AIMC Topic: Cardiac Surgical Procedures

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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...

Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

Cardiovascular diabetology
BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationsh...

Functional MRI-based machine learning strategy for prediction of postoperative delirium in cardiac surgery patients: A secondary analysis of a prospective observational study.

Journal of clinical anesthesia
STUDY OBJECTIVE: Delirium is a common complication after cardiac surgery and is associated with poor prognosis. An effective delirium prediction model could identify high-risk patients who might benefit from targeted prevention strategies. We introdu...