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As the global elderly population continues to rise, the risk of severe crashes among elderly drivers has become a pressing concern. This study presents a comprehensive examination of crash severity among this demographic, employing machine learning models and data gathered from Virginia, United States of America, between 2014 and 2021. The analysis integrates parametric models, namely logistic regression and linear discriminant analysis (LDA), as well as non-parametric models like random forest (RF) and extreme gradient boosting (XGBoost). Central to this study is the application of resampling techniques, specifically, random over-sampling examples (ROSE) and the synthetic minority over-sampling technique (SMOTE), to address the dataset’s inherent imbalance and enhance the models’ predictive performance. Our findings reveal that the inclusion of these resampling techniques significantly improves the predictive power of parametric models, notably increasing the true positive rate for severe crash prediction from 6% to 60% and boosting the geometric mean from 25% to 69% in logistic regression. Likewise, employing SMOTE resulted in a notable improvement in the non-parametric models’ performance, leading to a true positive rate increase from 8% to 36% in XGBoost. Moreover, the study established the superiority of parametric models over non-parametric counterparts when balanced resampling techniques are utilized. Beyond predictive modeling, the study delves into the effects of various contributing factors on crash severity, enhancing the understanding of how these factors influence elderly road safety. Ultimately, these findings underscore the immense potential of machine learning models in analyzing complex crash data, pinpointing factors that heighten crash severity, and informing targeted interventions to mitigate the risks of elderly driving. Published version

SEPARATION from cardiopulmonary bypass (CPB) after cardiac surgery is a progressive transition from full mechanical circulatory and respiratory support to spontaneous mechanical activity of the lungs and heart. During the separation phase, measurements of cardiac performance with transesophageal echocardiography (TEE) provide the rationale behind the diagnostic and therapeutic decision-making process. In many cases, it is possible to predict a complex separation from CPB, such as when there is known preoperative left or right ventricular dysfunction, bleeding, hypovolemia, vasoplegia, pulmonary hypertension, or owing to technical complications related to the surgery. Prompt diagnosis and therapeutic decisions regarding mechanical or pharmacologic support have to be made within a few minutes. In fact, a complex separation from CPB if not adequately treated leads to a poor outcome in the vast majority of cases. Unfortunately, no specific criteria defining complex separation from CPB and no management guidelines for these patients currently exist. Taking into account the above considerations, the aim of the present review is to describe the most common scenarios associated with a complex CPB separation and to suggest strategies, pharmacologic agents, and para-corporeal mechanical devices that can be adopted to manage patients with complex separation from CPB. The routine management strategies of complex CPB separation of 17 large cardiac centers from 14 countries in 5 continents will also be described.

Background: Volatile (inhaled) anesthetic agents have cardioprotective effects, which might improve clinical outcomes in patients undergoing coronary-artery bypass grafting (CABG). Methods: We conducted a pragmatic, multicenter, single-blind, controlled trial at 36 centers in 13 countries. Patients scheduled to undergo elective CABG were randomly assigned to an intraoperative anesthetic regimen that included a volatile anesthetic (desflurane, isoflurane, or sevoflurane) or to total intravenous anesthesia. The primary outcome was death from any cause at 1 year. Results: A total of 5400 patients were randomly assigned: 2709 to the volatile anesthetics group and 2691 to the total intravenous anesthesia group. On-pump CABG was performed in 64% of patients, with a mean duration of cardiopulmonary bypass of 79 minutes. The two groups were similar with respect to demographic and clinical characteristics at baseline, the duration of cardiopulmonary bypass, and the number of grafts. At the time of the second interim analysis, the data and safety monitoring board advised that the trial should be stopped for futility. No significant difference between the groups with respect to deaths from any cause was seen at 1 year (2.8% in the volatile anesthetics group and 3.0% in the total intravenous anesthesia group ; relative risk, 0.94 ; 95% confidence interval [CI], 0.69 to 1.29 ; P = 0.71), with data available for 5353 patients (99.1%), or at 30 days (1.4% and 1.3%, respectively ; relative risk, 1.11 ; 95% CI, 0.70 to 1.76), with data available for 5398 patients (99.9%). There were no significant differences between the groups in any of the secondary outcomes or in the incidence of prespecified adverse events, including myocardial infarction. Conclusions: Among patients undergoing elective CABG, anesthesia with a volatile agent did not result in significantly fewer deaths at 1 year than total intravenous anesthesia.