Neurocritical care
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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).
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Delayed cerebral ischemia (DCI), a complication of subarachnoid hemorrhage (SAH), is linked to cerebral vasospasm and associated with poor long-term outcome. We implemented a structured cerebral microdialysis (CMD) based protocol using the lactate/pyruvate ratio (LPR) as an indicator of the cerebral energy metabolic status in the neurocritical care decision making, using an LPR ≥ 30 as a cutoff suggesting an energy metabolic disturbance. We hypothesized that CMD monitoring could contribute to active, protocol-driven therapeutic interventions that may lead to the improved management of patients with SAH. ⋯ Active interventions were initiated in a majority of LPR events based on CMD monitoring. A low DCI incidence was observed, which may be associated with the active interventions. The potential aid of CMD in the clinical decision-making targeting DCI needs confirmation in additional SAH studies.
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Seizures are a harmful complication of acute intracerebral hemorrhage (ICH). "Early" seizures in the first week after ICH are a risk factor for deterioration, later seizures, and herniation. Ideally, seizure medications after ICH would only be administered to patients with a high likelihood to have seizures. We developed and validated machine learning (ML) models to predict early seizures after ICH. ⋯ Early seizures after ICH are predictable. Models using cortical hematoma location, age less than 65 years, and hematoma volume greater than 10 mL had a good accuracy rate, and performance improved with more independent variables. Additional methods to predict seizures could improve patient selection for monitoring and prophylactic seizure medications.
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Spontaneous intracerebral hemorrhage is a potentially devastating cause of brain injury, often occurring secondary to hypertension. Contrast extravasation on computed tomography angiography (CTA), known as the spot sign, has been shown to predict hematoma expansion and worse outcomes. Although hypertension has been associated with an increased rate of the spot sign being present, the relationship between spot sign and blood pressure has not been fully explored. ⋯ The presence of spot sign correlates with larger hematomas, worse outcomes, and increased surgical intervention. There is a significant association between spot sign and systolic blood pressure at the time of CTA, with the highest systolic blood pressure being recorded prior to CTA. Although the role of intensive blood pressure management in spontaneous intracerebral hemorrhage remains a subject of debate, patients with a spot sign may be a subgroup that could benefit from this.