Neurocritical care
-
Cerebral herniation due to brain edema is the major cause of neurological worsening in patients suffering large hemispheric strokes. In this study, we investigated whether quantitative pupillary response could help identify the neurological worsening due to brain swelling in patients with large hemispheric strokes. ⋯ Quantitative monitoring of the pupillary response using an automated pupillometer could be a useful and noninvasive tool for detecting neurological deterioration due to cerebral edema in large hemispheric stroke patients.
-
Cerebral edema and loss of gray-white matter differentiation on head computed tomography (CT) after cardiac arrest generally portend a poor prognosis. The interobserver variability in physician recognition of hypoxic-ischemic brain injury (HIBI) on early CT after out-of-hospital cardiac arrest has not been studied. ⋯ Physicians, including radiologists, demonstrated substantial interobserver variability when identifying HIBI on head CT soon after out-of-hospital cardiac arrest.
-
Critically ill aneurysmal subarachnoid hemorrhage (aSAH) patients suffer from systemic complications at a high rate. Hyperglycemia is a common intensive care unit (ICU) complication and has become a focus after aggressive glucose management was associated with improved ICU outcomes. Subsequent research has suggested that glucose variability, not a specific blood glucose range, may be a more appropriate clinical target. Glucose variability is highly correlated to poor outcomes in a wide spectrum of critically ill patients. Here, we investigate the changes between subsequent glucose values termed "inter-measurement difference," as an indicator of glucose variability and its association with outcomes in patients with aSAH. ⋯ Reduced glucose variability is highly correlated with in-patient survival and long-term mortality in aSAH patients. This finding was observed in the non-diabetic and well-controlled diabetic patients, suggesting a possible benefit for personalized glucose targets based on baseline HbA1c and minimizing variability. The inter-measure percentage change as an indicator of glucose variability is not only predictive of outcome, but is an easy-to-use tool that could be implemented in future clinical trials.