risk: A Secondary Analysis of the LoDoCo2 Trial
Bibliographic record
Abstract
Background The LoDoCo2 (Low‐Dose Colchicine 2) trial showed that colchicine reduced the risk for cardiovascular events in patients with chronic coronary syndrome. Current guidelines recommend colchicine use in selected high‐risk patients. The aim of this secondary analysis was to explore the relative and absolute benefits of colchicine according to baseline risk. Methods The LoDoCo2 trial randomized 5522 patients to colchicine 0.5 mg or placebo. The primary end point was a composite of cardiovascular death, spontaneous myocardial infarction, ischemic stroke, or ischemia‐driven coronary revascularization. First, a LoDoCo2 risk score was developed by Cox regression to identify high‐risk features for the primary end point. Second, the Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention was applied to explore robustness of findings. Results In the LoDoCo2 risk score, high‐risk features were age ≥75, diabetes, and current smoker. In high‐risk (≥1 high‐risk feature), compared with low‐risk (0 high‐risk features) patients, colchicine was associated with consistent relative (high risk: hazard ratio [HR], 0.72 [95% CI, 0.56–0.94] versus low risk: HR, 0.67 [95% CI, 0.52–0.88]; P for interaction=0.73) and absolute benefits (high risk: HR, −1.33 [95% CI, −2.38 to −0.27] versus low risk: HR, −0.93 [95% CI −1.57 to −0.30] events per 100 person‐years). Using the Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention, consistent relative and absolute benefits were found in high‐, intermediate‐, and low‐risk patients. Conclusions In patients with chronic coronary syndrome, the relative and absolute benefits of colchicine were consistent in those at high, intermediate, and low risk for cardiovascular events. These findings support the use of colchicine across the spectrum of baseline risk. Registration URL: https://www.anzctr.org.au ; Unique identifier: 12614000093684.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".