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...

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Bibliografiset tiedot

Päätekijät:	Edward G. Soltesz, MD, MPH, Randi J. Parks, PhD, Elise M. Jortberg, MS, Eugene H. Blackstone, MD
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Elsevier 2024-12-01
Sarja:	JTCVS Open
Aiheet:	CABG mitral valve surgery LV dysfunction machine learning postcardiotomy shock STS ACSD
Linkit:	http://www.sciencedirect.com/science/article/pii/S2666273624002766
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