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

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  • 1 School of Medicine, New York Medical College, Valhalla;
  • | 2 Department of Neurosurgery, Westchester Medical Center, Valhalla, New York;
  • | 3 Goodman Campbell Brain and Spine, Ascension St. Vincent Medical Center, Carmel, Indiana;
  • | 4 Department of Neurosurgery, Mount Sinai Hospital, New York, New York; and
  • | 5 Department of Neurosurgery, University of New Mexico, Albuquerque, New Mexico
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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 1.011.79; 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.

ABBREVIATIONS

AVM = arteriovenous malformation; cAVM = cerebral AVM; cAVM-VPM = cAVM–vasospasm predictive model; CHAID = chi-square automatic interaction detection; DCI = delayed cerebral ischemia; GCS = Glasgow Coma Scale; ICD-10-CM = International Classification of Diseases, Tenth Revision, Clinical Modification; IVH = intraventricular hemorrhage; NIS = National Inpatient Sample; ROC = receiver operating characteristic; SAH = subarachnoid hemorrhage.

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 1.011.79; 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.

Cerebral arteriovenous malformations (cAVMs) are congenital vascular lesions associated with high morbidity and mortality in young individuals as a consequence of rupture and subsequent hemorrhage.1,2 Arterial vasospasm, or transient constriction and occlusion of the cerebral vasculature,3 represents a common sequela of intracranial bleeds of various etiologies. Although cerebral vasospasm is well characterized in the setting of aneurysmal subarachnoid hemorrhage (SAH), comparatively little is known of this phenomenon following cAVM rupture. Given the propensity for vasospasm to progress to delayed cerebral ischemia and to portend poor outcome,3 it is imperative to further investigate this entity in cAVM, for which the existing body of literature is limited to case reports and small single-institution series.4–9 In this cross-sectional analysis we used population-level data to characterize the incidence and risk factors associated with the development of arterial vasospasm following cAVM rupture.

Methods

Data Source

The National Inpatient Sample (NIS), sponsored by the Healthcare Cost and Utilization Project (HCUP), reflects a 20% stratified cohort of hospitals in the United States and contains demographic, diagnostic, and procedural information for approximately 7,000,000 hospitalizations annually. More information about this database can be found at www.hcup-us.ahrq.gov. Given the public accessibility and de-identified nature of the information in this database, this study did not meet the requirements for institutional review board approval. For the same reason, patient consent was neither sought nor required.

Patient Selection and Cohort Development

Adult patients with primary admission diagnoses for ruptured cAVMs (International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] I60.8) were identified during the period of 2015 (fourth quarter, October through December) through 2019. Diagnosis of cerebral vasospasm (ICD-10-CM I67.84) was made in accordance with previous literature.10,11 To ensure that radiographic evidence was used for the identification of patients experiencing vasospasm, only patients receiving diagnostic cerebral angiograms (ICD-10-PCS B31XXXX) during their hospitalization were included in the analysis. Delayed cerebral ischemia (DCI) was defined as the concurrent coding of cerebral vasospasm and cerebral infarction due to nonthromboembolic and noniatrogenic causes (ICD-10-CM I63.5). Patients who were younger than 18 years and those who had hospitalizations associated with trauma or elective admissions were excluded from this analysis. Demographic characteristics (age, sex, admission Glasgow Coma Scale [GCS] score < 9, location of hemorrhage), comorbid conditions (diabetes mellitus, hypertension, obesity, congestive heart failure, chronic renal disease, hyperlipidemia, tobacco smoking, cocaine use, and alcohol use), and hospitalization events (leukocytosis, acute anemia, hyperglycemia, hyponatremia, hypernatremia, hypokalemia, hyperkalemia, fever, acute elevated blood pressure, hypovolemia, acute hypotension) were identified.

Clinical Endpoints

Cerebral vasospasm subsequent to cAVM rupture was the primary clinical endpoint of this analysis. Progression to DCI and clinical outcomes (routine discharge to home with or without services and in-hospital mortality) were evaluated as secondary endpoints.

Statistical Analysis

Complex samples statistical methods, incorporating stratum and cluster variables as well as hospitalization discharge weights, were performed to appropriately account for the sampling design employed by the NIS. Descriptive statistics were performed to compare characteristics between patients with and without progression to vasospasm following cAVM rupture. Dichotomous variables were assessed using Pearson’s chi-square test and presented as n (%), while a general linear model t-test was used to compare means of continuous parameters and reported with the standard error of the mean (SEM). Statistical significance was assessed at p < 0.05.

