Sam, Kevin

Introduction: Robust leptomeningeal collaterals protect the brain from ischemia, yet the determinants of poor collaterals have not been established. We aimed to identify predictors of poor collaterals in patients with large vessel occlusive stroke. Methods: Consecutive patients with large vessel occlusive stroke who underwent thrombectomy at 2 academic medical centers (derivation cohort/validation cohort) from 2012-2017 were included. Poor collaterals were defined as ≤50% filling on CT angiogram. Pre-specified predictors of poor collaterals were analyzed with adjusted logistic regression models: demographics (age, sex, race), risk factors (hypertension, diabetes, atrial fibrillation, smoking), hemodynamics (blood pressure, cardiac output, troponin), metabolic (hyperglycemia, hyponatremia, uremia), hematologic (anemia, leukocytosis, thrombocytosis) and neuroimaging evidence of chronic cerebral small-vessel disease and chronic steno-occlusive arterial disease. Results: Of the 248 total patients, poor collaterals were detected in 107 (43%). Mean age was 71±14y vs. 63±16y in patients with poor vs good collaterals, respectively (p<.001). There were 136 patients in the derivation cohort; 54 (48%) patients with poor collaterals. Multivariable modeling identified that older age (OR 1.8, p<.001), hyperglycemia (OR 2.4, p=.029) and white matter hyperintensities (WMH) (OR 6.1, p=.003) were independent predictors of poor collaterals in the derivation cohort. The validation cohort consisted of 136 patients; 53 (39%) had poor collaterals, of which older age (OR 1.4, p=.015), thrombocytosis (OR 24.0, p=.012), and WMH (OR 6.7, p=.018) were significant predictors of poor collaterals. Age and WMH were the only significant predictors of poor collaterals across the derivation and validation cohorts. When pooled the cohorts, older age (OR=1.5, p<.001), thrombocytosis (OR=7.6, p=.001) and WMH (OR=6.4, p<.001) were significant predictors of poor collaterals. Conclusions: We have identified that advanced age, WMH, and thrombocytosis are predictors of poor collaterals. Future studies to explore the effect of vascular aging on collateral therapeutics are indicated.

Background and Purpose— Cerebral small vessel disease (SVD) is associated with increased stroke risk and poor stroke outcomes. We aimed to evaluate whether chronic SVD burden is associated with poor recruitment of collaterals in large-vessel occlusive stroke. Methods— Consecutive patients with middle cerebral artery or internal carotid artery occlusion presenting within 6 hours after stroke symptom onset who underwent thrombectomy from 2012 to 2017 were included. The prespecified primary outcome was poor collateral flow, which was assessed on baseline computed tomographic angiography (poor, ≤50% filling; good, >50% filling). Markers of chronic SVD on brain magnetic resonance imaging were rated for the extent of white matter hyperintensities, enlarged perivascular spaces, chronic lacunar infarctions and cerebral microbleeds using the Standards for Reporting Vascular Changes on Neuroimaging criteria. Severity of SVD was quantified by adding the presence of each SVD feature, with a total possible score of 0 to 4; each SVD type was also evaluated separately. Multivariable logistic regression analyses were performed to evaluate the relationships between SVD and poor collaterals, with adjustment for potential confounders. Results— Of the 100 eligible patients, the mean age was 65±16 years, median National Institutes of Health Stroke Scale score was 15, and 68% had any SVD. Poor collaterals were observed in 46%, and those with SVD were more likely to have poor collaterals than patients without SVD (aOR, 1.9 [95% CI, 1.1–3.2]). Of the SVD types, poor collaterals were significantly associated with white matter hyperintensities (aOR, 2.9 per Fazekas increment [95% CI, 1.6–5.3]) but not with enlarged perivascular spaces (adjusted odds ratio [aOR], 1.3 [95% CI, 0.4–4.0]), lacunae (aOR, 2.1 [95% CI, 0.6–7.1]), or cerebral microbleeds (aOR, 2.1 [95% CI, 0.6–7.8]). Having a greater number of different SVD markers was associated with a higher odds of poor collaterals (crude trend P <0.001; adjusted P =0.056). There was a dose-dependent relationship between white matter hyperintensity burden and poor collaterals: adjusted odds of poor collaterals were 1.5, 3.0, and 9.7 across Fazekas scores of 1 to 3 ( P trend=0.015). No patient with an SVD score of 4 had good collaterals. Conclusions— Chronic cerebral SVD is associated with poor recruitment of collaterals in large vessel occlusive stroke. A prospective study to elucidate the potential mechanism of how SVD may impair the recruitment of collaterals is ongoing.

