Colchicine in cardiac disease: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Colchicine has unique anti-inflammatory properties that may be beneficial in various cardiovascular conditions. This systematic review and meta-analysis of randomized controlled trials (RCTs) examines this issue. METHODS: We searched MEDLINE, EMBASE, and the Cochrane Database from inception to June 2014 for RCTs using colchicine in adult patients with cardiac diseases. Results were pooled using random effects. RESULTS: 15 RCTs (n = 3431 patients, median treatment 3 and follow-up 15 months) were included. All but 2 used colchicine 1 mg/day. In 5 trials, n = 1301) at risk for cardiovascular disease (coronary artery disease, acute coronary syndrome or stroke, post-angioplasty [2 RCTs], or congestive heart failure), colchicine reduced composite cardiovascular outcomes by ~60 % (risk ratio [RR] 0.44, 95 % confidence interval [CI] 0.28-0.69, p = 0.0004; I(2) = 0 %) and showed a trend towards lower all-cause mortality (RR 0.50, 95 % CI 0.23-1.08, p = 0.08; I(2) = 0 %). In pericarditis or post-cardiotomy, colchicine decreased recurrent pericarditis or post-pericardiotomy syndrome (RR 0.50, 95 % CI 0.41-0.60, p < 0.0001; I(2) = 0 %; 8 RCTs, n = 1635), and post-pericardiotomy or ablation induced atrial fibrillation (RR 0.65, 95 % CI 0.51-0.82, p = 0.0003; I(2) = 31 %; 4 RCTs, n = 1118). The most common adverse event was diarrhea. Treatment discontinuation overall and due to adverse events (RR 4.34, 95 % CI 1.70-11.07, p = 0.002; I(2) = 29 %; 7 RCTs, 83/790 [10.5 %] vs. 11/697 [1.6 %]) was higher in colchicine-assigned patients. CONCLUSIONS: Current RCT data suggests that colchicine may reduce the composite rate of cardiovascular adverse outcomes in a range of patients with established cardiovascular disease. Furthermore, colchicine reduces rates of recurrent pericarditis, post-pericardiotomy syndrome, and peri-procedural atrial fibrillation following cardiac surgery. Further RCTs evaluating the potential of colchicine for secondary prevention of cardiovascular events would be of interest.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.035 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".