Multivariable logistic regression models composed of baseline clinical parameters and covariates associated with the hospitalization, respectively, identified significant independent associations with the development of vasospasm. A cAVM–vasospasm predictive model (cAVM-VPM) was subsequently constructed based on beta coefficients of significant variables (x) from multivariable analysis:
eq1

The discriminatory and predictive performance of this model was assessed through receiver operating characteristic (ROC) curve analysis. Sensitivity and specificity of the model were determined by the Youden index, the greatest combination of these parameters on the ROC curve. Decision tree analysis based on a chi-square automatic interaction detection (CHAID) algorithm with adjusted Bonferroni testing was performed to determine clinical covariates most predictive of correct classification of patients developing vasospasm. Significant parameters from previous multivariable analysis were used as candidate covariates for tree building.

Independent associations of vasospasm and DCI with clinical outcomes (routine discharge and in-hospital mortality) were evaluated through multivariable logistic regression analysis following adjustment for baseline clinical characteristics (age, sex, admission GCS score < 9, hemorrhage location, and comorbidities). Statistical significance was evaluated at p < 0.05 for multivariable comparisons and all analyses were performed with IBM SPSS version 26 software (IBM Corp.).

Results

Among 7215 cAVM patients identified, 935 developed vasospasm, corresponding to an overall incidence of 13.0%, and 110 of these patients (11.8%) subsequently progressed to DCI. Univariable comparisons of baseline characteristics and clinical variables as well as outcomes between patients developing and not developing vasospasm are shown in Table 1.

TABLE 1.

Comparison of baseline demographic and clinical characteristics, hospital course, and outcomes between ruptured cAVM patients with and without development of cerebral vasospasm

Pt Baseline DataTotal Cohort (n = 7215)Vasospasmp Value
Yes (n = 935, 13.0%)No (n = 6280, 87.0%)
Pt age, yrs55.5 ± 0.152.4 ± 0.455.9 ± 0.2<0.001*
Female sex3705 (51.4)590 (63.1)3115 (49.6)<0.001*
Admission GCS score <9405 (5.6)65 ± 7.0340 ± 5.40.036*
Intraparenchymal hemorrhage2035 (28.2)240 (25.7)1795 (28.6)0.065
SAH5180 (71.8)695 (74.3)4485 (71.4)0.065
IVH1165 (16.1)175 (18.7)990 (15.8)0.022*
Comorbid conditions
 Obesity1060 (14.7)110 (11.8)950 (15.1)0.007*
 Diabetes mellitus1290 (17.9)70 (7.5)1220 (19.4)<0.001*
 Hypertension4615 (64.0)625 (66.8)3990 (63.5)0.049*
 Congestive heart failure525 (7.3)70 (7.5)455 (7.2)0.791
 Chronic renal disease435 (6.0)30 (3.2)405 (6.4)<0.001*
 Hyperlipidemia2205 (30.6)240 (25.7)1965 (31.3)<0.001*
Substance use
 Tobacco smoking1160 (16.1)190 (20.3)970 (15.4)<0.001*
 Cocaine135 (1.9)20 (2.1)115 (1.8)0.517
 Alcohol400 (5.5)20 (2.1)380 (6.1)<0.001*
Lab & vital parameters
 Leukocytosis600 (8.3)120 (12.8)480 (7.6)<0.001*
 Acute anemia490 (6.8)70 (7.5)420 (6.7)0.365
 Hyperglycemia600 (8.3)85 (9.1)515 (8.2)0.358
 Hyponatremia1020 (14.1)195 (20.9)825 (13.1)<0.001*
 Hypernatremia860 (11.9)110 (11.8)750 (11.9)0.875
 Hypokalemia1290 (17.9)195 (20.9)1095 (17.4)0.011*
 Fever230 (3.2)45 (4.8)185 (2.9)0.002*
 Acute elevated blood pressure630 (8.7)85 (9.1)545 (8.7)0.677
 Hypovolemia235 (3.3)35 (3.7)200 (3.2)0.369
 Acute hypotension525 (7.3)100 (10.7)425 (6.8)<0.001*
Clinical outcomes
 Routine discharge3190 (44.2)425 (45.5)2765 (44.0)0.413
 In-hospital mortality480 (6.7)60 (6.4)420 (6.7)0.757

Pt = patient.

Values are presented as the number (%) of patients, compared using chi-square analysis, and continuous parameters are presented as the mean ± SEM, compared by t-test, unless otherwise indicated.

Denotes statistical significance evaluated at p < 0.05 for univariable comparisons.

