Citation

Devos H, Vandenberghe W, Nieuwboer A, Tant M, Baten G, De Weerdt W. Neurology 2007; 69(14): 1434-1441.

Affiliation

Katholieke Universiteit Leuven, Faculty of Kinesiology and Rehabilitation Sciences, Department of Rehabilitation Sciences, Tervuursevest 101, BE-3001 Leuven, Belgium. Hannes.Devos@faber.kuleuven.be

Copyright

(Copyright © 2007, Lippincott Williams and Wilkins)

DOI

10.1212/01.wnl.0000277640.58685.fc

PMID

17909156

Abstract

OBJECTIVE: To develop an efficient clinical screening battery to accurately predict the fitness to drive in people with Parkinson disease (PD). METHODS: This prospective study included 80 participants: 40 patients with PD and 40 healthy age- and sex-matched control subjects. All participants were assessed using a driving simulator, a driving history survey, and the Clinical Dementia Rating. The patients with PD also underwent a clinical test battery and an evaluation of fitness to drive performed by an official center, which included visual, cognitive, and on-road tests. A two-class decision from this driving assessment center was the main outcome measure. RESULTS: A screening battery assessing four clinical variables (disease duration, contrast sensitivity, Clinical Dementia Rating, and motor part of the Unified Parkinson's Disease Rating Scale) provided the best model (R(2) = 0.52) to predict the fitness to drive and correctly classified 36 (90%) of the patients with PD as pass or fail (sensitivity = 91%, specificity = 90%). The Test Ride for Investigating Practical fitness to drive (TRIP) driving simulator score discriminated significantly between drivers with PD and their healthy peers (p = 0.0008). When the TRIP driving simulator score was added to the clinical model, the total explained variance increased (R(2) = 0.60) and correctly classified 39 (97.5%) of drivers with PD into the pass/fail category (sensitivity = 91%, specificity = 100%). CONCLUSIONS: A short clinical screening battery that measures disease duration, contrast sensitivity, cognitive and motor functions can predict fitness to drive in people with Parkinson disease with a high degree of accuracy.

Language: en