Predictors of simulated driving performance in Huntington's disease.
Parkinsonism Relat Disord
; 60: 64-69, 2019 03.
Article
em En
| MEDLINE
| ID: mdl-30292732
BACKGROUND: As the disease progresses, patients with Huntington's disease (HD), an inherited neurodegenerative disorder, become less independent in their daily life activities and have to consider if they can still drive a car. For most patients, the decision to quit driving is difficult and affects their independence and social activities. OBJECTIVE: To investigate if cognitive, motor, or psychiatric symptoms can predict driving performance in HD gene carriers using a simulator situation. METHODS: Twenty-nine controls, 28 premanifest HD, and 30 manifest HD participated in this observational, cross-sectional study and underwent neuropsychological, motor, and psychiatric evaluations. All participants drove a motorway scenario in a driving simulator to evaluate driving performance. Group differences were analyzed using Analysis of Covariance and stepwise forward linear regression analysis was used to investigate which clinical assessments were predictors of driving simulator outcomes. RESULTS: Manifest HD drove slower and had less vehicle control in the driving simulator compared to controls and premanifest HD. They also performed worse on all clinical assessments compared to controls. Postural sway and slower speed of information processing were predictors of the driving simulator outcome measures. Psychiatric symptoms were unrelated to simulated driving. There were no significant differences between premanifest HD and controls. CONCLUSIONS: Increased postural sway and slower speed of processing are predictive of driving simulator performance in manifest HD. Worse performance on these clinical tasks might be useful as a first screening and could assist clinicians in their referral for an official on-road driving test.
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MEDLINE
Assunto principal:
Desempenho Psicomotor
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Condução de Veículo
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Doença de Huntington
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Equilíbrio Postural
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Disfunção Cognitiva
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article