Multivariable adjusted modeling identified the following baseline clinical covariates to be independently associated with the development of vasospasm (Table 2): age in years (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 GCS score < 9 (aOR 1.34, 95% CI 1.01–1.79; p = 0.045), intraventricular hemorrhage (IVH) (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]). Intraparenchymal (aOR 0.74, 95% CI 0.48–1.14; p = 0.168) and SAH (aOR 1.44, 95% CI 0.87–2.39; p = 0.157) were not associated with the development of vasospasm following multivariable adjustment.

TABLE 2.

Multivariable analysis—significant associations of clinical characteristics with development of cerebral vasospasm

Clinical CharacteristicBeta CoefficientaOR (95% CI)p Value
Age in yrs (by decade)−10.87 (0.83–0.92)<0.001*
Female sex+51.68 (1.45–1.95)<0.001*
Admission GCS score <9+31.34 (1.01–1.79)0.045*
IVH+61.87 (1.17–2.98)0.009*
Obesity−30.78 (0.63–0.97)0.025*
Hypertension+61.77 (1.49–2.08)<0.001*
Congestive heart failure+31.34 (1.01–1.78)0.043*
Tobacco smoking+41.48 (1.23–1.78)<0.001*
Leukocytosis+51.64 (1.32–2.04)<0.001*
Hyponatremia+51.66 (1.39–1.98)<0.001*
Acute hypotension+51.67 (1.31–2.11)<0.001*

Effect sizes of significant baseline clinical covariates and hospitalization events associated with the development of vasospasm presented as aORs with 95% CIs based on multivariable logistic regression analysis.

Denotes statistical significance evaluated at p < 0.05. Beta coefficients (rounded to the nearest whole number) from significant parameters were subsequently used to construct the cAVM-VPM.

The cAVM-VPM achieved an area under the curve of 0.65 (sensitivity 0.70, specificity 0.53, Youden index 0.23) (Fig. 1). A CHAID decision tree algorithm identified age 50–59 years (parent node, p < 0.001), hyponatremia, and leukocytosis as important determinants of vasospasm development that served as predictive nodes for the greatest rate of classification of patients with vasospasm (Supplementary Fig. 1). Following multivariable adjustment for baseline clinical characteristics, DCI, but not vasospasm alone, was independently associated with both 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) (Fig. 2).

FIG. 1.
FIG. 1.

ROC curve analysis for the cAVM-VPM.

FIG. 2.
FIG. 2.

Multivariable associations of vasospasm and DCI with routine discharge disposition and in-hospital mortality following cAVM rupture. Models adjusted for all baseline clinical characteristics. *Denotes statistical significance evaluated at p < 0.05.

Discussion

In this analysis, we used population-level data from the NIS to perform what is to our knowledge the first and only large-scale evaluation in the literature of cerebral vasospasm in the setting of cAVM rupture. In addition to establishing the incidence of occurrence and identifying common clinical risk factors, outcomes analysis demonstrated a more than two-fold increase in the risk of mortality in patients progressing to DCI. Our assessment of over 7000 patients with ruptured cAVM demonstrated a vasospasm incidence of 13.0%, which is consistent with previously documented incidence rates ranging from 2% to 31%,4,6,12 and is most congruent with the findings of a single-center study by Amuluru et al.,13 in which the authors documented an incidence of 13.9% following radiographic confirmation.

Our analysis showed a predisposition for vasospasm in younger patients and female patients and in patients with low GCS scores and hypertension. Previous studies have shown the inverse relationship between age and vasospasm risk in SAH patients.14 It has been hypothesized that the decrease in cerebral blood flow velocity as well as age-related atherosclerosis and vessel stiffening decreases the propensity for vasospasm to develop in the setting of vessel agitation.15–17 Female predominance in cases of cAVM has been previously shown, though this association is mechanistically unclear. Previous hypotheses have described a stimulating effect of estrogen on vascular tone.5,18 The GCS is a predictor of outcome in the setting of traumatic brain injury, and lower GCS has previously been associated with the development of vasospasm, likely due to elevated intracranial pressure, inflammation proliferation, and progression to cerebral edema.19 Additionally, the relationship between hypertension and vasospasm, while previously demonstrated, is not well understood.20 Potential reasons explored are the arteriopathy and decreased tolerance to cerebral ischemia characteristic of chronically hypertensive individuals.21,22 Elevated systolic blood pressure is a marker of left ventricular hypertrophy as well, which has been found to be associated with development of vasospasm in SAH.23 Interestingly, our analysis results suggested that obesity was protective against the development of vasospasm, which is consistent with previous literature published by this group of authors, who have identified a survival advantage in acute ischemic stroke patients presenting with elevated BMI.24,25 Finally, our analysis confirms that poor hemodynamic support10 is a significant contributor to the development of vasospasm, as both congestive heart failure and acute hypotension were independent predictors following multivariable analysis.

