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Trial registered on ANZCTR
Registration number
ACTRN12623001174673
Ethics application status
Approved
Date submitted
27/09/2023
Date registered
14/11/2023
Date last updated
14/11/2023
Date data sharing statement initially provided
14/11/2023
Type of registration
Retrospectively registered
Titles & IDs
Public title
Assessing cardiovascular disease risk from retinal images using artificial intelligence at primary care settings
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Scientific title
Assessing cardiovascular risk by integrating retinal photography and artificial intelligence at primary care settings
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Secondary ID [1]
310695
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Nil known
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Universal Trial Number (UTN)
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Trial acronym
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Cardiovascular disease risk assessment
331603
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Retinal assessment
331888
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Condition category
Condition code
Cardiovascular
328340
328340
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0
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Other cardiovascular diseases
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Eye
328618
328618
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0
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Normal eye development and function
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Intervention/exposure
Study type
Interventional
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Description of intervention(s) / exposure
Upon consent, participants will undergo non-mydriatic retinal photography for both eyes. Participants will not be dilated and images will be taken for both eyes. A trained clinical trial research assistant of the research team will take the retinal images for the participants, which takes around 5-10 minutes. If the image quality is insufficient (graded as "ungradable" by the artificial intelligence system), research assistants will try up to three attempts to get good-quality images. The session will be delivered in a one-on-one and face-to-face mode. Retinal images taken will then be transferred to an artificial intelligence system that we are testing and a retina-predicted cardiovascular disease (CVD) risk score will be generated. Image quality will be assessed by the artificial intelligence system before generating the retina-predicted CVD risk score. If the image quality is ungradable, the retina-predicted CVD risk score will be shown as not applicable. Besides retinal photography, participants will be asked to complete a health survey, and a satisfaction survey about their experiences of using the artificial intelligence system. Information used for well-established CVD risk score calculation, including blood pressure and lipid results is collected. If lipids are not available, research assistants will measure the weight and height of the participants. The whole session requires a once-off visit of 40 minutes to one hour. The trial is carried out at general practitioner clinics. Adherence will be determined by the completion status on the RedCap platform which is recorded by the research assistants.
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Intervention code [1]
327098
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Early detection / Screening
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Intervention code [2]
327269
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Prevention
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Comparator / control treatment
No control group
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Control group
Uncontrolled
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Outcomes
Primary outcome [1]
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The diagnostic accuracy of retina-predicted cardiovascular disease (rpCVD) risk score for detecting moderate/high CVD risk
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Assessment method [1]
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Sensitivity, specificity, accuracy, and positive and negative predictive value of the artificial intelligence system in detecting moderate/high retinal-predicted cardiovascular risk will be assessed relative to the reference standard, the well-established cardiovascular disease risk scores (calculated from the health factors collected during the visit).
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Timepoint [1]
336192
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Assessed at the conclusion of the study.
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Primary outcome [2]
336193
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The reliability of retina-predicted cardiovascular disease (rpCVD) risk score by comparing with well-established risk-factor-based cardiovascular disease risk calculators
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Assessment method [2]
336193
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Kappa statistics, correlation coefficient, mean difference and limits of agreement between the retina-predicted cardiovascular disease risk scores graded by the artificial intelligence algorithm and the well-established cardiovascular disease risk score calculated from the health factors collected during the visit.
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Timepoint [2]
336193
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Assessed at the conclusion of the study.
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Secondary outcome [1]
427275
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The satisfaction of patients using the retina-predicted cardiovascular disease (rpCVD) screening model.
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Assessment method [1]
427275
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A study-specific survey using 5-point Likert scale and open-ended questions will be used to assess the patients' satisfaction with the artificial intelligence system.
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Timepoint [1]
427275
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Assessed immediately after the patient uses the artificial intelligence system and receives the report during the once-off visit.
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Secondary outcome [2]
427276
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The proportion of moderate/high risk participants detected by the retina-predicted cardiovascular disease (rpCVD) screening model
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Assessment method [2]
427276
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Descriptive statistics for the moderate/high-risk detection rate by the retina-predicted cardiovascular disease screening system.
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Timepoint [2]
427276
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Assessed at the conclusion of the study.
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Secondary outcome [3]
428308
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The feasibility of the retinal-predicted cardiovascular disease risk score screening system in primary care clinics.
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Assessment method [3]
428308
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Feasibility will be determined by the proportion of the participants with gradable retina-predicted cardiovascular disease risk score results by the artificial intelligence system among all participants who undertake the intervention.
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Timepoint [3]
428308
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Assessed at the conclusion of the study.
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Secondary outcome [4]
428792
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The satisfaction of support staff and health-care providers using the retina-predicted cardiovascular disease (rpCVD) screening model.
