Why the study?
Assessing the predictive value of hemodynamic parameters is needed to optimize early diagnosis, prevention, and intensive care of cardiovascular events associated with CABG.
Hemodynamic monitoring combined with artificial intelligence technologies may help optimize early diagnosis and predict early and long-term outcomes in patients undergoing CABG.
Highlights potential of hemodynamic-AI integration for CABG prognostication; leaves open clinical utility pending prospective validation.
The review presents an analysis of the scientific literature on the assessment of the predictive value of hemodynamic parameters for predicting the immediate and long-term results of coronary artery bypass grafting (CABG). Modern options for hemodynamic and volumetric monitoring are considered, including transesophageal echocardiography, prepulmonary, transpulmonary thermodilution, as well as other methods based on estimation of pulse wave transit time. The information content of individual hemodynamic parameters is discussed to optimize the early diagnosis, prevention and intensive care of cardiovascular events associated with CABG. The scientific literature on stratification of the risks of postoperative complications and mortality based on the analysis of the predictive value of hemodynamic parameters is generalized. Variants of the integrated application of hemodynamic monitoring methods and artificial intelligence technologies for the development of automated systems for predicting the near and long-term results of CABG are analyzed.
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Rublev et al. (2020) studied this question.
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