Consideration of hemorrhage location following cAVM rupture revealed an independent association between IVH only (and neither intraparenchymal hemorrhage nor SAH) and vasospasm in our analysis. It has been previously suggested that while vasospasm may result from bleeding following intracranial aneurysm rupture and the rapid and high-pressure accumulation of blood in the subarachnoid space, the rupture of a cAVM is a comparatively low-pressure event.13 The majority of cAVM bleeds either occur in the peripheral convexity or are deep-seated hemorrhages, with blood products less likely to collect in the basal cisterns and territory of the circle of Willis at the skull base. Consequently, cAVM bleeds tend to be less severe than hemorrhages associated with aneurysm rupture.6,13,26 Vasospasm in the absence of SAH is not novel and has previously been attributed to stretching as a result of the mass effect of the bleed or AVM nidus, as well as decreased CSF clearance.8,27 In fact, a study by Amuluru et al. found no significant association between SAH and the development of vasospasm or DCI in cAVM patients.13 For IVH, a number of mechanisms may explain its independent influence on vasospasm. Bleeds in the ventricular system may lead to circulation of heme products into the subarachnoid, where they function as disrupters of the vascular endothelium.5 Furthermore, increased hemorrhagic deposition in the ventricular system can lead to delayed CSF circulation and delay of removal of accumulated heme products, thus exacerbating the effects of the blood product on cerebrovascular endothelium.13,28

Leukocytosis and hyponatremia were identified as inflammatory markers associated with the development of vasospasm in our analysis. A previous analysis of biomarkers for post-SAH vasospasm was performed to investigate the relationship between fever and leukocytosis with constriction of the cerebral vasculature.10 The link between hyponatremia and vasospasm is multifactorial, but may be due to the syndrome of inappropriate antidiuretic hormone secretion (SIADH), the iatrogenic administration of hypertonic saline to treat cerebral edema, and hypercortisolemia in the setting of acute brain injury. Hyponatremia itself can be a cause of cerebral edema, which can lead to cerebrovascular irritation, and it has been shown that declining sodium levels served as an early biomarker of impending vasospasm.10,29,30 Leukocytosis has also been previously shown to be a biomarker for vasospasm, perhaps as a result of sympathetic activation caused by bleed severity and cerebrovascular agitation. Moreover, leukocytosis represents underlying inflammatory processes, consistent with the consideration of vasospasm and DCI as characteristically inflammatory events.10,31

While vasospasm was prevalent in our cohort, it was not an independent predictor of poor outcomes. Instead, progression to DCI (development of new cerebral infarction due to vasospasm) was highly predictive of mortality and worse discharge dispositions. This has been previously seen clinically and reported in the literature, with vasospasm often identified as an important early step in the pathophysiology of DCI in SAH.32 Vasospasm leads to restriction of blood flow and oxygenation to tissue supplied by the cerebral vasculature, but permanent and irreversible damage does not occur until ischemic brain injury develops, drawing an important distinction between vasospasm and DCI.32–34 For this reason, asymptomatic vasospasm poses a significantly lower threat to ruptured cAVM patients and may first be treated with observation, whereas severe symptomatic vasospasm may preferentially be treated aggressively for the purpose of preventing progression to DCI and worse outcomes.

The observational study design inherent to analysis of administrative registry data, in which all diagnoses and procedures are identified by billing codes, is the primary limitation of this investigation.35,36 These ICD codes do not carry a temporal qualifier, meaning that their occurrence with respect to vasospasm (before or after) cannot be ascertained, which limits conclusions regarding causality.11 The inability of the NIS to accurately identify vasospasm and DCI and to differentiate these entities from ischemia and infarction due to the mass effect from hematoma expansion, increased intracranial pressure, or iatrogenic causes may have led to overreporting and a potential type I error. Moreover, the degree, time, and location of arterial vasospasm could not be identified. Finally, established cAVM-specific severity covariates, such as the Spetzler-Martin grading scale and malformation size, are not captured by the NIS. Nonetheless, utilization of data from a large, multicenter national cohort represents a distinct strength of this analysis.

