Neurocritical care
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Observational Study
Cerebral Blood Flow and Oxygen Delivery in Aneurysmal Subarachnoid Hemorrhage: Relation to Neurointensive Care Targets.
The primary aim was to determine to what extent continuously monitored neurointensive care unit (neuro-ICU) targets predict cerebral blood flow (CBF) and delivery of oxygen (CDO2) after aneurysmal subarachnoid hemorrhage. The secondary aim was to determine whether CBF and CDO2 were associated with clinical outcome. ⋯ Systemic and cerebral physiological variables exhibited a modest association with CBF and CDO2. Still, cerebral hypoperfusion and low CDO2 were common and low CDO2 was associated with poor outcome. Xe-CT imaging could be useful to help detect secondary brain injury not evident by high ICP and low CPP.
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Sex-related differences in patients with spontaneous, non-traumatic intracerebral hemorrhage (ICH) are poorly investigated so far. This study elucidates whether sex-related differences in ICH care in a neurocritical care setting exist, particularly regarding provided care, while also taking patient characteristics, and outcomes into account. ⋯ Sex-related differences in patients with ICH regarding to provided neurosurgical care exist. We provide evidence that insertion of EVD is associated with male sex, disregarding clear reasoning. A sex-bias as well as social factors may play a significant role in decision-making for the insertion of an EVD.
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Dysfunctional cerebral autoregulation often precedes delayed cerebral ischemia (DCI). Currently, there are no data-driven techniques that leverage this information to predict DCI in real time. Our hypothesis is that information using continuous updated analyses of multimodal neuromonitoring and cerebral autoregulation can be deployed to predict DCI. ⋯ A TTSAM algorithm using multimodal neuromonitoring and cerebral autoregulation calculations shows promise to classify DCI in real time.
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Predictions of functional outcome in neurocritical care (NCC) patients impact care decisions. This study compared the predictive values (PVs) of good and poor functional outcome among health care providers with and without NCC training. ⋯ Neurointensivists expected better outcomes than other providers and were better at predicting poor functional outcomes. The PV of a good outcome prediction was modest among all providers.
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There is an unfulfilled need to find the best way to automatically capture, analyze, organize, and merge structural and functional brain magnetic resonance imaging (MRI) data to ultimately extract relevant signals that can assist the medical decision process at the bedside of patients in postanoxic coma. We aimed to develop and validate a deep learning model to leverage multimodal 3D MRI whole-brain times series for an early evaluation of brain damages related to anoxoischemic coma. ⋯ A fully automated identification of clinically relevant signals from complex multimodal neuroimaging data is a major research topic that may bring a radical paradigm shift in the neuroprognostication of patients with severe brain injury. We report for the first time a successful discrimination between patients in postanoxic coma patients from people serving as controls by using 3D CNN whole-brain structural and functional MRI data. Clinical Trial Number http://ClinicalTrials.gov (No. NCT03482115).