Abstract
Progressive supranuclear palsy (PSP) is a rare and rapidly progressing atypical parkinsonism. Albeit existing clinical criteria for PSP have good specificity and sensitivity, there is a need for biomarkers able to capture early objective disease-specific abnormalities. This study aimed to identify gait patterns specifically associated with early PSP. The study population comprised 104 consecutively enrolled participants (83 PD and 21 PSP patients). Gait was investigated using a gait analysis system during normal gait and a cognitive dual task. Univariate statistical analysis and binary logistic regression were used to compare all PD patients and all PSP patients, as well as newly diagnosed PD and early PSP patients. Gait pattern was poorer in PSP patients than in PD patients, even from early stages. PSP patients exhibited reduced velocity and increased measures of dynamic instability when compared to PD patients. Application of predictive models to gait data revealed that PD gait pattern was typified by increased cadence and longer cycle length, whereas a longer stance phase characterized PSP patients in both mid and early disease stages. The present study demonstrates that quantitative gait evaluation clearly distinguishes PSP patients from PD patients since the earliest stages of disease. First, this might candidate gait analysis as a reliable biomarker in both clinical and research setting. Furthermore, our results may offer speculative clues for conceiving early disease-specific rehabilitation strategies.
Highlights
Progressive supranuclear palsy (PSP) is a rare and rapidly progressing atypical parkinsonism
The analysis was restricted to newly diagnosed Parkinson’s disease (PD) patients (N = 27) and early PSP patients (N = 12)
We demonstrated that PSP patients exhibited disease-specific gait pattern when compared to PD patients, even during the earliest stages of disease
Summary
Progressive supranuclear palsy (PSP) is a rare and rapidly progressing atypical parkinsonism. Application of predictive models to gait data revealed that PD gait pattern was typified by increased cadence and longer cycle length, whereas a longer stance phase characterized PSP patients in both mid and early disease stages. The present study demonstrates that quantitative gait evaluation clearly distinguishes PSP patients from PD patients since the earliest stages of disease. This might candidate gait analysis as a reliable biomarker in both clinical and research setting. Gait analysis has been employed for different objectives in PD patients, including the investigation of pathophysiological mechanisms underpinning the disease, evaluation of treatment outcomes, automatic recognition of PD symptoms, and implementation of algorithms for PD diagnosis and staging[11,12,13,14]. Gait analysis has been used to explore the association between specific gait patterns and specific symptoms of PD, such as mild cognitive impairment[15,16] and freezing of g ait[17]
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