Applicability of Online Chat-Based Artificial Intelligence Models to Colorectal Cancer Screening.

BACKGROUND: Over the past year, studies have shown potential in the applicability of ChatGPT in various medical specialties including cardiology and oncology. However, the application of ChatGPT and other online chat-based AI models to patient education and patient-physician communication on colorectal cancer screening has not been critically evaluated which is what we aimed to do in this study. METHODS: We posed 15 questions on important colorectal cancer screening concepts and 5 common questions asked by patients to the 3 most commonly used freely available artificial intelligence (AI) models. The responses provided by the AI models were graded for appropriateness and reliability using American College of Gastroenterology guidelines. The responses to each question provided by an AI model were graded as reliably appropriate (RA), reliably inappropriate (RI) and unreliable. Grader assessments were validated by the joint probability of agreement for two raters. RESULTS: ChatGPT and YouChat™ provided RA responses to the questions posed more often than BingChat. There were two questions that > 1 AI model provided unreliable responses to. ChatGPT did not provide references. BingChat misinterpreted some of the information it referenced. The age of CRC screening provided by YouChat™ was not consistently up-to-date. Inter-rater reliability for 2 raters was 89.2%. CONCLUSION: Most responses provided by AI models on CRC screening were appropriate. Some limitations exist in their ability to correctly interpret medical literature and provide updated information in answering queries. Patients should consult their physicians for context on the recommendations made by these AI models.

Cardiovascular Disease Risk Factors and Outcomes of Acute Myocardial Infarction in Young Adults: Evidence From 2 Nationwide Cohorts in the United States a Decade Apart.

The purpose of this study was to evaluate 2 national in-patient cohorts of young adults (18-44 years) hospitalized with acute myocardial infarction (AMI) a decade apart to highlight its prevalence, associated comorbidities, and in-hospital outcomes. We identified hospitalizations for AMI in young adults in 2007 and 2017 using the weighted data from the National Inpatient Sample. We compared admission rates, sociodemographic characteristics, in-hospital morbidity, complications, mortality, rate of coronary interventions, and healthcare utilization between the 2 cohorts. We found that the admission rate of AMI increased among young adults in 2017 vs 2007. The overall admission rate was higher in males, although with a decline (77.1% vs 66.1%), whereas it rose from 28.9% to 33.9% in females. Hypertension (47.8% vs 60.7%), smoking (49.7% vs 55.8%), obesity (14.8% vs 26.8%), and diabetes mellitus (22.0% vs 25.6%) increased in the 2017 cohort. Post-AMI complications: cardiogenic shock (aOR = 1.16 [1.06-1.27]) and fatal arrhythmias heightened with comparable all-cause mortality (aOR = 1.01 [0.93-1.10], P = 0.749). Reperfusion interventions, percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) decreased in the 2017 cohort (PCI; aOR = 0.95 [0.91-0.98], CABG; aOR = 0.66 [0.61-0.71], P < 0.001). Our study highlights the rise in AMI hospitalizations, plateauing of mortality, sex-based and racial disparities, the surge in post-MI complications, and a reassuring decline in the requirement of reperfusion interventions in young AMI patients over the decade.