Resuscitation
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Veno-arterial Extracorporeal Membrane Oxygenation (VA-ECMO) is a rescue treatment in refractory cardiogenic shock (CS) or refractory cardiac arrest (CA). Exposure to hyperoxemia is common during VA-ECMO, and its impact on patient's outcome remains unclear. ⋯ Severe hyperoxemia exposure after initiation of VA-ECMO may be associated with an almost doubled increased probability of poor neurological outcome and mortality. Clinical efforts should be made to avoid severe hyperoxemia during VA-ECMO support.
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The primary aim of this systematic review was to investigate the most common electroencephalogram (EEG)-based machine learning (ML) model with the highest Area Under Receiver Operating Characteristic Curve (AUC) in two ML categories, conventional ML and Deep Neural Network (DNN), to predict the neurologic outcomes after cardiac arrest; the secondary aim was to investigate common EEG features applied to ML models. ⋯ RF and CNN were the two most common ML models with the highest AUCs for predicting the neurologic outcomes after cardiac arrest. Using a multimodal model that combines EEG features and electronic health record data may further improve prognostic performance.
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The primary aim of this systematic review was to investigate the most common electroencephalogram (EEG)-based machine learning (ML) model with the highest Area Under Receiver Operating Characteristic Curve (AUC) in two ML categories, conventional ML and Deep Neural Network (DNN), to predict the neurologic outcomes after cardiac arrest; the secondary aim was to investigate common EEG features applied to ML models. ⋯ RF and CNN were the two most common ML models with the highest AUCs for predicting the neurologic outcomes after cardiac arrest. Using a multimodal model that combines EEG features and electronic health record data may further improve prognostic performance.
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This systematic review aimed to determine to what extent and why the care pathways for acute cardiac events in the community might differ for minoritised ethnic populations compared to non-minoritised populations. It also sought to identify the barriers and enablers that could influence variations in access to care for minoritised populations. ⋯ The extent and reasons for differences in cardiac care pathways are considerable. There are several remediable barriers and enablers that require attention to achieve equitable access to care for minoritised populations.