Neoatherosclerosis and plaque rupture as triggers for very late stent thrombosis in a bare-metal stent

Very late stent thrombosis has been increasingly described in the drug eluting stent era. A 56-year-old male presented with anterior ST-elevation myocardial infarction, he received a bare-metal stent in the left anterior descending artery in 2010. We obtained an optical coherence tomography scan, showing ruptured neoatherosclerotic plaque with thrombus

Smoker's paradox in ST-elevation myocardial infarction: Role of inflammation and platelets.

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Accuracy of ChatGPT-Generated Information on Head and Neck and Oromaxillofacial Surgery: A Multicenter Collaborative Analysis

Objective: To investigate the accuracy of Chat-Based Generative Pre-trained Transformer (ChatGPT) in answering questions and solving clinical scenarios of head and neck surgery. Study Design: Observational and valuative study. Setting: Eighteen surgeons from 14 Italian head and neck surgery units. Methods: A total of 144 clinical questions encompassing different subspecialities of head and neck surgery and 15 comprehensive clinical scenarios were developed. Questions and scenarios were inputted into ChatGPT4, and the resulting answers were evaluated by the researchers using accuracy (range 1-6), completeness (range 1-3), and references' quality Likert scales. Results: The overall median score of open-ended questions was 6 (interquartile range[IQR]: 5-6) for accuracy and 3 (IQR: 2-3) for completeness. Overall, the reviewers rated the answer as entirely or nearly entirely correct in 87.2% of cases and as comprehensive and covering all aspects of the question in 73% of cases. The artificial intelligence (AI) model achieved a correct response in 84.7% of the closed-ended questions (11 wrong answers). As for the clinical scenarios, ChatGPT provided a fully or nearly fully correct diagnosis in 81.7% of cases. The proposed diagnostic or therapeutic procedure was judged to be complete in 56.7% of cases. The overall quality of the bibliographic references was poor, and sources were nonexistent in 46.4% of the cases. Conclusion: The results generally demonstrate a good level of accuracy in the AI's answers. The AI's ability to resolve complex clinical scenarios is promising, but it still falls short of being considered a reliable support for the decision-making process of specialists in head-neck surgery

Accuracy of ChatGPT-Generated Information on Head and Neck and Oromaxillofacial Surgery: A Multicenter Collaborative Analysis

Objective: To investigate the accuracy of Chat-Based Generative Pre-trained Transformer (ChatGPT) in answering questions and solving clinical scenarios of head and neck surgery. Study design: Observational and valuative study. Setting: Eighteen surgeons from 14 Italian head and neck surgery units. Methods: A total of 144 clinical questions encompassing different subspecialities of head and neck surgery and 15 comprehensive clinical scenarios were developed. Questions and scenarios were inputted into ChatGPT4, and the resulting answers were evaluated by the researchers using accuracy (range 1-6), completeness (range 1-3), and references' quality Likert scales. Results: The overall median score of open-ended questions was 6 (interquartile range[IQR]: 5-6) for accuracy and 3 (IQR: 2-3) for completeness. Overall, the reviewers rated the answer as entirely or nearly entirely correct in 87.2% of cases and as comprehensive and covering all aspects of the question in 73% of cases. The artificial intelligence (AI) model achieved a correct response in 84.7% of the closed-ended questions (11 wrong answers). As for the clinical scenarios, ChatGPT provided a fully or nearly fully correct diagnosis in 81.7% of cases. The proposed diagnostic or therapeutic procedure was judged to be complete in 56.7% of cases. The overall quality of the bibliographic references was poor, and sources were nonexistent in 46.4% of the cases. Conclusion: The results generally demonstrate a good level of accuracy in the AI's answers. The AI's ability to resolve complex clinical scenarios is promising, but it still falls short of being considered a reliable support for the decision-making process of specialists in head-neck surgery

Cardiac magnetic resonance predictors of left ventricular remodelling following acute ST elevation myocardial infarction: The VavirimS study

Left ventricular (LV) remodelling (REM) ensuing after ST-elevation myocardial infarction (STEMI), has typically been studied by echocardiography, which has limitations, or cardiac magnetic resonance (CMR) in early phase that may overestimate infarct size (IS) due to tissue edema and stunning. This prospective, multicenter study investigated LV-REM performing CMR in the subacute phase, and 6 months after STEMI