Journal of cardiothoracic and vascular anesthesia
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J. Cardiothorac. Vasc. Anesth. · Oct 2023
Association Between Preoperative Sarcopenia and Early Postoperative Outcomes in Pediatric Patients Undergoing Total Correction of Tetralogy of Fallot: A Retrospective Cohort Study.
To identify the association between preoperative low muscle mass and early postoperative outcomes in pediatric patients undergoing total correction of tetralogy of Fallot (TOF). ⋯ The incidence of sarcopenia, as assessed by preoperative chest CT, was low in pediatric patients undergoing total correction of TOF, and preoperative sarcopenia did not predict early postoperative major adverse events.
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J. Cardiothorac. Vasc. Anesth. · Oct 2023
Observational StudyGastrointestinal Complications After Transesophageal Echocardiography for Mitral Valve Transcatheter Edge-to-Edge Repair: Insights From a Large Contemporary Cohort.
Transesophageal echocardiography-related complications (TEE-RC) are higher in structural heart interventions than in traditional operative settings. In mitral valve transcatheter edge-to-edge repair (MV-TEER), the incidence of TEE-RC may be higher than in other structural interventions. However, existing reports are limited and robust data evaluating TEE safety in this patient population are lacking. The authors sought to describe the incidence and risk factors of upper gastrointestinal injuries after TEE in patients undergoing MV-TEER. ⋯ In patients undergoing MV-TEER, TEE-RCs are uncommon, and major complications are rare. The authors' outcomes reflect those of a high-volume referral center with TEEs performed by cardiac anesthesiologists.
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J. Cardiothorac. Vasc. Anesth. · Oct 2023
CommentCon: Artificial Intelligence-Derived Algorithms to Guide Perioperative Blood Management Decision Making.
Artificial intelligence has the potential to improve the care that is given to patients; however, the predictive models created are only as good as the base data used in their design. Perioperative blood management presents a complex clinical conundrum in which significant variability and the unstructured nature of the required data make it difficult to develop precise prediction models. ⋯ Current systems created to predict perioperative blood transfusion are not generalizable across clinical settings, and there is a considerable cost implication required to research and develop artificial intelligence systems that would disadvantage resource-poor health systems. In addition, a lack of strong regulation currently means it is difficult to prevent bias.