Public Health and Cost Benefits of Successful Reperfusion After Thrombectomy for Stroke

Background and Purpose- The benefit that endovascular thrombectomy offers to patients with stroke with large vessel occlusions depends strongly on reperfusion grade as defined by the expanded Thrombolysis in Cerebral Infarction (eTICI) scale. Our aim was to determine the lifetime health and cost consequences of the quality of reperfusion for patients, healthcare systems, and society. Methods- A Markov model estimated lifetime quality-adjusted life years (QALY) and lifetime costs of endovascular thrombectomy-treated patients with stroke based on eTICI grades. The analysis was performed over a lifetime horizon in a United States setting, adopting healthcare and societal perspectives. The reference case analysis was conducted for stroke at 65 years of age. National health and cost consequences of improved eTICI 2c/3 reperfusion rates were estimated. Input parameters were based on best available evidence. Results- Lifetime QALYs increased for every grade of improved reperfusion (median QALYs for eTICI 0/1: 2.62; eTICI 2a: 3.46; eTICI 2b: 5.42; eTICI 2c: 5.99; eTICI 3: 6.73). Achieving eTICI 3 over eTICI 2b reperfusion resulted on average in 1.31 incremental QALYs as well as healthcare and societal cost savings of $10 327 and$20 224 per patient. A 10% increase in the eTICI 2c/3 reperfusion rate of all annually endovascular thrombectomy-treated patients with stroke in the United States is estimated to yield additional 3656 QALYs and save $21.0 million and$36.8 million for the healthcare system and society, respectively. Conclusions- Improved reperfusion grants patients with stroke additional QALYs and leads to long-term cost savings. Procedural strategies to achieve complete reperfusion should be assessed for safety and feasibility, even when initial reperfusion seems to be adequate

Effect of atrial fibrillation on endovascular thrombectomy for acute ischemic stroke. A meta-analysis of individual patient data from six randomised trials: Results from the HERMES collaboration

Background: Atrial fibrillation is an important risk factor for ischemic stroke, and is associated with an increased risk of poor outcome after ischemic stroke. Endovascular thrombectomy is safe and effective in acute ischemic stroke patients with large vessel occlusion of the anterior circulation. This meta-analysis aims to investigate whether there is an interaction between atrial fibrillation and treatment effect of endovascular thrombectomy, and secondarily whether atrial fibrillation is associated with worse outcome in patients with ischemic stroke due to large vessel occlusion. Methods: Individual patient data were from six of the recent randomised clinical trials (MR CLEAN, EXTEND-IA, REVASCAT, SWIFT PRIME, ESCAPE, PISTE) in which endovascular thrombectomy plus standard care was compared to standard care alone. Primary outcome measure was the shift on the modified Rankin scale (mRS) at 90 days. Secondary outcomes were functional independence (mRS 0–2) at 90 days, National Institutes of Health Stroke Scale score at 24 h, symptomatic intracranial hemorrhage and mortality at 90 days. The primary effect parameter was the adjusted common odds ratio, estimated with ordinal logistic regression (shift analysis); treatment effect modification of atrial fibrillation was assessed with a multiplicative interaction term. Results: Among 1351 patients, 447 p

Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks

Background and purpose: Infarct volume is a valuable outcome measure in treatment trials of acute ischemic stroke and is strongly associated with functional outcome. Its manual volumetric assessment is, however, too demanding to be implemented in clinical practice. Objective: To assess the value of convolutional neural networks (CNNs) in the automatic segmentation of infarct volume in follow-up CT images in a large population of patients with acute ischemic stroke. Materials and methods: We included CT images of 1026 patients from a large pooling of patients with acute ischemic stroke. A reference standard for the infarct segmentation was generated by manual delineation. We introduce three CNN models for the segmentati

Frameless stereotactic aspiration and thrombolysis of deep intracerebral hemorrhage is associated with reduction of hemorrhage volume and neurological improvement

Introduction: This ia a phase-2 safety trial to demonstrate the ability of frameless stereotactic aspiration and thrombolysis of ICH to safely remove blood. Methods: Patients with ICH in the deep basal ganglia and internal capsule of >5 cc volume were consented to undergo computed tomographic imaging for frameless stereotactic guidance registration. Using the frameless stereotactic (CT) guidance, a 4-mm diameter catheter was inserted into the body of the hematoma using a frontal burr hole approach. The catheter was aspirated and then flushed with saline and aspirated to remove unclotted blood. After a confirmatory CT scan to localize the catheter, 1 mg of recombinant tissue plasminogen activator (t-PA) was infused into the clot, permitted to bathe the clot for 30 minutes, and then drained into a closed circuit collection system. t-PA was infused every 8 hours for 48 hours. A follow up CT scan was obtained at 48 hours. Results: 28 patients with ICH (mean age 67.1) were admitted and underwent the procedure. Mean initial ICH volume was 54.6 cc ± 37.8. Mean time from onset to aspiration was 44 hours (range 7–180). Mean initial NIH Stroke scale (NIHSS) score was 24 (range 15–33). Compared with initial CT scan, there was a mean reduction of ICH volume by 77 ± 13% on final CT scan (p<0.0002). Compared with initial NIHSS, the discharge mean NIHSS (16 ± 6) was significantly improved (p<0.001). There were no infectious, hemodynamic or neurologic complications. There were no episodes of symptomatic hemorrhagic enlargement and one case of asymptomatic bleeding along the catheter tract. Conclusion: Frameless stereotactic aspiration and thrombolysis (FAST) of deep spontaneous intracerebral hemorrhage is a safe therapy that is associated with reduction in ICH volume, early improvement in NIHSS and potentially could be used to improve outcome

