AIMC Topic: Cardiopulmonary Bypass

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GenAI exceeds clinical experts in predicting acute kidney injury following paediatric cardiopulmonary bypass.

Scientific reports
The emergence of large language models (LLMs) opens new horizons to leverage, often unused, information in clinical text. Our study aims to capitalise on this new potential. Specifically, we examine the utility of text embeddings generated by LLMs in...

Pediatric cardiac surgery: machine learning models for postoperative complication prediction.

Journal of anesthesia
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 ...

Development and validation of a machine learning predictive model for perioperative myocardial injury in cardiac surgery with cardiopulmonary bypass.

Journal of cardiothoracic surgery
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...

Effect of Retrograde Autologous Priming on Coagulation Assessed by Rotation Thromboelastometry in Patients Undergoing Valvular Cardiac Surgery.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVES: To investigate the effect of retrograde autologous priming (RAP) on coagulation function using rotation thromboelastometry (ROTEM) in patients undergoing valvular cardiac surgery.

Oxygen delivery in pediatric cardiac surgery and its association with acute kidney injury using machine learning.

The Journal of thoracic and cardiovascular surgery
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...

Management algorithms and artificial intelligence systems for cardiopulmonary bypass.

Perfusion
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...

Neural network-based modeling of the number of microbubbles generated with four circulation factors in cardiopulmonary bypass.

Scientific reports
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...

A Comparative Study of Point-of-Care Prothrombin Time in Cardiopulmonary Bypass Surgery.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVE: Point-of-care (POC) devices allow for prothrombin time/international normalized ratio (PT/INR) testing in whole blood (WB) and timely administration of plasma or prothrombin complex concentrate during cardiopulmonary bypass surgery. This s...