Cerebral vasospasm following arteriovenous malformation rupture: a population-based cross-sectional study

Abstract

Objective: Studies examining the risk factors and clinical outcomes of arterial vasospasm secondary to cerebral arteriovenous malformation (cAVM) rupture are scarce in the literature. The authors used a population-based national registry to investigate this largely unexamined clinical entity.

Methods: Admissions for adult patients with cAVM ruptures were identified in the National Inpatient Sample during the period from 2015 to 2019. Complex samples multivariable logistic regression and chi-square automatic interaction detection (CHAID) decision tree analyses were performed to identify significant associations between clinical covariates and the development of vasospasm, and a cAVM-vasospasm predictive model (cAVM-VPM) was generated based on the effect sizes of these parameters.

Results: Among 7215 cAVM patients identified, 935 developed vasospasm, corresponding to an incidence rate of 13.0%; 110 of these patients (11.8%) subsequently progressed to delayed cerebral ischemia (DCI). Multivariable adjusted modeling identified the following baseline clinical covariates: decreasing age by decade (adjusted odds ratio [aOR] 0.87, 95% CI 0.83-0.92; p < 0.001), female sex (aOR 1.68, 95% CI 1.45-1.95; p < 0.001), admission Glasgow Coma Scale score < 9 (aOR 1.34, 95% CI 1.01-1.79; p = 0.045), intraventricular hemorrhage (aOR 1.87, 95% CI 1.17-2.98; p = 0.009), hypertension (aOR 1.77, 95% CI 1.50-2.08; p < 0.001), obesity (aOR 0.68, 95% CI 0.55-0.84; p < 0.001), congestive heart failure (aOR 1.34, 95% CI 1.01-1.78; p = 0.043), tobacco smoking (aOR 1.48, 95% CI 1.23-1.78; p < 0.019), and hospitalization events (leukocytosis [aOR 1.64, 95% CI 1.32-2.04; p < 0.001], hyponatremia [aOR 1.66, 95% CI 1.39-1.98; p < 0.001], and acute hypotension [aOR 1.67, 95% CI 1.31-2.11; p < 0.001]) independently associated with the development of vasospasm. Intraparenchymal and subarachnoid hemorrhage were not associated with the development of vasospasm following multivariable adjustment. Among significant associations, a CHAID decision tree algorithm identified age 50-59 years (parent node), hyponatremia, and leukocytosis as important determinants of vasospasm development. The cAVM-VPM achieved an area under the curve of 0.65 (sensitivity 0.70, specificity 0.53). Progression to DCI, but not vasospasm alone, was independently associated with in-hospital mortality (aOR 2.35, 95% CI 1.29-4.31; p = 0.016) and lower likelihood of routine discharge (aOR 0.62, 95% CI 0.41-0.96; p = 0.031).

Conclusions: This large-scale assessment of vasospasm in cAVM identifies common clinical risk factors and establishes progression to DCI as a predictor of poor neurological outcomes.

Keywords: arteriovenous malformation; database; decision tree analysis; delayed cerebral ischemia; intraventricular hemorrhage; predictive model; subarachnoid hemorrhage; vasospasm.