Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness.

Background: The continuation of life-sustaining therapy in critical care patients with anoxic-ischemic disorders of consciousness (AI-DOC) depends on prognostic tests such as serum neuron-specific enolase (NSE) concentration levels.

Objectives: To apply predictive models using machine learning methods to examine, one year after onset, the prognostic power of serial measurements of NSE in patients with AI-DOC. To compare the discriminative accuracy of this method to both standard single-day, absolute, and difference-between-days, relative NSE levels.

Consciousness Indexing and Outcome Prediction with Resting-State EEG in Severe Disorders of Consciousness.

We applied the following methods to resting-state EEG data from patients with disorders of consciousness (DOC) for consciousness indexing and outcome prediction: microstates, entropy (i.e. approximate, permutation), power in alpha and delta frequency bands, and connectivity (i.

Simultaneous EEG-PET-fMRI measurements in disorders of consciousness: an exploratory study on diagnosis and prognosis.

Previous studies could demonstrate that functional magnetic resonance imaging (fMRI), fludeoxyglucose positron emission tomography (FDG-PET), and electroencephalography (EEG) measures contain information about patients suffering from disorders of consciousness (DOC) and thus improve the clinical diagnosis. Additionally, the technical modalities were able to predict the outcome of patients. However, most studies lack proven reproducibility in a clinical setting.

Severe disorders of consciousness after acquired brain injury: A single-centre long-term follow-up study.

Objectives: To assess long-term clinical outcome, functional independence and health-related quality of life (HRQOL) in acquired brain injury (ABI) patients with a disorder of consciousness at admission to inpatient rehabilitation.

Methods: We selected patients from a cohort of ABI patients from a single centre. In addition to mortality, we measured level of consciousness with the Coma Remission Scale, functional independence with the Barthel Index, as well as generic and condition-specific HRQOL with the EQ5D and the "Quality of Life after Brain Injury" (QOLIBRI) respectively.

Hypoxia and Outcome Prediction in Early-Stage Coma (Project HOPE): an observational prospective cohort study.

Background: The number of resuscitated cardiac arrest patients suffering from anoxic-ischemic encephalopathy is considerable. However, outcome prediction parameters such as somatosensory evoked potentials need revision because they are based on data predating the implementation of mild therapeutical hypothermia and because data from our own laboratory suggest that they may fail to predict prognosis accurately. The present research project "Hypoxia and Outcome Prediction in Early-Stage Coma" is an ongoing observational prospective cohort study that aims to improve outcome prediction in anoxic coma by limiting the effects of falsely pessimistic predictions at the intensive care unit.

Stability of auditory event-related potentials in coma research.

Patients with unresponsive wakefulness syndrome (UWS) or in minimally conscious state (MCS) after brain injury show significant fluctuations in their behavioural abilities over time. As the importance of event-related potentials (ERPs) in the detection of traces of consciousness increases, we investigated the retest reliability of ERPs with repeated tests at four different time points. Twelve healthy controls and 12 inpatients (8 UWS, 4 MCS; 6 traumatic, 6 non-traumatic) were tested twice a day (morning, afternoon) for 2 days with an auditory oddball task.

Nonverbal memory tasks in early differential diagnosis of Alzheimer's disease and unipolar depression.

We examined whether there are selective deficits in early-stage Alzheimer's disease (AD; n = 27) and in unipolar depression (UD; n = 17) patients on recall and recognition of spatial and visual components of nonverbal memory (NVM) and whether the two groups can be differentiated based on their performance on such tasks. We also investigated which NVM measures had the best discrimination power. We tested spatial, visuospatial, and visuoconstructive abilities in AD and UD patients.