Conclusions

In this analysis we used large-scale population-level data from the NIS to investigate arterial vasospasm following cAVM rupture. Patient age, admission GCS score, IVH, leukocytosis, and hyponatremia were significant predictors of vasospasm, which was identified in 13% of patients. Clinical outcomes analysis determined that progression to DCI, but not vasospasm alone, was associated with higher mortality. Identification of incidence, risk factors, and clinical outcomes may offer guidance for the management of cAVM patients.

Disclosures

Dr. Dangayach reports receiving clinical or research support for the study described (includes equipment or material) from The Aneurysm and AVM Foundation (TAAF) and the American Academy of Neurology. Dr. Mayer reports being a consultant for Isorsia.

Author Contributions

Conception and design: Al-Mufti, Dicpinigaitis. Acquisition of data: Dicpinigaitis. Analysis and interpretation of data: Al-Mufti, Dicpinigaitis, Feldstein, Shapiro, Kamal, Amuluru, Pisapia, Dangayach, Liang, Bowers, Mayer, Gandhi. Drafting the article: all authors. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Statistical analysis: Dicpinigaitis. Administrative/technical/material support: Al-Mufti. Study supervision: Al-Mufti, Gandhi.

Supplemental Information

Online-Only Content

Supplemental material is available online.

References

  • 1

    Asif K, Leschke J, Lazzaro MA. Cerebral arteriovenous malformation diagnosis and management. Semin Neurol. 2013;33(5):468475.

  • 2

    Can A, Gross BA, Du R. The natural history of cerebral arteriovenous malformations. Handb Clin Neurol. 2017;143:1524.

  • 3

    Li K, Barras CD, Chandra RV, et al. A review of the management of cerebral vasospasm after aneurysmal subarachnoid hemorrhage. World Neurosurg.2019;126:513527.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Maeda K, Kurita H, Nakamura T, et al. Occurrence of severe vasospasm following intraventricular hemorrhage from an arteriovenous malformation. Report of two cases. J Neurosurg. 1997;87(3):436439.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Yokobori S, Watanabe A, Nakae R, et al. Cerebral vasospasms after intraventricular hemorrhage from an arteriovenous malformation: case report. Neurol Med Chir (Tokyo). 2010;50(4):320323.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Pendharkar AV, Guzman R, Dodd R, Cornfield D, Edwards MS. Successful treatment of severe cerebral vasospasm following hemorrhage of an arteriovenous malformation. Case report. J Neurosurg Pediatr. 2009;4(3):266269.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Gerard E, Frontera JA, Wright CB. Vasospasm and cerebral infarction following isolated intraventricular hemorrhage. Neurocrit Care. 2007;7(3):257259.

  • 8

    Kobayashi M, Takayama H, Mihara B, Kawase T. Severe vasospasm caused by repeated intraventricular haemorrhage from small arteriovenous malformation. Acta Neurochir (Wien). 2002;144(4):405406.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9

    Parkinson D, Bachers G. Arteriovenous malformations. Summary of 100 consecutive supratentorial cases. J Neurosurg. 1980;53(3):285299.

  • 10

    Rumalla K, Lin M, Ding L, et al. Risk factors for cerebral vasospasm in aneurysmal subarachnoid hemorrhage: a population-based study of 8346 patients. World Neurosurg.2021;145:e233e241.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Dicpinigaitis AJ, Feldstein E, Damodara N, et al. Development of cerebral vasospasm following traumatic intracranial hemorrhage: incidence, risk factors, and clinical outcomes. Neurosurg Focus. 2022;52(3):E14.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Matsumori K, Asahi S, Nakayama K, Miyasaka Y, Beppu T. Cerebral vasospasm following subarachnoid hemorrhage in arteriovenous malformation. Article in Japanese. No Shinkei Geka. 1983;11(8):829834.

    • Search Google Scholar
    • Export Citation
  • 13

    Amuluru K, Al-Mufti F, Romero CE, Gandhi CD. Isolated intraventricular hemorrhage associated with cerebral vasospasm and delayed cerebral ischemia following arteriovenous malformation rupture. Intervent Neurol. 2018;7(6):479489.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Torbey MT, Hauser TK, Bhardwaj A, et al. Effect of age on cerebral blood flow velocity and incidence of vasospasm after aneurysmal subarachnoid hemorrhage. Stroke. 2001;32(9):20052011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15

    Melamed E, Lavy S, Bentin S, Cooper G, Rinot Y. Reduction in regional cerebral blood flow during normal aging in man. Stroke. 1980;11(1):3135.

  • 16

    Kusunoki K, Oka Y, Saito M, et al. Changes in visibility of intracranial arteries on MRA with normal ageing. Neuroradiology. 1999;41(11):813819.

