The study aims to provide initial proof-of-concept validation data of an artificial intelligence-based model to estimate individual Parkinson's disease risk using demographic, clinical, genetic information and digital biomarker data collected via a smartwatch and a mobile application.
Age ≥ 50 years.
REM sleep behaviour disorder (RBD) confirmed with polysomnography.
Neurogenic orthostatic hypotension (nOH) defined as a drop in systolic / diastolic blood pressure ≥ 20/10mmHg within 3 minutes of active standing or tilt-table test, and with a blunted heart rate response (ΔHeart rate/ΔSBP ratio < 0.5 bpm/mmHg).
Objective hyposmia defined as University of Pennsylvania Smell Identification Test (UPSIT) score ≤ 15th percentile for age and sex.
Clinical diagnosis of Parkinson's disease (PD) according to MDS clinical diagnostic criteria.
Currently taking levodopa, dopamine agonists, MAO-B inhibitors, amantadine or another PD medication, except for low-dose treatment of restless leg syndrome (with permission of investigator).
Dementia defined as deterioration of cognitive function severe enough to impair functioning on daily activities.
Active treatment with neuroleptics, reserpine or metoclopramide (these drugs should be discontinued for at least 6 months before screening visit) due to their interference with dopamine transporter SPECT imaging acquisition and interpretation.
Queen Mary University of London
Lead sponsor
Hospital Ruber Internacional
Collaborator
University Hospital, Toulouse
Collaborator
Aristotle University Of Thessaloniki
Collaborator