Quantitative trunk sway analysis under challenging gait conditions in early and untreated Parkinson’s disease
| Autor: | Hamid Assar, Thomas Wolfsegger, Robert Pichler, Raffi Topakian |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Parkinson's disease Receiver operating characteristic analysis business.industry Torso Parkinson Disease Dermatology General Medicine medicine.disease Gait Trunk Psychiatry and Mental health Physical medicine and rehabilitation Rating scale Clinical diagnosis Basal ganglia Cohort medicine Humans Neurology (clinical) business Postural Balance human activities |
| Zdroj: | Neurological Sciences. 43:1411-1413 |
| ISSN: | 1590-3478 1590-1874 |
| DOI: | 10.1007/s10072-021-05699-w |
| Popis: | Introduction Even experienced clinicians may encounter difficulties in making a definitive diagnosis in the early motor stages of Parkinson's disease (PD). We investigated whether quantitative biomechanical trunk sway analysis could support the diagnosis of PD early on. Methods We quantified trunk sway performance using body-worn sensors during a test battery of six challenging gait conditions in a cohort of 17 early and untreated PD patients (with evidence of reduced tracer uptake in the basal ganglia on dopamine transporter scans) and 17 age- and sex-matched healthy controls (HCs). Results Compared to HC, the PD group (Hoehn & Yahr ≤ 2, Unified Parkinson's Disease Rating Scale motor score: mean 13.7 ± 3.5 points) showed significant trunk rigidity in five challenging gait tasks (decreased medio-lateral direction and sway angle area). Post hoc receiver operating characteristic analysis of the significant parameters revealed excellent discrimination with high sensitivity and specificity. Conclusion In the early and untreated motor stages of PD, patients exhibit significant trunk rigidity during challenging gait tasks. Trunk sway motion recorded with body-worn sensors might be a useful tool to disclose a sometimes hard-to-trace cardinal motor sign of PD and support an early clinical diagnosis. |
| Databáze: | OpenAIRE |
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