  • 17

    Baker AB, Iannone A. Cerebrovascular disease. I. The large arteries of the circle of Willis. Neurology. 1959;9(5):321332.

  • 18

    Carrera E, Schmidt JM, Oddo M, et al. Transcranial Doppler for predicting delayed cerebral ischemia after subarachnoid hemorrhage. Neurosurgery. 2009;65(2):316324.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19

    Al-Mufti F, Amuluru K, Lander M, et al. Low Glasgow Coma Score in traumatic intracranial hemorrhage predicts development of cerebral vasospasm. World Neurosurg.2018;120:e68e71.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20

    Inagawa T, Yahara K, Ohbayashi N. Risk factors associated with cerebral vasospasm following aneurysmal subarachnoid hemorrhage. Neurol Med Chir (Tokyo). 2014;54(6):465473.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21

    Ohman J, Servo A, Heiskanen O. Effect of intrathecal fibrinolytic therapy on clot lysis and vasospasm in patients with aneurysmal subarachnoid hemorrhage. J Neurosurg. 1991;75(2):197201.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Lasner TM, Weil RJ, Riina HA, et al. Cigarette smoking-induced increase in the risk of symptomatic vasospasm after aneurysmal subarachnoid hemorrhage. J Neurosurg. 1997;87(3):381384.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23

    Mayer SA, Lin J, Homma S, et al. Myocardial injury and left ventricular performance after subarachnoid hemorrhage. Stroke. 1999;30(4):780786.

  • 24

    Dicpinigaitis AJ, Palumbo KE, Gandhi CD, et al. Association of elevated body mass index with functional outcome and mortality following acute ischemic stroke: the obesity paradox revisited. Cerebrovasc Dis. Published online February 14, 2022.doi: 10.1159/000521513

    • Search Google Scholar
    • Export Citation
  • 25

    Lapow JM, Dicpinigaitis AJ, Pammal RS, et al. Obstructive sleep apnea confers lower mortality risk in acute ischemic stroke patients treated with endovascular thrombectomy: National Inpatient Sample analysis 2010-2018. J Neurointerv Surg. Published online December 20, 2021. doi: 10.1136/neurintsurg-2021-018161

    • Search Google Scholar
    • Export Citation
  • 26

    Zubkov AY, Ogihara K, Tumu P, et al. Bloody cerebrospinal fluid alters contractility of cultured arteries. Neurol Res. 1999;21(6):553558.

  • 27

    Perrein A, Petry L, Reis A, Baumann A, Mertes P, Audibert G. Cerebral vasospasm after traumatic brain injury: an update. Minerva Anestesiol. 2015;81(11):12191228.

    • Search Google Scholar
    • Export Citation
  • 28

    Claassen J, Bernardini GL, Kreiter K, et al. Effect of cisternal and ventricular blood on risk of delayed cerebral ischemia after subarachnoid hemorrhage: the Fisher scale revisited. Stroke. 2001;32(9):20122020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29

    Uozumi Y, Mizobe T, Miyamoto H, et al. Decreased serum sodium levels predict symptomatic vasospasm in patients with subarachnoid hemorrhage. J Clin Neurosci. 2017;46:118123.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30

    Chandy D, Sy R, Aronow WS, Lee WN, Maguire G, Murali R. Hyponatremia and cerebrovascular spasm in aneurysmal subarachnoid hemorrhage. Neurol India. 2006;54(3):273275.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31

    Bambakidis NC, Selman WR. Vasospasm. J Neurosurg. 2011;114(4):932934.

  • 32

    Dankbaar JW, Rijsdijk M, van der Schaaf IC, Velthuis BK, Wermer MJ, Rinkel GJ. Relationship between vasospasm, cerebral perfusion, and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Neuroradiology. 2009;51(12):813819.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33

    Rijsdijk M, van der Schaaf IC, Velthuis BK, Wermer MJ, Rinkel GJ. Global and focal cerebral perfusion after aneurysmal subarachnoid hemorrhage in relation with delayed cerebral ischemia. Neuroradiology. 2008;50(9):813820.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34

    Weidauer S, Vatter H, Beck J, et al. Focal laminar cortical infarcts following aneurysmal subarachnoid haemorrhage. Neuroradiology. 2008;50(1):18.

  • 35

    Dicpinigaitis AJ, Gandhi CD, Shah SP, et al. Endovascular thrombectomy with and without preceding intravenous thrombolysis for treatment of large vessel anterior circulation stroke: a cross-sectional analysis of 50,000 patients. J Neurol Sci. 2022;434:120168.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36

    Dicpinigaitis AJ, Kazim SF, Schmidt MH, et al. Association of baseline frailty status and age with postoperative morbidity and mortality following intracranial meningioma resection. J Neurooncol. 2021;155(1):4552.

