Why the study?
Does the assessment of genetic and dynamic biomarkers predict adverse clinical outcomes and graft patency in patients undergoing CABG?
Does the assessment of genetic and dynamic biomarkers predict adverse clinical outcomes and graft patency in patients undergoing CABG?
While genetic and dynamic biomarkers show potential associations with adverse outcomes after CABG, their routine clinical use for outcome prediction remains in early developmental phases requiring larger validation studies.
Biomarker panels for CABG risk prediction remain premature for clinical use; leaves open validation of specific algorithms in larger prospective studies.
Coronary artery bypass surgery (CABG) is still one of the most frequently performed surgical procedures all over the world. The results of this procedure have been constantly improved over the years with low perioperative mortality rates, with relatively low complication rates. To further improve these outstanding results, the clinicians focused their attention at biomarkers as outcome predictors. Although biological testing for disease prediction has already been discussed many times, the role of biomarkers in outcome prediction after CABG is still controversial. In this article, we reviewed the current knowledge regarding the role of genetic and dynamic biomarkers and their possible association with the occurrence of adverse clinical outcomes after CABG. We also took into consideration that the molecular pathway activation and the possible imbalance may affect hard outcomes and graft patency. We analyzed biomarkers classified in two different categories depending on their possibility to change over time: genetic markers and dynamic markers. Moreover, we evaluated these markers by dividing them, into sub-categories, such as inflammation, hemostasis, renin-angiotensin, endothelial function, and other pathways. We showed that biomarkers might be associated with unfavorable outcomes after surgery, and in some cases improved outcome prediction. However, the identification of a specific panel of biomarkers or of some algorithms including biomarkers is still in an early developmental phase. Finally, larger studies are needed to analyze broad panel of biomarkers with the specific aim to evaluate the prediction of hard outcomes and graft patency.
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Parolari et al. (2016) studied this question.
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