Impact of COVID-19 on arthritis with generative AI

Objective: The study aims to examine the effects of the COVID-19 pandemic on the prevalence of arthritis in the US using a specific generative AI tool. Methods: The AI tool with Bing.com/copilot, designed to generate Python code, uses data from the Centers for Disease Control and Prevention (CDC) to visualize trends and uncover insights in four key areas: (1) The prevalence of arthritis in adults aged 18 years and older who have diabetes, (2) The prevalence of fair or poor health in adults aged 18 years and older who have arthritis, (3) The prevalence of activity limitations due to arthritis in adults aged 18 years and older with doctor -diagnosed arthritis, (4) The prevalence of arthritis in adults aged 18 years and older who are obese. This research did not require approval from an institutional review board or an ethics committee. Results: The findings reveal a significant decline in the prevalence of arthritis among adults with conditions such as diabetes and obesity during the COVID-19 pandemic. There was also an observed improvement in activity limitations among patients with doctor -diagnosed arthritis. Conclusion: The study highlights the potential impact of the pandemic on chronic disease management, particularly arthritis. It underscores the importance of continued monitoring and care for patients with arthritis, especially during a global health crisis like the COVID-19 pandemic. The use of AI tools in generating insights from health data proves to be valuable in this context.