Journal of cardiothoracic and vascular anesthesia
38262805
OBJECTIVES: To investigate the effect of retrograde autologous priming (RAP) on coagulation function using rotation thromboelastometry (ROTEM) in patients undergoing valvular cardiac surgery.
Journal of cardiothoracic and vascular anesthesia
29429928
OBJECTIVE: Cardiopulmonary bypass (CPB) surgery commonly threatens the heart and remote organs with ischemia-reperfusion injury. Transient episodes of ischemia to nonvital tissue, known as remote ischemic preconditioning (RIPC), is thought to help lo...
Journal of cardiothoracic and vascular anesthesia
29398374
OBJECTIVE: This study was designed to investigate the association between ocular blood flow measured using laser speckle flowgraphy (LSFG) and radial arterial pressure during aortic arch surgery.
The need for the estimation of the number of microbubbles (MBs) in cardiopulmonary bypass surgery has been recognized among surgeons to avoid postoperative neurological complications. MBs that exceed the diameter of human capillaries may cause endoth...
This article introduces management algorithms to support operators in choosing the best strategy for metabolic management during cardiopulmonary bypass using artificial intelligence systems. We developed algorithms for the identification of the optim...
The Journal of thoracic and cardiovascular surgery
35840430
OBJECTIVE: Acute kidney injury (AKI) after pediatric cardiac surgery with cardiopulmonary bypass (CPB) is a frequently reported complication. In this study we aimed to determine the oxygen delivery indexed to body surface area (Doi) threshold associa...
BACKGROUND: Perioperative myocardial injury (PMI) with different cut-off values has showed to be associated with different prognostic effect after cardiac surgery. Machine learning (ML) method has been widely used in perioperative risk predictions du...
PURPOSE: Managing children undergoing cardiac surgery with cardiopulmonary bypass (CPB) presents a significant challenge for anesthesiologists. Machine Learning (ML)-assisted tools have the potential to enhance the recognition of patients at risk of ...