Introduction: Cerebral small-vessel disease (SVD) is associated with increased stroke risk and poor stroke outcomes. We aimed to evaluate if chronic SVD burden is associated with poor recruitment of collaterals in large-vessel occlusive stroke. Methods: Consecutive patients with MCA±ICA occlusion presenting within 6 hours after stroke symptoms onset from 2012- 2016 were included. Primary outcome was collateral flow, which was assessed on baseline CT-angiogram (poor ≤50% filling, good >50% filling). Markers of chronic SVD on brain MRI were rated for the presence of WMH (Fazekas scale 2-3), enlarged perivascular spaces (EPVS), chronic lacunae, and any cerebral microbleeds (CMB) using the STRIVE criteria. Severity of SVD was quantified by adding the presence of each SVD feature to a maximum score of 4. Multivariable logistic regression models were performed to evaluate the relationships between SVD and poor collaterals. Results: Of the 100 patients, the mean age was 65±16, median NIHSS was 15, and 68% had SVD. Poor collaterals were observed in 46%, and those with SVD were more likely to have poor collaterals (aOR 1.9; 95%CI 1.1-3.2) than patients without SVD. Of the SVD types, poor collaterals were associated with WMH (aOR 2.9 per Fazekas increment; 95%CI 1.6-5.3) but not EPVS (aOR 1.3; 0.4-4.0), lacunae (aOR 2.1; 0.6-7.1), or CMB (aOR 2.1; 0.6-7.8). Having a greater number of different SVD markers was associated with a higher odds of poor collaterals (crude trend p<.001; adjusted p=.056). There was a dose-dependent relationship between WMH burden and poor collaterals: adjusted odds of poor collaterals were 1.5, 3.0, and 9.7 across Fazekas scores of 1-3 (trends P=.015, Table). No patient with SVD score of 4 had good collaterals. Conclusions: Chronic cerebral small-vessel disease is associated with poor recruitment of collaterals in large-vessel occlusive stroke. A prospective study to elucidate the mechanism of how SVD may impair the recruitment of collaterals is ongoing.

Introduction: Robust leptomeningeal collaterals protect brain from ischemia, yet the determinants of poor collaterals remains unclear. We aimed to identify predictors of poor collaterals in patients with large-vessel occlusive stroke. Methods: We analyzed 112 consecutive patients with middle cerebral artery ± internal carotid artery occlusion from 2012-2016 who presented within 6 hours after stroke symptoms onset. Collaterals on baseline CT-angiogram (poor collaterals ≤50% filling, good collaterals >50% filling) were reviewed blinded to clinical data. Pre-specified predictors of poor collaterals were analyzed with adjusted logistic regression models: including known predictors (age, vascular risk factors and metabolic derangements) and hypothesized predictors (low cardiac output, elevated inflammatory markers, and imaging evidence for chronic cerebral small-vessel disease and chronic steno-occlusive arterial disease). Results: The mean age was 67± 16 years, there were 48% women, 57% white, and median NIHSS was 15 (IQR 11-20). Poor collaterals at baseline were detected in 48%. Multivariable modeling identified that age (aOR 1.8 per 10 years; 95% CI 1.3-2.6; p<0.001), black race (aOR 2.1; 95% CI 1.0-4.5; p=0.043), high blood glucose level (aOR 2.4 per 100 mg/dl; 95% CI 1.1-5.1; p=0.029), and high WMH burden (aOR 6.1; 95%CI 1.8-20.4; p=0.003) were independent predictors of poor collaterals. Associations between low cardiac output, elevated inflammatory markers, intracranial atherosclerosis and poor collaterals did not reach statistical significance (Table). Conclusions: We have identified that advanced age, black race, hyperglycemia, and white matter hyperintensities are predictors of poor collaterals. Independent replication study at another institution is ongoing to further explore the hypothesized predictors.