    • Crossref
    • Search Google Scholar
    • Export Citation

Supplementary Materials

Illustration from Agosti et al. (E5). Used with permission of Mayo Foundation for Medical Education and Research. All rights reserved.

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    ROC curve analysis for the cAVM-VPM.

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    Multivariable associations of vasospasm and DCI with routine discharge disposition and in-hospital mortality following cAVM rupture. Models adjusted for all baseline clinical characteristics. *Denotes statistical significance evaluated at p < 0.05.

  • 1

    Asif K, Leschke J, Lazzaro MA. Cerebral arteriovenous malformation diagnosis and management. Semin Neurol. 2013;33(5):468475.

  • 2

    Can A, Gross BA, Du R. The natural history of cerebral arteriovenous malformations. Handb Clin Neurol. 2017;143:1524.

  • 3

    Li K, Barras CD, Chandra RV, et al. A review of the management of cerebral vasospasm after aneurysmal subarachnoid hemorrhage. World Neurosurg.2019;126:513527.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Maeda K, Kurita H, Nakamura T, et al. Occurrence of severe vasospasm following intraventricular hemorrhage from an arteriovenous malformation. Report of two cases. J Neurosurg. 1997;87(3):436439.

    • Search Google Scholar
    • Export Citation
  • 5

    Yokobori S, Watanabe A, Nakae R, et al. Cerebral vasospasms after intraventricular hemorrhage from an arteriovenous malformation: case report. Neurol Med Chir (Tokyo). 2010;50(4):320323.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6

    Pendharkar AV, Guzman R, Dodd R, Cornfield D, Edwards MS. Successful treatment of severe cerebral vasospasm following hemorrhage of an arteriovenous malformation. Case report. J Neurosurg Pediatr. 2009;4(3):266269.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7

    Gerard E, Frontera JA, Wright CB. Vasospasm and cerebral infarction following isolated intraventricular hemorrhage. Neurocrit Care. 2007;7(3):257259.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8

    Kobayashi M, Takayama H, Mihara B, Kawase T. Severe vasospasm caused by repeated intraventricular haemorrhage from small arteriovenous malformation. Acta Neurochir (Wien). 2002;144(4):405406.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9

    Parkinson D, Bachers G. Arteriovenous malformations. Summary of 100 consecutive supratentorial cases. J Neurosurg. 1980;53(3):285299.

  • 10

    Rumalla K, Lin M, Ding L, et al. Risk factors for cerebral vasospasm in aneurysmal subarachnoid hemorrhage: a population-based study of 8346 patients. World Neurosurg.2021;145:e233e241.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11

    Dicpinigaitis AJ, Feldstein E, Damodara N, et al. Development of cerebral vasospasm following traumatic intracranial hemorrhage: incidence, risk factors, and clinical outcomes. Neurosurg Focus. 2022;52(3):E14.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Matsumori K, Asahi S, Nakayama K, Miyasaka Y, Beppu T. Cerebral vasospasm following subarachnoid hemorrhage in arteriovenous malformation. Article in Japanese. No Shinkei Geka. 1983;11(8):829834.

    • Search Google Scholar
    • Export Citation
  • 13

    Amuluru K, Al-Mufti F, Romero CE, Gandhi CD. Isolated intraventricular hemorrhage associated with cerebral vasospasm and delayed cerebral ischemia following arteriovenous malformation rupture. Intervent Neurol. 2018;7(6):479489.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Torbey MT, Hauser TK, Bhardwaj A, et al. Effect of age on cerebral blood flow velocity and incidence of vasospasm after aneurysmal subarachnoid hemorrhage. Stroke. 2001;32(9):20052011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15

    Melamed E, Lavy S, Bentin S, Cooper G, Rinot Y. Reduction in regional cerebral blood flow during normal aging in man. Stroke. 1980;11(1):3135.

  • 16

    Kusunoki K, Oka Y, Saito M, et al. Changes in visibility of intracranial arteries on MRA with normal ageing. Neuroradiology. 1999;41(11):813819.

  • 17

    Baker AB, Iannone A. Cerebrovascular disease. I. The large arteries of the circle of Willis. Neurology. 1959;9(5):321332.

