Abstract
Models to predict stroke risk with the aim of stroke prevention often use age as a factor in the model (Choudhury et al., 2015; Conroy et al., 2003; D’Agostino etal., 2008; Wolf et al., 1991). However, stroke risk scores often underestimate riskfor specific age groups, particularly younger age groups and the contribution of different risk factors to overall stroke risk changes over time (Boehme et al., 2017; Seshadri et al., 2006). Additionally, because age is a strong predictor of stroke, age can dominate the risk score (Leening et al., 2017). Longitudinal Studies such as the Irish Longitudinal study on Aging (TILDA) allow us to track these changein risk factors (TILDA, 2019). We aim to determine risk factors using an age group specific analysis in order to reduce the underestimation of risk for certainage groups.
Original language | English |
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DOIs | |
Publication status | Published - 2021 |
Event | Longitudinal Studies Conference - Wellcome Genome Campus, United Kingdom Duration: 10 Mar 2021 → 12 Mar 2021 |
Conference
Conference | Longitudinal Studies Conference |
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Country/Territory | United Kingdom |
City | Wellcome Genome Campus |
Period | 10/03/21 → 12/03/21 |
Keywords
- stroke risk
- age group
- risk factors
- longitudinal studies
- TILDA