Artificial intelligence systems for predicting chronic ischemic heart disease outcomes in cardiac surgery patients based on presence of anemia: a literature review

Abstract

Materials and methods. The PubMed and RSCI databases were analyzed covering the period of 2000-2023. 906 articles were found using the keywords “artificial intelligence”, “anemia”, coronary artery disease”, “hemoglobin”, “cardiac surgery”, of which 38 met the criteria for inclusion in the analysis. Results. In a number of countries around the world, artificial intelligence (AI) systems have now been created to predict the course of IHD, however, at the moment, data have been published on the single system with AI elements, presented by the developers of the University of Turin (Italy). It has the functionality of predicting the course of IHD and complications of invasive procedures for IHD against the background of anemic syndrome, based on the use of the HAS-BLEED scale. The increase in the number of CABG operations determines the importance of further research into their long-term results and the development of programs for their management, which will take into account such factors that are important for choosing a strategy for their management and the possibility of influencing the risks of an unfavorable prognosis. This review presents published data on the developed and used digital products based on artificial intelligence intended for the management of patients with coronary artery disease, including taking into account basic hematological parameters. Conclusion. Analysis of existing developed AI systems showed a focus on solving prognostic issues. At the same time, in our opinion, the range of analyzed parameters is not wide enough, in particular, taking into account the presence of anemia, which plays one of the key roles in modifying the risk of adverse outcomes (coronary deaths, repeated acute coronary events, progression of CHF).