In the treatment of myocardial infarction, a balance is needed between the prevention of ischemic and bleeding problems (Brar, 2016). The applications of hP2Y12 inhibitors may reach a threshold that additional platelet inhibition can elevate major bleeding and abolish the effects on the inhibition of ischemic events (Brar, 2016).

To solve the problems, it may be helpful to identify the population groups with high ischemic risks for long-term dual antiplatelet therapy. In addition, the length of the dual antiplatelet therapy is relevant. It is also necessary to identify the best possible treatment duration.

Health informatics strategies including machine learning have been suggested for more robust approaches for risk prediction (Brar, 2016). The analysis of the data from electronic health records (EHRs) and the applications of the prediction algorithm may help with the identifications of the threshold and the optimal schedules. The combination of clinical observations and informatics methods may help improve the practice of personalize medicine in the treatment of myocardial infarction by finding the optimal strategies using long-term dual antiplatelet therapy.

References:

Brar, S. S. (2016). The Yin and Yang of Long-Term Dual Antiplatelet Therapy. Journal of the American College of Cardiology, 67(10), 1155–1157. https://doi.org/10.1016/j.jacc.2015.12.061

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