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

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.