BackgroundThe presence of angiographic vasospasm after aneurysmal subarachnoid hemorrhage (aSAH) is associated with delayed-cerebral ischemia (DCI)-related cerebral infarction and worsened neurological outcome. Transcranial doppler (TCD) measurements of cerebral blood velocity are commonly used after aSAH to screen for vasospasm. We sought to determine whether time-varying TCD measured vasospasm severity is associated with cerebral infarction and to investigate the performance characteristics of different time/severity cutoffs for predicting cerebral infarction.MethodsWe used a retrospective, single-center cohort of consecutive adult aSAH patients with angiographic vasospasm and at least one TCD study. Our primary outcome was DCI-related cerebral infarction, defined as an infarction developing at least 2 days after any surgical intervention without an alternative cause. Time-varying TCD vasospasm severity was defined ordinally (absent, mild, moderate, severe) by the most abnormal vessel on each post-admission hospital day. Cox proportional-hazards models were used to examine associations between time-varying vasospasm severity and infarction. The optimal TCD-based time/severity thresholds for predicting infarction were then identified using the Youden J statistic.ResultsOf 218 aSAH patients with angiographic vasospasm, 27 (12%) developed DCI-related infarction. As compared to those without infarction, patients with infarction had higher modified Fisher scale (mFS) scores, and an earlier onset of more-severe vasospasm. Adjusted for mFS, vasospasm severity was associated with infarction (aHR 1.9, 95% CI: 1.3-2.6). A threshold of at least mild vasospasm severity on hospital day 4 had a negative predictive value of 92% for the development of infarction, but a positive predictive value of 25%.ConclusionsIn aSAH, TCD-measured vasospasm severity is associated with DCI-related infarction. In a single-center dataset, a TCD-based threshold for predicting infarction had a high negative predictive value, supporting its role as an early screening tool to identify at-risk patients.
Introduction Disorders of consciousness, EEG background suppression and epileptic seizures are associated with poor outcome after cardiac arrest. The underlying patterns of anoxic brain injury associated with each remain unknown. Our objective was to identify the distribution of anoxic brain injury after cardiac arrest, as measured with diffusion MRI, and to define the regional correlates of disorders of consciousness, EEG background suppression, and seizures. Methods We analyzed patients from a prospectively-maintained, single-center database of unresponsive patients who underwent diffusion-weighted MRI following cardiac arrest (n = 204). We classified each patient based on recovery of consciousness (command-following) before discharge, the most continuous EEG background (burst suppression versus continuous), and the presence or absence of seizures. Anoxic brain injury was measured using the apparent diffusion coefficient (ADC) signal. We identified abnormalities in ADC relative to control subjects without cardiac arrest (n = 48) and used voxel lesion symptom mapping to identify regional associations with disorders of consciousness, EEG background suppression, and seizures. We then used a bootstrapped lasso regression procedure to identify robust, multivariate regional associations with each clinical and EEG variable. Finally, using area under receiver operating characteristic curves, we then compared the classification ability of the strongest regional associations to that of brain-wide summary measures. Results Compared to control subjects, cardiac arrest patients demonstrated a reduction in the ADC signal that was most significant in the occipital lobes. Disorders of consciousness were associated with reduced ADC most prominently in the occipital lobes, but also in the basal ganglia, medial thalamus and cerebellar nuclei. Regional injury more accurately classified patients with disorders of consciousness than whole-brain injury. Background suppression mapped to a similar set of brain regions, but regional injury could no better classify patients than whole-brain measures. Seizures were less common in patients with more severe anoxic injury, particularly in those with injury to the lateral temporal white matter. Discussion Anoxic brain injury was most prevalent in posterior cerebral regions, and this regional pattern of injury was a better predictor of disorders of consciousness than whole-brain injury measures. EEG background suppression lacked a specific regional association, but patients with injury to the temporal lobe were less likely to have seizures. Collectively, our results suggest that the regional pattern of anoxic brain injury is relevant to the clinical and electrographic sequelae of cardiac arrest and may hold importance for prognosis.
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