AIMC Topic: Cardiac Surgical Procedures

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Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis.

BMC anesthesiology
BACKGROUND: Intraoperative hypotension (IOH), defined as a mean arterial pressure (MAP) below 65 mmHg, is a common complication during surgery and is associated with significant postoperative morbidity, including acute kidney injury, myocardial injur...

Artificial intelligence-based action recognition and skill assessment in robotic cardiac surgery simulation: a feasibility study.

Journal of robotic surgery
To create a deep neural network capable of recognizing basic surgical actions and categorizing surgeons based on their skills using video data only. Nineteen surgeons with varying levels of robotic experience performed three wet lab tasks on a porcin...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

Nature communications
While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence ...

Current and future applications of robotics in structural heart interventions.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
Robotics entered the cardiovascular field in the late 1990s with a robot-assisted coronary artery bypass graft. Since then, the use of robots has become a common part of cardiovascular surgery in several types of interventions. The experience in tran...

Development and validation of a cardiac surgery-associated acute kidney injury prediction model using the MIMIC-IV database.

PloS one
OBJECTIVE: This study aimed to develop an innovative early prediction model for acute kidney injury (AKI) following cardiac surgery in intensive care unit (ICU) settings, leveraging preoperative and postoperative clinical variables, and to identify k...

Shaping the Future of Cardiac Anesthesia: Emerging Trends and Research Directions.

Anesthesiology clinics
This article provides an overview of knowledge gaps that need to be addressed in perioperative cardiac surgery, including concomitant surgical procedures, approaches to the conduct of cardiopulmonary bypass, precision medicine, and patient-important ...

The Year in Perioperative Echocardiography: Selected Highlights from 2024.

Journal of cardiothoracic and vascular anesthesia
This article is the ninth of an annual series reviewing the research highlights of the year pertaining to the subspecialty of perioperative echocardiography for the Journal of Cardiothoracic and Vascular Anesthesia. The authors thank the editor-in-ch...

Right ventricular dysfunction following tetralogy of Fallot correction: anatomical determinants and therapeutic strategies.

International journal of surgery (London, England)
Right ventricular dysfunction following surgical correction of tetralogy of Fallot (TOF) remains a major determinant of long-term morbidity and mortality in survivors. Despite advancements in surgical techniques, residual anatomical abnormalities - i...

Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study.

International journal of surgery (London, England)
BACKGROUND: This study addresses the critical need for timely and accurate diagnosis of early postoperative infection (EPI) following cardiac surgery. EPI significantly impacts patient outcomes and healthcare costs, making its early detection vital.

Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.

Scientific reports
Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience extubation failure and reintubation. The aim of this study was to establish an extubation prediction model using explainable machine learning and identif...