Colchicine for Major Adverse Cardiovascular Events: An Updated ChatGPT-Assisted Systematic Review and Meta-Analysis

Abstract

Colchicine has been studied as an anti-inflammatory treatment for cardiovascular prevention, but findings from randomized trials have been inconsistent. This meta-analysis evaluated the efficacy and safety of colchicine in reducing major adverse cardiovascular events (MACE) and its individual components, using ChatGPT as an assistant throughout the process. Randomized trials of colchicine for cardiovascular prevention were systematically identified, and data extraction, risk of bias assessment, and meta-analyses were performed with ChatGPT under human supervision. The primary outcome was MACE, while secondary outcomes included myocardial infarction (MI), stroke, revascularization, cardiovascular mortality, and all-cause mortality. Eleven trials involving 30,888 patients were included. Colchicine significantly reduced MACE (risk ratio 0.75, 95% CI 0.63-0.88), though no significant effects were observed for MI, stroke, cardiovascular mortality, or all-cause mortality. In addition to its clinical findings, this study illustrates the potential of ChatGPT to assist in systematic reviews and meta-analyses by automating screening, data extraction, bias assessment, and statistical code generation. This integration reduced researcher time by over 70% while maintaining accuracy through human validation. Overall, colchicine appears to lower the risk of MACE but the results of the CLEAR trial have lowered certainty, while the findings highlight the feasibility and efficiency gains of using large language models in evidence synthesis workflows.

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