Pro: Early Extubation (<1 Hour) After Cardiac Surgery Is a Useful, Safe, and Cost-Effective Method in Select Patient Populations

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

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 identify the most important predictors of extubation failure in patients undergoing cardiac surgery. Data from 776 adult patients who underwent cardiac surgery and were intubated for more than 24 h were obtained from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The primary endpoint was extubation failure according to the WIND criteria, with 205 patients experiencing extubation failure. The data was split into a training set (80%) and a test set (20%). The performance of the XGBoost algorithm was the highest (AUC 0.793, Mean Precision 0.700, Brier Score0.150), which was better than that of logistic regression (AUC 0.766, Mean Precision 0.553, Brier Score0.173) and random forest (AUC 0.791, Mean Precision 0.510, Brier Score 0.181). The most crucial predictor of extubation failure is the mean value of the anion gap in the 24 h before extubation. The other main features include ventilator parameters and blood gas indicators. By applying machine learning to large datasets, we developed a new method for predicting extubation failure after cardiac surgery in critically ill patients. Based on the predictive factors analyzed, internal environmental indicators and ventilation characteristics were important predictors of extubation failure. Therefore, these predictive factors should be considered when determining extubation readiness.

Minimally invasive technique facilitates early extubation after cardiac surgery: a single-center retrospective study

BACKGROUND

Postoperative time to extubation plays a role in prognosis after heart valve surgery; however, its exact impact has not been clarified. This study compared the postoperative outcomes of minimally invasive surgery and conventional sternotomy, focusing on early extubation and factors influencing prolonged mechanical ventilation.

METHODS

Data from 744 patients who underwent heart valve surgery at the Zhejiang Provincial People's Hospital between August 2019 and June 2022 were retrospectively analyzed. The outcomes in patients who underwent conventional median sternotomy (MS) and minimally invasive (MI) video-assisted thoracoscopic surgery were compared using inverse probability of treatment weighting (IPTW) and Kaplan-Meier curves. Clinical data, including surgical data, postoperative cardiac function, postoperative complications, and intensive care monitoring data, were analyzed.

RESULTS

After propensity score matching and IPTW, 196 cases of conventional MS were compared with 196 cases of MI video-assisted thoracoscopic surgery. Compared to patients in the conventional MS group, those in the MI video-assisted thoracoscopic surgery group in the matched cohort had a higher early postoperative extubation rate (P < 0.01), reduced incidence of postoperative pleural effusion (P < 0.05), significantly shorter length of stay in the intensive care unit (P < 0.01), shorter overall length of hospital stay (P < 0.01), and lower total cost of hospitalization (P < 0.01).

CONCLUSIONS

Successful early tracheal extubation is important for the intensive care management of patients after heart valve surgery. The advantages of MI video-assisted thoracoscopic surgery over conventional MS include significant reductions in the duration of use of mechanical ventilation support, reduced length of intensive care unit stay, reduced total length of hospitalization, and a favorable patient recovery rate.