BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using...BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using ChatGPT to streamline and enhance the meta-analysis process.AIM To investigate the potential of ChatGPT to conduct meta-analyses in interventional cardiology by comparing the results of ChatGPT-generated analyses with those of randomly selected,human-conducted meta-analyses on the same topic.METHODS We systematically searched PubMed for meta-analyses on interventional cardiology published in 2024.Five metaanalyses were randomly chosen.ChatGPT 4.0 was used to perform meta-analyses on the extracted data.We compared the results from ChatGPT with the original meta-analyses,focusing on key effect sizes,such as risk ratios(RR),hazard ratios,and odds ratios,along with their confidence intervals(CI)and P values.RESULTS The ChatGPT results showed high concordance with those of the original meta-analyses.For most outcomes,the effect measures and P values generated by ChatGPT closely matched those of the original studies,except for the RR of stent thrombosis in the Sreenivasan et al study,where ChatGPT reported a non-significant effect size,while the original study found it to be statistically significant.While minor discrepancies were observed in specific CI and P values,these differences did not alter the overall conclusions drawn from the analyses.CONCLUSION Our findings suggest the potential of ChatGPT in conducting meta-analyses in interventional cardiology.However,further research is needed to address the limitations of transparency and potential data quality issues,ensuring that AI-generated analyses are robust and trustworthy for clinical decision-making.展开更多
文摘BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using ChatGPT to streamline and enhance the meta-analysis process.AIM To investigate the potential of ChatGPT to conduct meta-analyses in interventional cardiology by comparing the results of ChatGPT-generated analyses with those of randomly selected,human-conducted meta-analyses on the same topic.METHODS We systematically searched PubMed for meta-analyses on interventional cardiology published in 2024.Five metaanalyses were randomly chosen.ChatGPT 4.0 was used to perform meta-analyses on the extracted data.We compared the results from ChatGPT with the original meta-analyses,focusing on key effect sizes,such as risk ratios(RR),hazard ratios,and odds ratios,along with their confidence intervals(CI)and P values.RESULTS The ChatGPT results showed high concordance with those of the original meta-analyses.For most outcomes,the effect measures and P values generated by ChatGPT closely matched those of the original studies,except for the RR of stent thrombosis in the Sreenivasan et al study,where ChatGPT reported a non-significant effect size,while the original study found it to be statistically significant.While minor discrepancies were observed in specific CI and P values,these differences did not alter the overall conclusions drawn from the analyses.CONCLUSION Our findings suggest the potential of ChatGPT in conducting meta-analyses in interventional cardiology.However,further research is needed to address the limitations of transparency and potential data quality issues,ensuring that AI-generated analyses are robust and trustworthy for clinical decision-making.
