Machine learning−derived multivariable predictors of postcardiotomy cardiogenic shock in high-risk cardiac surgery patientsCentral MessagePerspective

Machine learning−derived multivariable predictors of postcardiotomy cardiogenic shock in high-risk cardiac surgery patientsCentral MessagePerspective

Objective: To develop a model for preoperatively predicting postcardiotomy cardiogenic shock (PCCS) in patients with poor left ventricular (LV) function undergoing cardiac surgery. Methods: From the Society of Thoracic Surgeons Adult Cardiac Database, 11,493 patients with LV ejection fraction ≤35% u...

Full description

Bibliographic Details
Main Authors: Edward G. Soltesz, MD, MPH, Randi J. Parks, PhD, Elise M. Jortberg, MS, Eugene H. Blackstone, MD
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:JTCVS Open
Subjects:
CABG
mitral valve surgery
LV dysfunction
machine learning
postcardiotomy shock
STS ACSD
Online Access:http://www.sciencedirect.com/science/article/pii/S2666273624002766

Internet

http://www.sciencedirect.com/science/article/pii/S2666273624002766

Similar Items