AI-Enhanced Predictive Modeling for Identifying Depression and Delirium in Cardiovascular Patients Scheduled for Cardiac Surgery

Comprehensive Summary

It has been seen in past studies that about a third of patients with cardiovascular disease also have depression, indicating a potential link between the two. The aim of this study was to create an AI model that can identify depression and delirium in patients experiencing cardiac diseases. The model was trained using a total of 244 patients, all of whom were set to undergo coronary artery bypass surgery. Each patient took a psychiatric evaluation before to assess if they had depression, they were assessed once each day for 5 days post operation. Additionally blood samples were taken twice a day, measuring the levels of sRAGE, MCP-1, hsCRP. An analysis was done to see the correlation between the levels measured and the level (or if) patients had depression. This information was then used to generate the AI model, which was used to test if the patients had a risk of depression after a cardiac procedure. The results of the analysis indicated that higher levels of sRAGE were associated with increased likelihood of depression.

Outcomes and Implications

Depression can increase the risk for cardiac issues and mortality, the use of this AI model can allow for earlier detection and therefore earlier intervention for these problems. The AI model proved to be successful, using sRAGE levels to detect the presence of depression in a patient. More testing should be done before being used clinically, in order to test its accuracy in a larger population.