Neurocritical care
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Neurologically critically ill patients present with unique disease trajectories, prognostic uncertainties, and challenges to end-of-life (EOL) care. Acute brain injuries place these patients at risk for underrecognized symptoms and unmet EOL management needs, which can negatively affect their quality of care and lead to complicated grief in surviving loved ones. To care for patients nearing the EOL in the neurointensive care unit, health care clinicians must consider neuroanatomic localization, barriers to symptom assessment and management, unique aspects of the dying process, and EOL management needs. ⋯ We aim to define current best practices, barriers, and future directions for EOL care of the neurologically critically ill patient.
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Despite improvements in survival after illnesses requiring extracorporeal life support, cerebral injury continues to hinder successful outcomes. Cerebral autoregulation (CA) is an innate protective mechanism that maintains constant cerebral blood flow in the face of varying systemic blood pressure. However, it is impaired in certain disease states and, potentially, following initiation of extracorporeal circulatory support. ⋯ Next, we examine factors intrinsic to ECMO that may affect CA, such as cannulation, changes in pulsatility, the inflammatory and adaptive immune response, intracranial hemorrhage, and ischemic stroke, in addition to ECMO management factors, such as oxygenation, ventilation, flow rates, and blood pressure management. We highlight potential mechanisms that lead to disruption of CA in both pediatric and adult populations, the challenges of measuring CA in these patients, and potential associations with neurological outcome. Altogether, we discuss individualized CA monitoring as a potential target for improving neurological outcomes in extracorporeal life support.
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To investigate patients with disorders of consciousness (DoC) for residual awareness, guidelines recommend quantifying glucose brain metabolism using positron emission tomography. However, this is not feasible in the intensive care unit (ICU). Cerebral blood flow (CBF) assessed by arterial spin labeling magnetic resonance imaging (ASL-MRI) could serve as a proxy for brain metabolism and reflect consciousness levels in acute DoC. We hypothesized that ASL-MRI would show compromised CBF in coma and unresponsive wakefulness states (UWS) but relatively preserved CBF in minimally conscious states (MCS) or better. ⋯ CBF measurement in ICU patients using ASL-MRI is feasible but cannot distinguish between the lower and the upper ends of the acute DoC spectrum. We suggest that pilot testing of diagnostic interventions at the extremes of this spectrum is a time-efficient approach in the continued quest to develop DoC neuroimaging markers in the ICU.
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Observational Study
Association Between Early Hyperoxemia Exposure and Intensive Care Unit Mortality in Intracerebral Hemorrhage: An Observational Cohort Analysis.
Supraphysiologic levels of oxygen could have potential adverse effects on the brain that may be dose and time dependent in patients with brain injury. We therefore aimed to assess whether exposure to excess supplemental oxygen, measured as time-weighted mean exposure to hyperoxemia, was associated with intensive care unit (ICU) mortality in patients with intracerebral hemorrhage (ICH). ⋯ In patients with ICH admitted to the ICU, we observed an association between hyperoxemia dose and ICU mortality. Further prospective study is required to inform guidance on early systemic oxygen targets in ICH.
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Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity. ⋯ Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.