Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).

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.Behavioural, sociodemographic and other risk factors were assessed in a pop...

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Main Authors: Douglas G Manuel, Meltem Tuna, Richard Perez, Peter Tanuseputro, Deirdre Hennessy, Carol Bennett, Laura Rosella, Claudia Sanmartin, Carl van Walraven, Jack V Tu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4670216?pdf=render
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spelling doaj-65169fdb74294343a695dbc980651b3b2020-11-24T20:50:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011012e014334210.1371/journal.pone.0143342Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).Douglas G ManuelMeltem TunaRichard PerezPeter TanuseputroDeirdre HennessyCarol BennettLaura RosellaClaudia SanmartinCarl van WalravenJack V TuHealth 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.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).We observed 3236 incident stroke events (1551 resulting in hospitalization; 1685 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.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.http://europepmc.org/articles/PMC4670216?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Douglas G Manuel
Meltem Tuna
Richard Perez
Peter Tanuseputro
Deirdre Hennessy
Carol Bennett
Laura Rosella
Claudia Sanmartin
Carl van Walraven
Jack V Tu
spellingShingle Douglas G Manuel
Meltem Tuna
Richard Perez
Peter Tanuseputro
Deirdre Hennessy
Carol Bennett
Laura Rosella
Claudia Sanmartin
Carl van Walraven
Jack V Tu
Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).
PLoS ONE
author_facet Douglas G Manuel
Meltem Tuna
Richard Perez
Peter Tanuseputro
Deirdre Hennessy
Carol Bennett
Laura Rosella
Claudia Sanmartin
Carl van Walraven
Jack V Tu
author_sort Douglas G Manuel
title Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).
title_short Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).
title_full Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).
title_fullStr Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).
title_full_unstemmed Predicting Stroke Risk Based on Health Behaviours: Development of the Stroke Population Risk Tool (SPoRT).
title_sort predicting stroke risk based on health behaviours: development of the stroke population risk tool (sport).
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description 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.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).We observed 3236 incident stroke events (1551 resulting in hospitalization; 1685 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.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.
url http://europepmc.org/articles/PMC4670216?pdf=render
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