Diagnostic performance of clinical motor and non-motor tests of Parkinson disease: a matched case–control study
Article first published online: 24 APR 2008
© 2008 The Author(s). Journal compilation © 2008 EFNS
European Journal of Neurology
Volume 15, Issue 7, pages 685–691, July 2008
How to Cite
Bohnen, N. I., Studenski, S. A., Constantine, G. M. and Moore, R. Y. (2008), Diagnostic performance of clinical motor and non-motor tests of Parkinson disease: a matched case–control study. European Journal of Neurology, 15: 685–691. doi: 10.1111/j.1468-1331.2008.02148.x
- Issue published online: 15 MAY 2008
- Article first published online: 24 APR 2008
- Received 14 January 2008 Accepted 25 March 2008
- diagnostic accuracy;
- Parkinson disease;
Background and purpose: The diagnosis of Parkinson disease (PD) is made typically on the basis of motor abnormalities. PD is now recognized to have both motor and non-motor manifestations, indicating a need for the development of reliable non-motor diagnostic tests for PD. The aim of the present study was to compare the accuracy of various clinical motor and non-motor tests for the diagnosis of PD.
Methods: Forty-five PD patients (Hoehn and Yahr stages 1–3; mean age 59.5 ± 10.0 years) and 45 healthy controls matched for gender and age completed a clinimetric motor test battery to assess limb bradykinesia, tremor and balance. Non-motor tests consisted of depression, anxiety and smell identification ratings. Area under the receiver operator characteristic curve (AUC) analysis was used.
Results: We found that smell identification was the most accurate predictor of the presence of PD within the overall group of patients and matched control subjects (AUC = 0.886) and also in the subgroups of mild severity (Hoehn and Yahr stages 1–1.5; AUC = 0.923), young-onset (AUC = 0.888) and female PD patients (AUC = 0.797). The second best diagnostic test was the grooved pegboard test for the clinically most affected body side.
Conclusions: We conclude that olfactory function is the most accurate diagnostic predictor within a heterogeneous sample of patients with PD.