Predicting discharge mortality after acute ischemic stroke using balanced data.

Several models have been developed to predict stroke outcomes (e.g., stroke mortality, patient dependence, etc.) in recent decades. However, there is little discussion regarding the problem of between-class imbalance in stroke datasets, which leads to prediction bias and decreased performance. In this paper, we demonstrate the use of the Synthetic Minority Over-sampling Technique to overcome such problems. We also compare state of the art machine learning methods and construct a six-variable support vector machine (SVM) model to predict stroke mortality at discharge. Finally, we discuss how the identification of a reduced feature set allowed us to identify additional cases in our research database for validation testing. Our classifier achieved a c-statistic of 0.865 on the cross-validated dataset, demonstrating good classification performance using a reduced set of variables

Abstract TP50: Efficacy of Stent-retriever Thrombectomy in MRI Vs. CT Perfusion Selected Patients in SWIFT PRIME

Background: The majority of patients enrolled in SWIFT PRIME had CT perfusion imaging immediately prior to randomization; 34 patients were randomized following a diffusion and perfusion MRI. Methods: Patients with MCA (M1) and distal carotid occlusions were randomized to treatment with tPA alone vs. tPA + Solitaire stent retriever. The primary outcome was the distribution of the mRS at 90 days. The same automated software (RAPID) was used for both MRI and CTP patients to identify patients with the Target mismatch profile for enrollment. Results: MRI selection was performed in 34 patients; CTP in 139. Mean age was 71 years (MRI) vs. 68 years (CTP), p=0.08; baseline NIHSS was 17 in both groups. Target mismatch profile was present in 95% (MRI) vs. 83% (CTP), p=0.3. Median time from ER arrival to randomization was 69 min (MRI) vs. 67 min (CTP), p=0.61. A higher percentage of the MRI group was transferred from an outside hospital (59% vs. 35%, p=0.02) and therefore the time from stroke onset to randomization was longer in the MRI group (236 minutes vs. 179 minutes, p=0.003.) Baseline median ischemic core volumes were similar in the MRI vs. CTP group (7 ml vs. 5 ml); baseline perfusion lesions were larger in the MRI group (133 ml vs. 97 ml, P=0.01) Reperfusion rates (> 90%/TICI 3) did not differ in the Solitaire treated patients in the MRI (94%) vs. CTP (85%) groups, p=0.7. The primary efficacy analysis (distribution of mRS at 90 days) demonstrated a statistically significant benefit in both the MRI (p=0.02) and CTP subgroups (p=0.01). Among MRI selected patients, mRS 0-2 at 90 days occurred in 63% of the Solitaire group vs. 33% of the tPA alone group (ARR 30%, p=0.17) and infarct growth was reduced (17 ml vs. 50 ml, p=0.089). CTP selected patients had mRS 0-2 rates at 90 days of 60% in the Solitaire group vs. 40% tPA alone (ARR 20%, p=0.025) and a reduction in infarct growth (14 vs. 27 ml, p=0.047). Conclusions: Although MRI selected patients in SWIFT PRIME were slightly older and treated longer after symptom onset, they demonstrated a statistically significant benefit on the primary efficacy endpoint. Reductions in infarct growth and rates of favorable clinical outcomes in the MR subgroup were also comparable to those seen in the CT perfusion subgroup

Multiparametric Magnetic Resonance Imaging for Prediction of Parenchymal Hemorrhage in Acute Ischemic Stroke After Reperfusion Therapy.

