Neurocritical care
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Randomized Controlled Trial Multicenter Study
Predicting Gastrostomy Tube Placement After Intracerebral Hemorrhage: External Validation of the GRAVo Score.
Dysphagia is a common consequence of intracerebral hemorrhages (ICH). It can lead to enduring impairments of dietary intake and the requirement for feeding via percutaneous gastrostomy (PEG) tubes. However, variabilities in the course of swallowing recovery after ICH make it difficult to anticipate the need for PEG placement in an individual patient. A new tool called the GRAVo score was recently developed to predict PEG tube placement after an ICH but has not been externally validated. Our study aims were to externally validate the GRAVo score in a multicenter cohort and reexamine the role of race in predicting PEG placement, given the uncertain biological plausibility for this relationship observed in the derivation cohort. ⋯ The results of our external validation demonstrate the validity of GRAVo scores for predicting PEG tube placement after an ICH. However, its performance was more modest compared with that of the derivation cohort. Inclusion of the race variable had no measurable effect on model performance. Differences in patient characteristics between these cohorts may have influenced our results. These findings should be taken into consideration when using the GRAVo score to assist clinical decision making on PEG placement after an ICH.
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Multicenter Study Observational Study
Association Between Serum Albumin and Hospital-Acquired Infections After Aneurysmal Subarachnoid Hemorrhage.
Low serum albumin levels have been identified as a predictor of infectious complications in critically ill patients. However, the association in patients with aneurysmal subarachnoid hemorrhage (aSAH) remains unclear. We aimed to evaluate the prognostic value of hypoalbuminemia using blood samples at admission in patients with aSAH. ⋯ In this large study of matched patients with aSAH, hypoalbuminemia at admission was associated with hospital-acquired infections. A decrease in serum albumin levels within 72 h of admission was associated with higher hospital-acquired infections.
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Multicenter Study
Neurological Prognostication After Hypoglycemic Coma: Role of Clinical and EEG Findings.
Hypoglycemic coma (HC) is an uncommon but severe clinical condition associated with poor neurological outcome. There is a dearth of robust neurological prognostic factors after HC. On the other hand, there is an increasing body of literature on reliable prognostic markers in the postanoxic coma, a similar-albeit not identical-situation. The objective of this study was thus to investigate the use and predictive value of these markers in HC. ⋯ This preliminary study suggests that highly malignant EEG patterns might be reliable prognostic markers of unfavorable outcome after HC. Other EEG findings, including lack of EEG reactivity and seizures and clinical findings appear less accurate. These findings should be replicated in a larger multicenter prospective study.
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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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Big data (BD) and artificial intelligence (AI) have increasingly been used in neurocritical care. "BD" can be operationally defined as extremely large datasets that are so large and complex that they cannot be analyzed by using traditional statistical modeling. "AI" means the ability of machines to perform tasks similar to those performed by human intelligence. We present a brief overview of the most commonly applied AI techniques to perform BD analytics and discuss some of the recent promising examples in the field of neurocritical care. The latter include the following: cognitive motor dissociation in disorders of consciousness, hypoxic-ischemic injury following cardiac arrest, delayed cerebral ischemia and vasospasm after subarachnoid hemorrhage, and monitoring of intracranial pressure. ⋯ These collaborations will allow us to share data, combine predictive algorithms, and analyze multiple and cumulative sources of data retrospectively and prospectively. Once AI algorithms are validated at multiple centers, they should be tested in randomized controlled trials investigating their impact on clinical outcome. The neurocritical care community must work to ensure that AI incorporates standards to ensure fairness and health equity rather than reflect our biases present in our collective conscience.