BackgroundWhile diffuse atherosclerotic disease affecting the posterior circulation has been described extensively, the prevalence, natural history and angiographic characteristics of isolated symptomatic basilar artery stenosis (ISBAS) remain unknown.MethodsWe reviewed our prospective institutional database to identify patients with ≥50% symptomatic basilar artery (BA) stenosis without significant atherosclerotic burden in the vertebral or posterior cerebral arteries. Stroke mechanism, collateral circulation, and degree and length of stenosis were analysed. The primary outcome was time from index event to new transient ischaemic attack (TIA), acute ischaemic stroke (AIS) or death. Other outcome variables included modified Rankin Scale (mRS) score on discharge and last follow-up.ResultsOf 6369 patients with AIS/TIA, 91 (1.43%) had ISBAS. Seventy-three (80.2%) patients presented with AIS and 18 (19.8%) with TIA. Twenty-nine (31.9%) were women and the median age was 66.8±13.6 years. The mean follow-up time was 2.7 years. The most common stroke mechanism was artery-to-artery thromboembolism (45.2%), followed by perforator occlusion (28.7%) and flow-dependent/hypoperfusion (15.1%). The percentage of stenosis was lower in patients who had favourable outcome compared with those with mRS 3–6 on discharge (78.3±14.3 vs 86.9±14.5, p=0.007). Kaplan-Meier curves showed higher recurrence/death rates in patients with ≥80% stenosis, mid-basilar location and poor collateral circulation. Approximately 13% of patients with ISBAS presented with complete BA occlusion.ConclusionISBAS is an uncommon (1.43%) cause of TIA and AIS. Men in their 60s are mostly affected, and artery-to-artery embolism is the most common stroke mechanism. Mid-basilar location, ≥80% stenosis and poor collateral circulation are important factors associated with worse prognosis.

Background: Contrast-induced neurotoxicity (CIN) is a rare complication of neurointerventional procedures and its understanding remains limited. We evaluated the association of CIN with systemic hemodynamics in patients undergoing neuroendovascular interventions. Methods: We conducted a 1:2 matched case-control study from a prospectively collected database of 2510 neurointerventional patients. We defined CIN as new neurological deficits presented ≤24 h post-operation after excluding other possible etiologies. We obtained demographic, clinical and imaging data, and baseline and intraprocedural blood pressures (BP) from medical records. The area between baseline and intraprocedural BP was used to measure sustained variability of BP over time. A generalized linear mixed model and generalized estimating equation were used to analyze the BP difference between groups over time. Results: We evaluated 11 CIN cases and 22 controls. 2746 and 5837 min of continued BP data were analyzed for cases and controls, respectively. CIN cases had higher measurements and greater variability for: Systolic BP (SBP) [median 125 (IQR:121-147) vs. 114 (IQR:107-124) mmHg], median area above baseline [median 350 (IQR:25-1328) vs. 52 (IQR:0-293) mmHg*minutes] and mean arterial pressure (MAP) [median 85 (IQR:79-98) vs. 80 (IQR:74-89) mmHg]. CIN cases demonstrated a significant mean increase in SBP and MAP of 23.41 mmHg (p < 0.01) and 13.79 mmHg (p < 0.01) when compared to controls, respectively, over the perioperative time. Conclusion: Sustained hypertension and high BP variability may contribute to the pathophysiology of CIN. Acute hypertension can increase blood-brain barrier permeability and potentially allow contrast to leak into the brain parenchyma causing direct toxicity and CIN symptoms.

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Cross validation is commonly used for selecting tuning parameters in penalized regression, but its use in penalized Cox regression models has received relatively little attention in the literature. Due to its partial likelihood construction, carrying out cross validation for Cox models is not straightforward, and there are several potential approaches for implementation. Here, we propose two new cross-validation methods for Cox regression and compare them to approaches that have been proposed elsewhere. Our proposed approach of cross-validating the linear predictors seems to offer an attractive balance of performance and numerical stability. We illustrate these advantages using simulated data as well as using them to analyze data from a high-dimensional study of survival in lung cancer patients.