Background and purposePatients with acute ischemic stroke are at increased risk of developing parenchymal hemorrhage (PH), particularly in the setting of reperfusion therapies. We have developed a predictive model to examine the risk of PH using combined magnetic resonance perfusion and diffusion parameters, including cerebral blood volume (CBV), apparent diffusion coefficient, and microvascular permeability (K2).MethodsVoxel-based values of CBV, K2, and apparent diffusion coefficient from the ischemic core were obtained using pretreatment magnetic resonance imaging data from patients enrolled in the MR RESCUE clinical trial (Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy). The associations between PH and extreme values of imaging parameters were assessed in univariate and multivariate analyses. Receiver-operating characteristic curve analysis was performed to determine the optimal parameter(s) and threshold for predicting PH.ResultsIn 83 patients included in this analysis, 20 developed PH. Univariate analysis showed significantly lower 10th percentile CBV and 10th percentile apparent diffusion coefficient values and significantly higher 90th percentile K2 values within the infarction core of patients with PH. Using classification tree analysis, the 10th percentile CBV at threshold of 0.47 and 90th percentile K2 at threshold of 0.28 resulted in overall predictive accuracy of 88.7%, sensitivity of 90.0%, and specificity of 87.3%, which was superior to any individual or combination of other classifiers.ConclusionsOur results suggest that combined 10th percentile CBV and 90th percentile K2 is an independent predictor of PH in patients with acute ischemic stroke with diagnostic accuracy superior to individual classifiers alone. This approach may allow risk stratification for patients undergoing reperfusion therapies.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT00389467

Multiparametric Magnetic Resonance Imaging for Prediction of Parenchymal Hemorrhage in Acute Ischemic Stroke After Reperfusion Therapy

Background and Purpose— Patients with acute ischemic stroke are at increased risk of developing parenchymal hemorrhage (PH), particularly in the setting of reperfusion therapies. We have developed a predictive model to examine the risk of PH using combined magnetic resonance perfusion and diffusion parameters, including cerebral blood volume (CBV), apparent diffusion coefficient, and microvascular permeability (K2). Methods— Voxel-based values of CBV, K2, and apparent diffusion coefficient from the ischemic core were obtained using pretreatment magnetic resonance imaging data from patients enrolled in the MR RESCUE clinical trial (Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy). The associations between PH and extreme values of imaging parameters were assessed in univariate and multivariate analyses. Receiver-operating characteristic curve analysis was performed to determine the optimal parameter(s) and threshold for predicting PH. Results— In 83 patients included in this analysis, 20 developed PH. Univariate analysis showed significantly lower 10th percentile CBV and 10th percentile apparent diffusion coefficient values and significantly higher 90th percentile K2 values within the infarction core of patients with PH. Using classification tree analysis, the 10th percentile CBV at threshold of 0.47 and 90th percentile K2 at threshold of 0.28 resulted in overall predictive accuracy of 88.7%, sensitivity of 90.0%, and specificity of 87.3%, which was superior to any individual or combination of other classifiers. Conclusions— Our results suggest that combined 10th percentile CBV and 90th percentile K2 is an independent predictor of PH in patients with acute ischemic stroke with diagnostic accuracy superior to individual classifiers alone. This approach may allow risk stratification for patients undergoing reperfusion therapies. Clinical Trial Registration— URL: https://www.clinicaltrials.gov. Unique identifier: NCT00389467

Outcome prediction in large vessel occlusion ischemic stroke with or without endovascular stroke treatment: THRIVE-EVT

Introduction: The THRIVE score and the THRIVE-c calculation are validated ischemic stroke outcome prediction tools based on patient variables that are readily available at initial presentation. Randomized controlled trials (RCTs) have demonstrated the benefit of endovascular treatment (EVT) for many patients with large vessel occlusion (LVO), and pooled data from these trials allow for adaptation of the THRIVE-c calculation for use in shared clinical decision making regarding EVT.Methods: To extend THRIVE-c for use in the context of EVT, we extracted data from the Virtual International Stroke Trials Archive (VISTA) from 7 RCTs of EVT. Models were built in a randomly selected development cohort using logistic regression that included the predictors from THRIVE-c: age, NIH Stroke Scale (NIHSS) score, presence of hypertension, diabetes mellitus, and/or atrial fibrillation, as well as randomization to EVT and, where available, the Alberta Stroke Program Early CT Score (ASPECTS).Results: Good outcome was achieved in 366/787 (46.5%) of subjects randomized to EVT and in 236/795 (29.7%) of subjects randomized to control (P<0.001), and the improvement in outcome with EVT was seen across age, NIHSS, and THRIVE-c good outcome prediction. Models to predict outcome using THRIVE elements (age, NIHSS, and comorbidities) together with EVT, with or without ASPECTS, had similar performance by ROC analysis in the development and validation cohorts (THRIVE-EVT ROC area under the curve [AUC] = 0.716 in development, 0.727 in validation, P=0.30; THRIVE-EVT+ASPECTS ROC AUC = 0.718 in development, 0.718 in validation, P=0.12).Conclusion: THRIVE-EVT may be used alongside the original THRIVE-c calculation to improve outcome probability estimation for patients with acute ischemic stroke, including patients with or without LVO, and to model the potential improvement in outcomes with EVT for an individual patient based on variables that are available at initial presentation. Online calculators for THRIVE-c estimation are available at www.thrivescore.org and www.mdcalc.com/thrive-score-for-stroke-outcome