Abstract
Background. The process of determining whether patients with stroke should drive again often involves off-road evaluations and road tests that usually take about 2 to 3 h to complete. Objectives. This prospective study sought to identify the combination of tests that best predicts fitness to drive after stroke. The main aim was to develop a short and predictive predriving assessment battery. Methods. Sixty-eight consecutive stroke patients were studied who performed a mandatory predriving assessment at the Belgian Road Safety Institute, Brussels, within 18 months. Performance in a predriving assessment included medical examination (when needed), visual and neuropsychological evaluations, and an on-road test. Based on these assessments, a physician, psychologist, and the driving safety expert who administered the tests decided if a subject was either "fit to drive," "temporarily unfit to drive," or "unfit to drive." Results. Logistic regression analysis revealed a combination of visual neglect, figure of Rey, and on-road tests as the model that best predicted (R2 = 0.73) fitness to drive after stroke. Using a discriminant function that included the 3 tests of the logistic model, the fitness to drive judgments of 59 (86.8%) subjects were correctly predicted. The sensitivity and specificity of the predictions were 79.4% and 94.1%, respectively. Conclusion. Fitness to drive after stroke can be predicted from performance on a few road-related tests with a high degree of accuracy. However, some individuals require extended assessments and further tests.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 417-423 |
| Number of pages | 7 |
| Journal | Neurorehabilitation and Neural Repair |
| Volume | 20 |
| Issue number | 3 |
| DOIs | |
| State | Published - Aug 1 2006 |
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Keywords
- Cerebrovascular accident
- Motor vehicles
- Neuropsychological tests
- Rehabilitation
- Road test
- Visual tests
ASJC Scopus subject areas
- Rehabilitation
- Neurology
- Clinical Neurology
Cite this
Prediction of driving after stroke : A prospective study. / Akinwuntan, A. E.; Feys, H.; De Weerdt, W.; Baten, G.; Arno, P.; Kiekens, C.
In: Neurorehabilitation and Neural Repair, Vol. 20, No. 3, 01.08.2006, p. 417-423.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Prediction of driving after stroke
T2 - A prospective study
AU - Akinwuntan, A. E.
AU - Feys, H.
AU - De Weerdt, W.
AU - Baten, G.
AU - Arno, P.
AU - Kiekens, C.
PY - 2006/8/1
Y1 - 2006/8/1
N2 - Background. The process of determining whether patients with stroke should drive again often involves off-road evaluations and road tests that usually take about 2 to 3 h to complete. Objectives. This prospective study sought to identify the combination of tests that best predicts fitness to drive after stroke. The main aim was to develop a short and predictive predriving assessment battery. Methods. Sixty-eight consecutive stroke patients were studied who performed a mandatory predriving assessment at the Belgian Road Safety Institute, Brussels, within 18 months. Performance in a predriving assessment included medical examination (when needed), visual and neuropsychological evaluations, and an on-road test. Based on these assessments, a physician, psychologist, and the driving safety expert who administered the tests decided if a subject was either "fit to drive," "temporarily unfit to drive," or "unfit to drive." Results. Logistic regression analysis revealed a combination of visual neglect, figure of Rey, and on-road tests as the model that best predicted (R2 = 0.73) fitness to drive after stroke. Using a discriminant function that included the 3 tests of the logistic model, the fitness to drive judgments of 59 (86.8%) subjects were correctly predicted. The sensitivity and specificity of the predictions were 79.4% and 94.1%, respectively. Conclusion. Fitness to drive after stroke can be predicted from performance on a few road-related tests with a high degree of accuracy. However, some individuals require extended assessments and further tests.
AB - Background. The process of determining whether patients with stroke should drive again often involves off-road evaluations and road tests that usually take about 2 to 3 h to complete. Objectives. This prospective study sought to identify the combination of tests that best predicts fitness to drive after stroke. The main aim was to develop a short and predictive predriving assessment battery. Methods. Sixty-eight consecutive stroke patients were studied who performed a mandatory predriving assessment at the Belgian Road Safety Institute, Brussels, within 18 months. Performance in a predriving assessment included medical examination (when needed), visual and neuropsychological evaluations, and an on-road test. Based on these assessments, a physician, psychologist, and the driving safety expert who administered the tests decided if a subject was either "fit to drive," "temporarily unfit to drive," or "unfit to drive." Results. Logistic regression analysis revealed a combination of visual neglect, figure of Rey, and on-road tests as the model that best predicted (R2 = 0.73) fitness to drive after stroke. Using a discriminant function that included the 3 tests of the logistic model, the fitness to drive judgments of 59 (86.8%) subjects were correctly predicted. The sensitivity and specificity of the predictions were 79.4% and 94.1%, respectively. Conclusion. Fitness to drive after stroke can be predicted from performance on a few road-related tests with a high degree of accuracy. However, some individuals require extended assessments and further tests.
KW - Cerebrovascular accident
KW - Motor vehicles
KW - Neuropsychological tests
KW - Rehabilitation
KW - Road test
KW - Visual tests
UR - http://www.scopus.com/inward/record.url?scp=33746634775&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33746634775&partnerID=8YFLogxK
U2 - 10.1177/1545968306287157
DO - 10.1177/1545968306287157
M3 - Article
C2 - 16885428
AN - SCOPUS:33746634775
VL - 20
SP - 417
EP - 423
JO - Neurorehabilitation and Neural Repair
JF - Neurorehabilitation and Neural Repair
SN - 1545-9683
IS - 3
ER -