Construction of a Joint Prediction Model for the Occurrence of Ischemic Stroke and Acute Myocardial Infarction Based on Bioinformatic Analysis.

Ischemic stroke (IS) has imposed significant threat to both middle-aged and elderly people worldwide. Acute myocardial infarction (AMI) is a rare but serious complication following IS, which can further increase patient disability and mortality rates. With the development of intravenous thrombolysis and endovascular treatment, the prognosis of IS has been greatly improved. However, the pathogenesis of IS complicated with AMI is still unclear. To fill this gap, this work uses bioinformatic analysis, where IS and AMI datasets were combined for differential gene analysis, and then, a ROC prediction model for target gene analysis was constructed. It is found that OSM gene has the highest prediction accuracy (AUC = 0.793), followed by IL6ST, IL6, JAK1, IL6R, and JAK2 genes. Joint prediction model showed higher accuracy in predicting the outcome of control and case (AUC = 0.918). The etiology of ischemic stroke and acute myocardial infarction is complicated. Their cooccurring pathological mechanisms and the conversion between the two diseases could not be explained by a single gene. Therefore, the joint prediction model in this work can provide a better prediction accuracy for research purpose.