Neurocritical care
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Beta-lactam neurotoxicity is a relatively uncommon yet clinically significant adverse effect in critically ill patients. This study sought to define the incidence of neurotoxicity, derive a prediction model for beta-lactam neurotoxicity, and then validate the model in an independent cohort of critically ill adults. ⋯ In this single center cohort of critically ill patients, beta-lactam neurotoxicity was demonstrated less frequently than previously reported. We identified obesity as a novel risk factor for the development of neurotoxicity. The prediction model needs to be further refined before it can be used in clinical practice as a tool to avoid drug-related harm.
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Randomized Controlled Trial
Timely and Appropriate Administration of Inhaled Argon Provides Better Outcomes for tMCAO Mice: A Controlled, Randomized, and Double-Blind Animal Study.
Inhaled argon (iAr) has shown promising therapeutic efficacy for acute ischemic stroke and has exhibited impressive advantages over other inert gases as a neuroprotective agent. However, the optimal dose, duration, and time point of iAr for acute ischemic stroke are unknown. Here, we explored variable iAr schedules and evaluated the neuroprotective effects of acute iAr administration on lesion volume, brain edema, and neurological function in a mouse model of cerebral ischemic/reperfusion injury. ⋯ Timely iAr administration during ischemia showed optimal neurological outcomes and minimal infarct volumes. Moreover, an appropriate duration of argon administration was important for better neuroprotective efficacy. These findings may provide vital guidance for using argon as a neuroprotective agent and moving to clinical trials in acute ischemic stroke.
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Multicenter Study
Hospital Length of Stay and 30-Day Mortality Prediction in Stroke: A Machine Learning Analysis of 17,000 ICU Admissions in Brazil.
Hospital length of stay and mortality are associated with resource use and clinical severity, respectively, in patients admitted to the intensive care unit (ICU) with acute stroke. We proposed a structured data-driven methodology to develop length of stay and 30-day mortality prediction models in a large multicenter Brazilian ICU cohort. ⋯ Hospital length of stay and 30-day mortality of patients admitted to the ICU with stroke were accurately predicted through machine learning methods, even in the absence of stroke-specific data, such as the National Institutes of Health Stroke Scale score or neuroimaging findings. The proposed methods using general intensive care databases may be used for resource use allocation planning and performance assessment of ICUs treating stroke. More detailed acute neurological and management data, as well as long-term functional outcomes, may improve the accuracy and applicability of future machine-learning-based prediction algorithms.
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Multicenter Study Observational Study
Prolonged Automated Robotic TCD Monitoring in Acute Severe TBI: Study Design and Rationale.
Transcranial Doppler ultrasonography (TCD) is a portable, bedside, noninvasive diagnostic tool used for the real-time assessment of cerebral hemodynamics. Despite the evident utility of TCD and the ability of this technique to function as a stethoscope to the brain, its use has been limited to specialized centers because of the dearth of technical and clinical expertise required to acquire and interpret the cerebrovascular parameters. Additionally, the conventional pragmatic episodic TCD monitoring protocols lack dynamic real-time feedback to guide time-critical clinical interventions. Fortunately, with the recent advent of automated robotic TCD technology in conjunction with the automated software for TCD data processing, we now have the technology to automatically acquire TCD data and obtain clinically relevant information in real-time. By obviating the need for highly trained clinical personnel, this technology shows great promise toward a future of widespread noninvasive monitoring to guide clinical care in patients with acute brain injury. ⋯ The overarching goal of this study is to establish safety and feasibility of prolonged automated TCD monitoring for patients with TBI in the intensive care unit and identify clinically meaningful and pragmatic noninvasive targets for future interventions.