  • 18

    Carrera E, Schmidt JM, Oddo M, et al. Transcranial Doppler for predicting delayed cerebral ischemia after subarachnoid hemorrhage. Neurosurgery. 2009;65(2):316324.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19

    Al-Mufti F, Amuluru K, Lander M, et al. Low Glasgow Coma Score in traumatic intracranial hemorrhage predicts development of cerebral vasospasm. World Neurosurg.2018;120:e68e71.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20

    Inagawa T, Yahara K, Ohbayashi N. Risk factors associated with cerebral vasospasm following aneurysmal subarachnoid hemorrhage. Neurol Med Chir (Tokyo). 2014;54(6):465473.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21

    Ohman J, Servo A, Heiskanen O. Effect of intrathecal fibrinolytic therapy on clot lysis and vasospasm in patients with aneurysmal subarachnoid hemorrhage. J Neurosurg. 1991;75(2):197201.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Lasner TM, Weil RJ, Riina HA, et al. Cigarette smoking-induced increase in the risk of symptomatic vasospasm after aneurysmal subarachnoid hemorrhage. J Neurosurg. 1997;87(3):381384.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23

    Mayer SA, Lin J, Homma S, et al. Myocardial injury and left ventricular performance after subarachnoid hemorrhage. Stroke. 1999;30(4):780786.

  • 24

    Dicpinigaitis AJ, Palumbo KE, Gandhi CD, et al. Association of elevated body mass index with functional outcome and mortality following acute ischemic stroke: the obesity paradox revisited. Cerebrovasc Dis. Published online February 14, 2022.doi: 10.1159/000521513

    • Search Google Scholar
    • Export Citation
  • 25

    Lapow JM, Dicpinigaitis AJ, Pammal RS, et al. Obstructive sleep apnea confers lower mortality risk in acute ischemic stroke patients treated with endovascular thrombectomy: National Inpatient Sample analysis 2010-2018. J Neurointerv Surg. Published online December 20, 2021. doi: 10.1136/neurintsurg-2021-018161

    • Search Google Scholar
    • Export Citation
  • 26

    Zubkov AY, Ogihara K, Tumu P, et al. Bloody cerebrospinal fluid alters contractility of cultured arteries. Neurol Res. 1999;21(6):553558.

  • 27

    Perrein A, Petry L, Reis A, Baumann A, Mertes P, Audibert G. Cerebral vasospasm after traumatic brain injury: an update. Minerva Anestesiol. 2015;81(11):12191228.

    • Search Google Scholar
    • Export Citation
  • 28

    Claassen J, Bernardini GL, Kreiter K, et al. Effect of cisternal and ventricular blood on risk of delayed cerebral ischemia after subarachnoid hemorrhage: the Fisher scale revisited. Stroke. 2001;32(9):20122020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29

    Uozumi Y, Mizobe T, Miyamoto H, et al. Decreased serum sodium levels predict symptomatic vasospasm in patients with subarachnoid hemorrhage. J Clin Neurosci. 2017;46:118123.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30

    Chandy D, Sy R, Aronow WS, Lee WN, Maguire G, Murali R. Hyponatremia and cerebrovascular spasm in aneurysmal subarachnoid hemorrhage. Neurol India. 2006;54(3):273275.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31

    Bambakidis NC, Selman WR. Vasospasm. J Neurosurg. 2011;114(4):932934.

  • 32

    Dankbaar JW, Rijsdijk M, van der Schaaf IC, Velthuis BK, Wermer MJ, Rinkel GJ. Relationship between vasospasm, cerebral perfusion, and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Neuroradiology. 2009;51(12):813819.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33

    Rijsdijk M, van der Schaaf IC, Velthuis BK, Wermer MJ, Rinkel GJ. Global and focal cerebral perfusion after aneurysmal subarachnoid hemorrhage in relation with delayed cerebral ischemia. Neuroradiology. 2008;50(9):813820.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34

    Weidauer S, Vatter H, Beck J, et al. Focal laminar cortical infarcts following aneurysmal subarachnoid haemorrhage. Neuroradiology. 2008;50(1):18.

  • 35

    Dicpinigaitis AJ, Gandhi CD, Shah SP, et al. Endovascular thrombectomy with and without preceding intravenous thrombolysis for treatment of large vessel anterior circulation stroke: a cross-sectional analysis of 50,000 patients. J Neurol Sci. 2022;434:120168.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36

    Dicpinigaitis AJ, Kazim SF, Schmidt MH, et al. Association of baseline frailty status and age with postoperative morbidity and mortality following intracranial meningioma resection. J Neurooncol. 2021;155(1):4552.

    • Crossref
    • Search Google Scholar
    • Export Citation

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