Neurocritical care
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Subtle and profound changes in autonomic nervous system (ANS) function affecting sympathetic and parasympathetic homeostasis occur as a result of critical illness. Changes in ANS function are particularly salient in neurocritical illness, when direct structural and functional perturbations to autonomic network pathways occur and may herald impending clinical deterioration or intervenable evolving mechanisms of secondary injury. Sympathetic and parasympathetic balance can be measured quantitatively at the bedside using multiple methods, most readily by extracting data from electrocardiographic or photoplethysmography waveforms. ⋯ Here, we review data-analytic approaches to measuring ANS dysfunction from routine bedside physiologic data streams and integrating this data into multimodal machine learning-based model development to better understand phenotypical expression of pathophysiologic mechanisms and perhaps even serve as early detection signals. Attention will be given to examples from our work in acute traumatic brain injury on detection and monitoring of paroxysmal sympathetic hyperactivity and prediction of neurologic deterioration, and in large hemispheric infarction on prediction of malignant cerebral edema. We also discuss future clinical applications and data-analytic challenges and future directions.
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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
Intracranial Pressure Monitoring in the Intensive Care Unit for Patients with Severe Traumatic Brain Injury: Analysis of the CENTER-TBI China Registry.
Although the current guidelines recommend the use of intracranial pressure (ICP) monitoring in patients with severe traumatic brain injury (sTBI), the evidence indicating benefit is limited. The present study aims to evaluate the impact of ICP monitoring on patients with sTBI in the intensive care unit (ICU). ⋯ Although ICP monitoring was not widely used by all of the centers participating in this study, patients with sTBI managed with ICP monitoring show a better outcome in overall survival. Nevertheless, the use of ICP monitoring makes the management of sTBI more complex and increases the costs of medical care by prolonging the patient's stay in the ICU or hospital.
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Strong evidence in support of guidelines for traumatic brain injury (TBI) is lacking. Large-scale observational studies may offer a complementary source of evidence to clinical trials to improve the care and outcome for patients with TBI. They are, however, challenging to execute. ⋯ We see potential for individual patient data meta-analyses in connection to other large-scale projects. Our collaboration with Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) has taught us that although standardized data collection and coding according to common data elements can facilitate such meta-analyses, further data harmonization is required for meaningful results. Both CENTER-TBI and TRACK-TBI have demonstrated the complexity of the conduct of large-scale collaborative studies that produce high-quality science and new insights.