Accuracy of Online Artificial Intelligence Models in Primary Care Settings.

INTRODUCTION: The importance of preventive medicine and primary care in the sphere of public health is expanding, yet a gap exists in the utilization of recommended medical services. As patients increasingly turn to online resources for supplementary advice, the role of artificial intelligence (AI) in providing accurate and reliable information has emerged. The present study aimed to assess ChatGPT-4's and Google Bard's capacity to deliver accurate recommendations in preventive medicine and primary care. METHODS: Fifty-six questions were formulated and presented to ChatGPT-4 in June 2023 and Google Bard in October 2023, and the responses were independently reviewed by two physicians, with each answer being classified as "accurate," "inaccurate," or "accurate with missing information." Disagreements were resolved by a third physician. RESULTS: Initial inter-reviewer agreement on grading was substantial (Cohen's Kappa was 0.76, 95%CI [0.61-0.90] for ChatGPT-4 and 0.89, 95%CI [0.79-0.99] for Bard). After reaching a consensus, 28.6% of ChatGPT-4-generated answers were deemed accurate, 28.6% inaccurate, and 42.8% accurate with missing information. In comparison, 53.6% of Bard-generated answers were deemed accurate, 17.8% inaccurate, and 28.6% accurate with missing information. Responses to CDC and immunization-related questions showed notable inaccuracies (80%) in both models. CONCLUSIONS: ChatGPT-4 and Bard demonstrated potential in offering accurate information in preventive care. It also brought to light the critical need for regular updates, particularly in the rapidly evolving areas of medicine. A significant proportion of the AI models' responses were deemed "accurate with missing information," emphasizing the importance of viewing AI tools as complementary resources when seeking medical information.

Systematic Review and Meta-Analysis Comparing Complete Versus Incomplete or Culprit-only Revascularization by Percutaneous Coronary Intervention in Elderly Patients with Acute Coronary Syndrome.

BACKGROUND: Complete revascularization (CR) is favored over culprit-only or incomplete revascularization (IR) for patients with acute coronary syndrome (ACS) and multi-vessel disease (MVD) due to better long-term outcomes. However, the optimal revascularization strategy is currently uncertain in elderly patients, where frailty, polypharmacy, multi-morbidity, inherent bleeding risk and presumed cognitive decline can often burden the decision-making process. METHODS: We searched Medline, PubMed, and Google Scholar from inception to April 2024. The search of databases identified relevant studies that reported the comparative effects of CR and IR in the elderly population undergoing percutaneous coronary intervention (PCI). Data was pooled for individual studies using random-effects models on Comprehensive Meta-Analysis software, with statistical significance set at p<0.05. RESULTS: The meta-analysis included 14 studies and 62577 patients. CR demonstrated a significant reduction in all-cause mortality [RR: 0.680; 95% CI: 0.57-0.82; p=<0.001], cardiovascular-related mortality [RR: 0.620; 95% CI: 0.478-0.805; p=<0.001], and myocardial infarction [RR: 0.675; 95% CI: 0.553-0.823; p=<0.001] rates. There was no difference between the risk of stroke [RR: 1.044; 95% CI: 0.733-1.486; p=0.81], major bleeding [RR: 1.001; 95% CI: 0.787-1.274; p=0.991], stent thrombosis [RR: 1.015; 95% CI: 0.538-1.916; p=0.936], and contrast-induced acute kidney injury [RR: 1.187; 95% CI: 0.963-1.464; p=0.109]. CONCLUSION: The meta-analysis suggests that CR may be a favorable revascularization strategy for elderly patients undergoing PCI, displaying a significant decrease in mortality and repeat myocardial infarction risk.