Predictors of in-ICU length of stay among congenital heart defect patients using artificial intelligence model: A pilot study.

Objective: This study aims to develop a predictive model using artificial intelligence to estimate the ICU length of stay (LOS) for Congenital Heart Defects (CHD) patients after surgery, improving care planning and resource management.

Design: We analyze clinical data from 2240 CHD surgery patients to create and validate the predictive model. Twenty AI models are developed and evaluated for accuracy and reliability.

Dobutamine-sparing versus dobutamine-to-all strategy in cardiac surgery: a randomized noninferiority trial.

Background: The detrimental effects of inotropes are well-known, and in many fields they are only used within a goal-directed therapy approach. Nevertheless, standard management in many centers includes administering inotropes to all patients undergoing cardiac surgery to prevent low cardiac output syndrome and its implications. Randomized evidence in favor of a patient-tailored, inotrope-sparing approach is still lacking.

Improving preoperative risk-of-death prediction in surgery congenital heart defects using artificial intelligence model: A pilot study.

Background: Congenital heart disease accounts for almost a third of all major congenital anomalies. Congenital heart defects have a significant impact on morbidity, mortality and health costs for children and adults. Research regarding the risk of pre-surgical mortality is scarce.

Effect of a Perioperative Intra-Aortic Balloon Pump in High-Risk Cardiac Surgery Patients: A Randomized Clinical Trial.

Objectives: The aim of this study was to evaluate the efficacy of perioperative intra-aortic balloon pump use in high-risk cardiac surgery patients.

Design: A single-center randomized controlled trial and a meta-analysis of randomized controlled trials.

Setting: Heart Institute of São Paulo University.