Novel insights on association and reactivity of Bispectral Index, frontal electromyogram, and autonomic responses in nociception-sedation monitoring of critical care patients.

Background: Assessing nociception and sedation in mechanically ventilated patients in the ICU is challenging, with few reliable methods available for continuous monitoring. Measurable cardiovascular and neurophysiological signals, such as frontal EEG, frontal EMG, heart rate, and blood pressure, have potential in sedation and nociception monitoring. The hypothesis of this explorative study is that derived variables from the aforementioned signals predict the level of sedation, as described by the Richmond Agitation-Sedation score (RASS), and respond to painful stimuli during critical care.

Dynamic prediction of mortality after traumatic brain injury using a machine learning algorithm.

Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure (ICP) and cerebral perfusion pressure (CPP). The transformation of ICP and CPP time-series data into a dynamic prediction model could aid clinicians to make more data-driven treatment decisions. We retrained and externally validated a machine learning model to dynamically predict the risk of mortality in patients with TBI.

Foundations of Brain Image Segmentation: Pearls and Pitfalls in Segmenting Intracranial Blood on Computed Tomography Images.

Not only the time-dependent varying of signal intensity (i.e. haematoma evolution) characteristics of the intracranial blood in computed tomography images, but also the fluctuating image quality, the distortions introduced after medical interventions, and the brain deformations and intensity profile variations due to underlying pathologies make the segmentation of intracranial blood a challenging task.

Responsiveness Index versus the RASS-Based Method for Adjusting Sedation in Critically Ill Patients.

Background: Sedation of intensive care patients is needed for patient safety, but deep sedation is associated with adverse outcomes. Frontal electromyogram-based Responsiveness Index (RI) aims to quantify the level of sedation and is scaled 0-100 (low index indicates deep sedation). We compared RI-based sedation to Richmond Agitation-Sedation Scale- (RASS-) based sedation.

Effect of Inhaled Xenon on Cardiac Function in Comatose Survivors of Out-of-Hospital Cardiac Arrest-A Substudy of the Xenon in Combination With Hypothermia After Cardiac Arrest Trial.

Unlabelled: This explorative substudy aimed at determining the effect of inhaled xenon on left ventricular function by echocardiography in comatose survivors of out-of-hospital cardiac arrest.

Design: A randomized two-group single-blinded phase 2 clinical drug trial.

Setting: A multipurpose ICU in two university hospitals.