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- Publisher Website: 10.1371/journal.pone.0143342
- Scopus: eid_2-s2.0-84956651210
- PMID: 26637172
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Article: Predicting stroke risk based on health behaviours: Development of the Stroke Population Risk Tool (SPoRT)
Title | Predicting stroke risk based on health behaviours: Development of the Stroke Population Risk Tool (SPoRT) |
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Authors | |
Issue Date | 2015 |
Citation | PLoS ONE, 2015, v. 10, n. 12, article no. e0143342 How to Cite? |
Abstract | Background: 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 Identifier | http://hdl.handle.net/10722/346611 |
DC Field | Value | Language |
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dc.contributor.author | Manuel, Douglas G. | - |
dc.contributor.author | Tuna, Meltem | - |
dc.contributor.author | Perez, Richard | - |
dc.contributor.author | Tanuseputro, Peter | - |
dc.contributor.author | Hennessy, Deirdre | - |
dc.contributor.author | Bennett, Carol | - |
dc.contributor.author | Rosella, Laura | - |
dc.contributor.author | Sanmartin, Claudia | - |
dc.contributor.author | Van Walraven, Carl | - |
dc.contributor.author | Tu, Jack V. | - |
dc.date.accessioned | 2024-09-17T04:12:03Z | - |
dc.date.available | 2024-09-17T04:12:03Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | PLoS ONE, 2015, v. 10, n. 12, article no. e0143342 | - |
dc.identifier.uri | http://hdl.handle.net/10722/346611 | - |
dc.description.abstract | Background: 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.language | eng | - |
dc.relation.ispartof | PLoS ONE | - |
dc.title | Predicting stroke risk based on health behaviours: Development of the Stroke Population Risk Tool (SPoRT) | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1371/journal.pone.0143342 | - |
dc.identifier.pmid | 26637172 | - |
dc.identifier.scopus | eid_2-s2.0-84956651210 | - |
dc.identifier.volume | 10 | - |
dc.identifier.issue | 12 | - |
dc.identifier.spage | article no. e0143342 | - |
dc.identifier.epage | article no. e0143342 | - |
dc.identifier.eissn | 1932-6203 | - |