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Trial registered on ANZCTR
Registration number
ACTRN12621000453886
Ethics application status
Approved
Date submitted
7/02/2021
Date registered
19/04/2021
Date last updated
2/03/2023
Date data sharing statement initially provided
19/04/2021
Type of registration
Prospectively registered
Titles & IDs
Public title
Parkinson’s Disease Spiral Analysis Project
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Scientific title
Parkinson’s Disease Spiral Analysis Project: development of an artificial intelligence algorithm to identify 'on' and 'off' states in Parkinson's Disease
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Secondary ID [1]
303376
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None
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Universal Trial Number (UTN)
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Trial acronym
PD-SAP
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Parkinson's Disease
320648
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Condition category
Condition code
Neurological
318500
318500
0
0
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Parkinson's disease
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Intervention/exposure
Study type
Observational
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Patient registry
False
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
Each participant will undergo a physical examination by a neurologist to determine if they are in 'on' or 'off' state. 'On' state is defined as when the patient's Parkinson's Disease symptoms are under adequate control; 'off' state is defined as a state when the symptoms are under suboptimal control. Then they will be asked to wear a smart watch with an accelerometer on their writing hand and draw a spiral.
They will be asked to do this in the 'on' and 'off' state. Each session is expected to take ~30 min maximum and can take place on the same day, or up to 1 month apart, depending on the participant's preference.. An individual's participation will be considered complete when there is one spiral from both of the 'on' and 'off' state. Multiple sessions, if a patient is deemed to be in the same state as the previous session, may be required to achieve this outcome.
The photo of the spiral, and the accelerometer data, will be entered into a machine learning algorithm to determine if this algorithm can determine whether a spiral was produced in 'on' or 'off' state.
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Intervention code [1]
319685
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Not applicable
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Comparator / control treatment
Nil applicable
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Control group
Uncontrolled
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Outcomes
Primary outcome [1]
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The positive predictive value (PPV) for detecting 'on' state of Parkinson's Disease in participants using an artificial intelligence algorithm will be determined by comparing the rate of 'on' state participants as assessed by a neurologist (reference standard) compared to the rate of 'on' state participants assessed by analysis of a drawing assessed by the artificial intelligence algorithm
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Assessment method [1]
326455
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Timepoint [1]
326455
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12 months post baseline.
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Secondary outcome [1]
391544
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The positive predictive value (PPV) for detecting 'off' state of Parkinson's Disease in participants using an artificial intelligence algorithm will be determined by comparing the rate of 'off' state participants as assessed by a neurologist (reference standard) compared to the rate of 'off' state participants assessed by analysis of a drawing assessed by the artificial intelligence algorithm
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Assessment method [1]
391544
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Timepoint [1]
391544
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12 months post baseline
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Eligibility
Key inclusion criteria
1. Parkinson’s Disease patients on appropriate therapy
2. Able to hold a pen and draw while wearing a wrist watch
3. Able to read, follow instructions, and communicate with others in English
4. No cognitive impairment
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Presence of any comorbidities or conditions, in the opinion of the investigator, that would preclude successful completion of the study
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Study design
Purpose
Screening
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Duration
Longitudinal
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Selection
Defined population
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Timing
Both
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Statistical methods / analysis
The statistical analysis will consist of analyzing the accuracy of the algorithm. This will simply consist of checking how many spirals the algorithm identifies correctly by dividing the number of correctly identified spirals by the total number of spirals tested to obtain accuracy as percentage. There will be no interim analyses. Machine learning experts have advised that ~400 of spirals of each state would be required, and 200 from each state to validate - ie total of 1200 spiral proudction.
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Recruitment
Recruitment status
Recruiting
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Date of first participant enrolment
Anticipated
4/04/2022
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Actual
2/05/2022
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Date of last participant enrolment
Anticipated
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Actual
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Date of last data collection
Anticipated
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Actual
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Sample size
Target
200
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Accrual to date
150
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Final
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Recruitment in Australia
Recruitment state(s)
NSW
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Recruitment hospital [1]
18587
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Gosford Hospital - Gosford
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Recruitment postcode(s) [1]
32960
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2250 - Gosford
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Funding & Sponsors
Funding source category [1]
307789
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Hospital
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Name [1]
307789
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Gosford Hospital
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Address [1]
307789
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Corner Racecourse Road and Holden St
Gosford NSW 2250
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Country [1]
307789
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Australia
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Primary sponsor type
Individual
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Name
Yun Hwang
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Address
Department of Neurology
Gosford Hospital
Corner Racecourse Rd and Holden St
Gosford NSW 2250
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Country
Australia
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Secondary sponsor category [1]
308499
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None
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Name [1]
308499
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Address [1]
308499
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Country [1]
308499
0
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
307805
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Hunter New England Human Research Ethics Committee
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Ethics committee address [1]
307805
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Hunter New England Human Research Ethics Committee Hunter New England Local Health District Level 3, POD, HMRI, Lot 1 Kookaburra Circuit New Lambton Heights NSW 2305
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Ethics committee country [1]
307805
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Australia
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Date submitted for ethics approval [1]
307805
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Approval date [1]
307805
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17/11/2020
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Ethics approval number [1]
307805
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2020/ETH02373
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Summary
Brief summary
This study attempts to harness advances in machine learning and artificial intelligence to faciliate monitoring of symptom fluctuations in Parkinson's disease. Participants will be asked to draw a spiral while wearing a smart watch with accelerometer function in both 'on' and 'off' state, based on clinical assessment. These samples will be used to train the algorithm, and an independent set of samples used for validation of the algorithm.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
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Dr Yun Tae Hwang
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Address
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Department of Neurology
Gosford Hospital
Corner Racecourse Rd and Holden St
Gosford NSW 2250
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Country
108562
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Australia
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Phone
108562
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+61243202404
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Fax
108562
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+61243203783
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Email
108562
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[email protected]
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Contact person for public queries
Name
108563
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Yun Tae Hwang
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Address
108563
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Department of Neurology
Gosford Hospital
Corner Racecourse Rd and Holden St
Gosford NSW 2250
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Country
108563
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Australia
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Phone
108563
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+61243202404
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Fax
108563
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+61243203783
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Email
108563
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[email protected]
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Contact person for scientific queries
Name
108564
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Yun Tae Hwang
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Address
108564
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Department of Neurology
Gosford Hospital
Corner Racecourse Rd and Holden St
Gosford NSW 2250
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Country
108564
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Australia
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Phone
108564
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+61243202404
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Fax
108564
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+61243203783
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Email
108564
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[email protected]
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Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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No/undecided IPD sharing reason/comment
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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