Pandian, Jeyaraj

Background: Despite the well-established potent benefit of mechanical thrombectomy (MT) for large vessel occlusion (LVO) stroke, access to MT has not been studied globally. We conducted a worldwide survey of countries on 6 continents to define MT access (MTA), the disparities in MTA, and its determinants on a global scale. Methods: Our survey was conducted in 75 countries through the Mission Thrombectomy 2020+ global network between November 22, 2020, and February 28, 2021. The primary end points were the current annual MTA, MT operator availability, and MT center availability. MTA was defined as the estimated proportion of patients with LVO receiving MT in a given region annually. The availability metrics were defined as ([current MT operators×50/current annual number of estimated thrombectomy-eligible LVOs]×100 = MT operator availability) and ([current MT centers×150/current annual number of estimated thrombectomy-eligible LVOs]×100= MT center availability). The metrics used optimal MT volume per operator as 50 and an optimal MT volume per center as 150. Multivariable-adjusted generalized linear models were used to evaluate factors associated with MTA. Results: We received 887 responses from 67 countries. The median global MTA was 2.79% (interquartile range, 0.70–11.74). MTA was <1.0% for 18 (27%) countries and 0 for 7 (10%) countries. There was a 460-fold disparity between the highest and lowest nonzero MTA regions and low-income countries had 88% lower MTA compared with high-income countries. The global MT operator availability was 16.5% of optimal and the MT center availability was 20.8% of optimal. On multivariable regression, country income level (low or lower–middle versus high: odds ratio, 0.08 [95% CI, 0.04–0.12]), MT operator availability (odds ratio, 3.35 [95% CI, 2.07–5.42]), MT center availability (odds ratio, 2.86 [95% CI, 1.84–4.48]), and presence of prehospital acute stroke bypass protocol (odds ratio, 4.00 [95% CI, 1.70–9.42]) were significantly associated with increased odds of MTA. Conclusions: Access to MT on a global level is extremely low, with enormous disparities between countries by income level. The significant determinants of MT access are the country’s per capita gross national income, prehospital LVO triage policy, and MT operator and center availability.

Background The greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the ‘mass’ approach), the ‘high risk’ approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer™, has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods. Methods 752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke Riskometer™) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R2 statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm. Results The Stroke Riskometer™ performed well against the FSRS five-year AUROC for both males (FSRS = 75·0% (95% CI 72·3%–77·6%), Stroke Riskometer™ = 74·0(95% CI 71·3%–76·7%) and females [FSRS = 70·3% (95% CI 67·9%–72·8%, Stroke Riskometer™ = 71·5% (95% CI 69·0%–73·9%)], and better than QStroke [males–59·7% (95% CI 57·3%–62·0%) and comparable to females = 71·1% (95% CI 69·0%–73·1%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 0·51–0·56, D-statistic ranging from 0·01–0·12). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data ( P < 0·006). Conclusions The Stroke Riskometer™ is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer™ will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors.