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Article: Predicting stroke risk based on health behaviours: Development of the Stroke Population Risk Tool (SPoRT)

TitlePredicting stroke risk based on health behaviours: Development of the Stroke Population Risk Tool (SPoRT)
Authors
Issue Date2015
Citation
PLoS ONE, 2015, v. 10, n. 12, article no. e0143342 How to Cite?
AbstractBackground: Health behaviours, important factors in cardiovascular disease, are increasingly a focus of prevention. We appraised whether stroke risk can be accurately assessed using self-reported information focused on health behaviours. Methods: Behavioural, sociodemographic and other risk factors were assessed in a population-based survey of 82 259 Ontarians who were followed for a median of 8.6 years (688 000 person-years follow-up) starting in 2001. Predictive algorithms for 5-year incident stroke resulting in hospitalization were created and then validated in a similar 2007 survey of 28 605 respondents (median 4.2 years follow-up). Results: We observed 3 236 incident stroke events (1 551 resulting in hospitalization; 1 685 in the community setting without hospital admission). The final algorithms were discriminating (C-stat: 0.85, men; 0.87, women) and well-calibrated (in 65 of 67 subgroups for men; 61 of 65 for women). An index was developed to summarize cumulative relative risk of incident stroke from health behaviours and stress. For men, each point on the index corresponded to a 12% relative risk increase (180% risk difference, lowest (0) to highest (9) scores). For women, each point corresponded to a 14% relative risk increase (340% difference, lowest (0) to highest (11) scores). Algorithms for secondary stroke outcomes (stroke resulting in death; classified as ischemic; excluding transient ischemic attack; and in the community setting) had similar health behaviour risk hazards. Conclusion: Incident stroke can be accurately predicted using self-reported information focused on health behaviours. Risk assessment can be performed with population health surveys to support population health planning or outside of clinical settings to support patient-focused prevention.
Persistent Identifierhttp://hdl.handle.net/10722/346611

 

DC FieldValueLanguage
dc.contributor.authorManuel, Douglas G.-
dc.contributor.authorTuna, Meltem-
dc.contributor.authorPerez, Richard-
dc.contributor.authorTanuseputro, Peter-
dc.contributor.authorHennessy, Deirdre-
dc.contributor.authorBennett, Carol-
dc.contributor.authorRosella, Laura-
dc.contributor.authorSanmartin, Claudia-
dc.contributor.authorVan Walraven, Carl-
dc.contributor.authorTu, Jack V.-
dc.date.accessioned2024-09-17T04:12:03Z-
dc.date.available2024-09-17T04:12:03Z-
dc.date.issued2015-
dc.identifier.citationPLoS ONE, 2015, v. 10, n. 12, article no. e0143342-
dc.identifier.urihttp://hdl.handle.net/10722/346611-
dc.description.abstractBackground: Health behaviours, important factors in cardiovascular disease, are increasingly a focus of prevention. We appraised whether stroke risk can be accurately assessed using self-reported information focused on health behaviours. Methods: Behavioural, sociodemographic and other risk factors were assessed in a population-based survey of 82 259 Ontarians who were followed for a median of 8.6 years (688 000 person-years follow-up) starting in 2001. Predictive algorithms for 5-year incident stroke resulting in hospitalization were created and then validated in a similar 2007 survey of 28 605 respondents (median 4.2 years follow-up). Results: We observed 3 236 incident stroke events (1 551 resulting in hospitalization; 1 685 in the community setting without hospital admission). The final algorithms were discriminating (C-stat: 0.85, men; 0.87, women) and well-calibrated (in 65 of 67 subgroups for men; 61 of 65 for women). An index was developed to summarize cumulative relative risk of incident stroke from health behaviours and stress. For men, each point on the index corresponded to a 12% relative risk increase (180% risk difference, lowest (0) to highest (9) scores). For women, each point corresponded to a 14% relative risk increase (340% difference, lowest (0) to highest (11) scores). Algorithms for secondary stroke outcomes (stroke resulting in death; classified as ischemic; excluding transient ischemic attack; and in the community setting) had similar health behaviour risk hazards. Conclusion: Incident stroke can be accurately predicted using self-reported information focused on health behaviours. Risk assessment can be performed with population health surveys to support population health planning or outside of clinical settings to support patient-focused prevention.-
dc.languageeng-
dc.relation.ispartofPLoS ONE-
dc.titlePredicting stroke risk based on health behaviours: Development of the Stroke Population Risk Tool (SPoRT)-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1371/journal.pone.0143342-
dc.identifier.pmid26637172-
dc.identifier.scopuseid_2-s2.0-84956651210-
dc.identifier.volume10-
dc.identifier.issue12-
dc.identifier.spagearticle no. e0143342-
dc.identifier.epagearticle no. e0143342-
dc.identifier.eissn1932-6203-

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