The Stroke Riskometer(TM) App: Validation of a Data Collection Tool and Stroke Risk Predictor
Parmar, P; Krishnamurthi, R; Ikram, MA; Hofman, A; Mirza, SS; Varakin, Y; Kravchenko, M; Piradov, M; Thrift, AG; Norrving, B; Wang, W; Mandal, DK; Barker-Collo, S; Sahathevan, R; Davis, S; Saposnik, G; Kivipelto, M; Sindi, S; Bornstein, NM; Giroud, M; Béjot, Y; Brainin, M; Poulton, R; Narayan, KM; Correia, M; Freire, A; Kokubo, Y; Wiebers, D; Mensah, G; BinDhim, NF; Barber, PA; Pandian, JD; Hankey, GJ; Mehndiratta, MM; Azhagammal, S; Ibrahim, NM; Abbott, M; Rush, E; Hume, P; Hussein, T; Bhattacharjee, R; Purohit, M; Feigin, VL; Stroke RiskometerTM Collaboration Writing Group
MetadataShow full metadata
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(TM) , has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods.