Shawn Marshall, Michel Bédard, Brenda Vrkljan, Holly Tuokko, Michelle M Porter, Gary Naglie, Mark J Rapoport, Barbara Mazer, Isabelle Gélinas, Sylvain Gagnon, Judith L Charlton, Sjaan Koppel, Lynn MacLeay, Anita Myers, Ranjeeta Mallick, Tim Ramsay, Ian Stiell, George Wells, Malcolm Man-Son-Hing
{"title":"老年司机风险分层工具的开发。","authors":"Shawn Marshall, Michel Bédard, Brenda Vrkljan, Holly Tuokko, Michelle M Porter, Gary Naglie, Mark J Rapoport, Barbara Mazer, Isabelle Gélinas, Sylvain Gagnon, Judith L Charlton, Sjaan Koppel, Lynn MacLeay, Anita Myers, Ranjeeta Mallick, Tim Ramsay, Ian Stiell, George Wells, Malcolm Man-Son-Hing","doi":"10.1093/gerona/glad044","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Assessing an older adult's fitness-to-drive is an important part of clinical decision making. However, most existing risk prediction tools only have a dichotomous design, which does not account for subtle differences in risk status for patients with complex medical conditions or changes over time. Our objective was to develop an older driver risk stratification tool (RST) to screen for medical fitness-to-drive in older adults.</p><p><strong>Methods: </strong>Participants were active drivers aged 70 and older from 7 sites across 4 Canadian provinces. They underwent in-person assessments every 4 months with an annual comprehensive assessment. Participant vehicles were instrumented to provide vehicle and passive Global Positioning System (GPS) data. The primary outcome measure was police-reported, expert-validated, at-fault collision adjusted per annual kilometers driven. Predictor variables included physical, cognitive, and health assessment measures.</p><p><strong>Results: </strong>A total of 928 older drivers were recruited for this study beginning in 2009. The average age at enrollment was 76.2 (standard deviation [SD] = 4.8) with 62.1% male participants. The mean duration for participation was 4.9 (SD = 1.6) years. The derived Candrive RST included 4 predictors. Out of 4 483 person-years of driving, 74.8% fell within the lowest risk category. Only 2.9% of person-years were in the highest risk category where the relative risk for at-fault collisions was 5.26 (95% confidence interval = 2.81-9.84) compared to the lowest risk group.</p><p><strong>Conclusions: </strong>For older drivers whose medical conditions create uncertainty regarding their fitness-to-drive, the Candrive RST may assist primary health care providers when initiating a conversation about driving and to guide further evaluation.</p>","PeriodicalId":49953,"journal":{"name":"Journals of Gerontology Series A-Biological Sciences and Medical Sciences","volume":" ","pages":"2348-2355"},"PeriodicalIF":4.3000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692431/pdf/","citationCount":"0","resultStr":"{\"title\":\"Candrive-Development of a Risk Stratification Tool for Older Drivers.\",\"authors\":\"Shawn Marshall, Michel Bédard, Brenda Vrkljan, Holly Tuokko, Michelle M Porter, Gary Naglie, Mark J Rapoport, Barbara Mazer, Isabelle Gélinas, Sylvain Gagnon, Judith L Charlton, Sjaan Koppel, Lynn MacLeay, Anita Myers, Ranjeeta Mallick, Tim Ramsay, Ian Stiell, George Wells, Malcolm Man-Son-Hing\",\"doi\":\"10.1093/gerona/glad044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Assessing an older adult's fitness-to-drive is an important part of clinical decision making. However, most existing risk prediction tools only have a dichotomous design, which does not account for subtle differences in risk status for patients with complex medical conditions or changes over time. Our objective was to develop an older driver risk stratification tool (RST) to screen for medical fitness-to-drive in older adults.</p><p><strong>Methods: </strong>Participants were active drivers aged 70 and older from 7 sites across 4 Canadian provinces. They underwent in-person assessments every 4 months with an annual comprehensive assessment. Participant vehicles were instrumented to provide vehicle and passive Global Positioning System (GPS) data. The primary outcome measure was police-reported, expert-validated, at-fault collision adjusted per annual kilometers driven. Predictor variables included physical, cognitive, and health assessment measures.</p><p><strong>Results: </strong>A total of 928 older drivers were recruited for this study beginning in 2009. The average age at enrollment was 76.2 (standard deviation [SD] = 4.8) with 62.1% male participants. The mean duration for participation was 4.9 (SD = 1.6) years. The derived Candrive RST included 4 predictors. Out of 4 483 person-years of driving, 74.8% fell within the lowest risk category. Only 2.9% of person-years were in the highest risk category where the relative risk for at-fault collisions was 5.26 (95% confidence interval = 2.81-9.84) compared to the lowest risk group.</p><p><strong>Conclusions: </strong>For older drivers whose medical conditions create uncertainty regarding their fitness-to-drive, the Candrive RST may assist primary health care providers when initiating a conversation about driving and to guide further evaluation.</p>\",\"PeriodicalId\":49953,\"journal\":{\"name\":\"Journals of Gerontology Series A-Biological Sciences and Medical Sciences\",\"volume\":\" \",\"pages\":\"2348-2355\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692431/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journals of Gerontology Series A-Biological Sciences and Medical Sciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/gerona/glad044\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journals of Gerontology Series A-Biological Sciences and Medical Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/gerona/glad044","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Candrive-Development of a Risk Stratification Tool for Older Drivers.
Background: Assessing an older adult's fitness-to-drive is an important part of clinical decision making. However, most existing risk prediction tools only have a dichotomous design, which does not account for subtle differences in risk status for patients with complex medical conditions or changes over time. Our objective was to develop an older driver risk stratification tool (RST) to screen for medical fitness-to-drive in older adults.
Methods: Participants were active drivers aged 70 and older from 7 sites across 4 Canadian provinces. They underwent in-person assessments every 4 months with an annual comprehensive assessment. Participant vehicles were instrumented to provide vehicle and passive Global Positioning System (GPS) data. The primary outcome measure was police-reported, expert-validated, at-fault collision adjusted per annual kilometers driven. Predictor variables included physical, cognitive, and health assessment measures.
Results: A total of 928 older drivers were recruited for this study beginning in 2009. The average age at enrollment was 76.2 (standard deviation [SD] = 4.8) with 62.1% male participants. The mean duration for participation was 4.9 (SD = 1.6) years. The derived Candrive RST included 4 predictors. Out of 4 483 person-years of driving, 74.8% fell within the lowest risk category. Only 2.9% of person-years were in the highest risk category where the relative risk for at-fault collisions was 5.26 (95% confidence interval = 2.81-9.84) compared to the lowest risk group.
Conclusions: For older drivers whose medical conditions create uncertainty regarding their fitness-to-drive, the Candrive RST may assist primary health care providers when initiating a conversation about driving and to guide further evaluation.
期刊介绍:
Publishes articles representing the full range of medical sciences pertaining to aging. Appropriate areas include, but are not limited to, basic medical science, clinical epidemiology, clinical research, and health services research for professions such as medicine, dentistry, allied health sciences, and nursing. It publishes articles on research pertinent to human biology and disease.