Background and ObjectivesFemale-specific factors and psychosocial factors may be important in the prediction of strokebut are not included in prediction models that are currently used. We... Show moreBackground and ObjectivesFemale-specific factors and psychosocial factors may be important in the prediction of strokebut are not included in prediction models that are currently used. We investigated whetheraddition of these factors would improve the performance of prediction models for the risk ofstroke in women younger than 50 years.MethodsWe used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20–49 years without a history of cardiovasculardisease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportionalhazards models to predict stroke risk were developed, including traditional cardiovascularfactors, and compared with models that additionally included female-specific and psychosocialfactors. We compared the risk models using the c-statistic and slope of the calibration curve at afollow-up of 10 years. We developed an age-specific stroke risk prediction tool that may helpcommunicating the risk of stroke in clinical practice.ResultsWe included 409,026 women with a total of 3,990,185 person-years of follow-up. Strokeoccurred in 2,751 women (incidence rate 6.9 [95% CI 6.6–7.2] per 10,000 person-years).Models with only traditional cardiovascular factors performed poorly to moderately in all agegroups: 20–29 years: c-statistic: 0.617 (95% CI 0.592–0.639); 30–39 years: c-statistic: 0.615(95% CI 0.596–0.634); and 40–49 years: c-statistic: 0.585 (95% CI 0.573–0.597). After addingthe female-specific and psychosocial risk factors to the reference models, the model discrimi-nation increased moderately, especially in the age groups 30–39 (Dc-statistic: 0.019) and 40–49years (Dc-statistic: 0.029) compared with the reference models, respectively.DiscussionThe addition of female-specific factors and psychosocial risk factors improves the discrimina-tory performance of prediction models for stroke in women younger than 50 years. Show less
Background: An increased risk of stroke in patients with migraine has been primarily found for women. The sex-dependent mechanisms underlying the migraine-stroke association, however, remain... Show moreBackground: An increased risk of stroke in patients with migraine has been primarily found for women. The sex-dependent mechanisms underlying the migraine-stroke association, however, remain unknown. This study aims to explore these sex differences to improve our understanding of pathophysiological mechanisms behind the migraine-stroke association.Methods: We included 2,492 patients with ischemic stroke from the prospective multicenter Dutch Parelsnoer Institute Initiative study, 425 (17%) of whom had a history of migraine. Cardiovascular risk profile, stroke cause (TOAST classification), and outcome [modified Rankin scale (mRS) at 3 months] were compared with both sexes between patients with and without migraine.Results: A history of migraine was not associated with sex differences in the prevalence of conventional cardiovascular risk factors. Women with migraine had an increased risk of stroke at young age (onset < 50 years) compared with women without migraine (RR: 1.7; 95% CI: 1.3-2.3). Men with migraine tended to have more often stroke in the TOAST category other determined etiology (RR: 1.7; 95% CI: 1.0-2.7) in comparison with men without migraine, whereas this increase was not found in women with migraine. Stroke outcome was similar for women with or without migraine (mRS >= 3 RR 1.1; 95% CI 0.7-1.5), whereas men seemed to have a higher risk of poor outcome compared with their counterparts without migraine (mRS >= 3 RR: 1.5; 95% CI: 1.0-2.1).Conclusion: Our results indicate possible sex differences in the pathophysiology underlying the migraine-stroke association, which are unrelated to conventional cardiovascular risk factors. Further research in larger cohorts is needed to validate these findings. Show less