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Assessment method [4]
428792
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A study-specific survey using 5-point Likert scale and open-ended questions will be used to assess the supporting staff and health-care providers' satisfaction with the artificial intelligence system.
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Timepoint [4]
428792
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Assessed at the conclusion of the study at specific study sites.
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Eligibility
Key inclusion criteria
Patients who have completed all or parts of a cardiovascular disease risk assessment in the past six months and are aged between 45 and 70 years old, will be identified by the research team as eligible to participate.
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Minimum age
45
Years
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Maximum age
70
Years
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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
Participants with medical conditions necessitating immediate or urgent medical interventions.
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Study design
Purpose of the study
Prevention
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Allocation to intervention
Non-randomised trial
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Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
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Methods used to generate the sequence in which subjects will be randomised (sequence generation)
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Masking / blinding
Open (masking not used)
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Who is / are masked / blinded?
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Intervention assignment
Single group
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Other design features
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Phase
Not Applicable
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Type of endpoint/s
Efficacy
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Statistical methods / analysis
All rpCVD will be compared with well-established risk-factor-based CVD risk scores. The well-established risk score will be considered as the reference standard for the accuracy of the rpCVD. The indicators for accuracy include sensitivity, specificity, accuracy, positive and negative predictive value, and area under curve (AUC). The indicators for reliability include limits of agreement between rpCVD and well-established risk factors, mean absolute error for continuous risk values, and kappa statistic for categorical risk levels.
Assessment of end-user acceptability will be determined by the positive response rate/screening rate. The responses to the 5-point Likert scale question will be analysed using the “document variable statistics” function in MAXQDA software. Data from the open-ended questionnaire will be analysed thematically. All themed information will be shared for review by the project steering committee.
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Recruitment
Recruitment status
Recruiting
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Date of first participant enrolment
Anticipated
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Actual
19/06/2023
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Date of last participant enrolment
Anticipated
30/06/2024
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Actual
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Date of last data collection
Anticipated
30/06/2024
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Actual
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Sample size
Target
600
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Accrual to date
227
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Final
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Recruitment in Australia
Recruitment state(s)
VIC
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Funding & Sponsors
Funding source category [1]
314912
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Government body
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Name [1]
314912
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National Health and Medical Research Council (NHMRC) Medical Research Future Fund
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Address [1]
314912
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Level 15, 595 Collins Street Melbourne VIC 3000
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Country [1]
314912
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Australia
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Funding source category [2]
315109
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Commercial sector/Industry
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Name [2]
315109
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Eyetelligence Pty Ltd
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Address [2]
315109
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Level-14/333 Collins St, Melbourne VIC 3000
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Country [2]
315109
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Australia
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Primary sponsor type
Other
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Name
Centre for Eye Research Australia
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Address
Level 7/32 Gisborne St, East Melbourne VIC 3002
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Country
Australia
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Secondary sponsor category [1]
316919
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None
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Name [1]
316919
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Address [1]
316919
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Country [1]
316919
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
313904
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St Vincent’s Hospital (Melbourne) Human Research Ethics Committee
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Ethics committee address [1]
313904
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41 Victoria Parade Fitzroy VIC 3065
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Ethics committee country [1]
313904
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Australia
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Date submitted for ethics approval [1]
313904
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17/01/2023
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Approval date [1]
313904
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23/02/2023
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Ethics approval number [1]
313904
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Summary
Brief summary
Researchers at the Centre for Eye Research Australia (CERA) in collaboration with industry partner Eyetelligence Pty Ltd have developed a system integrating retinal photography and artificial intelligence (AI) to predict the risk of heart diseases. The retina is located at the back of the eye and has the important ability to sense vision. When the retina is photographed, it shows small vessels that can indicate the health of your heart. The cardiovascular disease (CVD) risk score refers to the probability of developing CVD events in the future. This project aims to assess the real-world impact, accuracy, and feasibility of the rpCVD screening system in primary care settings in Australia.
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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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Prof Mingguang He
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Address
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Level 7/32 Gisborne St, East Melbourne VIC 3002, Centre for Eye Research Australia
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Country
129738
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Australia
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Phone
129738
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+610399298361
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Fax
129738
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Email
129738
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[email protected]
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Contact person for public queries
Name
129739
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Mingguang He
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Address
129739
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Level 7/32 Gisborne St, East Melbourne VIC 3002, Centre for Eye Research Australia
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Country
129739
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Australia
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Phone
129739
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+610399298361
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Fax
129739
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Email
129739
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[email protected]
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Contact person for scientific queries
Name
129740
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Mingguang He
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Address
129740
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Level 7/32 Gisborne St, East Melbourne VIC 3002, Centre for Eye Research Australia
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Country
129740
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Australia
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Phone
129740
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+610399298361
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Fax
129740
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Email
129740
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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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