Abstract TP19: Role of Pial Collateral Flow in Acute Ischemic Stroke Outcomes

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Background and Purpose: Collateral flow can influence the pace and extent of evolution to irreversible tissue damage and thus have a significant impact on the clinical outcome of patients with acute ischemic stroke (AIS), including those treated with endovascular treatment (ET). Using prospectively collected data of a Stroke Registry, we explored the relationship between digital subtraction angiography (DSA) collateral status and clinical outcome of AIS patients with middle cerebral artery (MCA) occlusion treated with ET.Methods: We reviewed the data of all patients with acute MCA occlusion treated with ET within the past 5 years. Baseline DSA collaterals were classified as - no (0), poor (1), intermediate (2) and good (3). Clinical outcomes were assessed using the National Institute of Health Stroke Scale (NIHSS) at 24-48 hours and at the time of discharge. Multivariable regression analysis was done to evaluate association of DSA collateral score with the outcome. The regression model was adjusted for the age, baseline NIHSS, infusion of intravenous (IV) thrombolytic (tPA) and symptom-onset to angiographic recanalization time.Results: 50 patients with the MCA occlusion were treated with ET and 25 (50%) patients received IV tPA prior to ET. Median baseline NIHSS score was 19.5. Median time from the onset to IV tPA was 122 minutes and onset to angiographic recanalization was 277 minutes, respectively. Patients with DSA collateral score of 0, 1, 2 and 3 were 7 (15%), 21 (44%), 15 (31%) and 5 (10%), respectively. Every 1-point increase in the DSA collateral score was associated with 4.5-point reduction in NIHSS at 24-48 hours and 4.9-point reduction in NIHSS at discharge (Standard Error 1.4, p<0.01 for both).Conclusions: In the patients with AIS due to MCA occlusion, better collaterals on the DSA are independently associated with improved NIHSS at 24-48 hours after ET and at the time of discharge. This concept needs to be explored further in a larger dataset that will also include additional imaging parameters.

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