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A Study to Evaluate a Accuracy of the AIVARIX AI-based Application in Detecting Signs C 1-2 Classes of CVD in Outpatients Seeking Consultancy of Phlebologists in the Russian Federation
This study is a multicenter observational study, which is carried out in frame of routine clinical practice in Russia. The program will include patients suggestive to chronic venous diseases (CVDs) including but not limited to those with C1 and C2 classes by CEAP classification, who will be seeking professional phlebologists' consultation. Study conduction is scheduled in Russia in 2022-2023. The planned number of patients is 414
The main goal of this study is to describe the AIVARIX app accuracy in detecting C1 and C2 classes by CEAP classification of chronic venous disease (CVD) in patients who are consulted by phlebologists on symptoms and signs suggestive to CVD. At single visit, investigating physicians (phlebologists) will be assessing and collecting parameters of interest which they should input in eCRF. Following data will be collected at the visit: a signed consent form from a patient, demographic characteristics (age, sex), eligibility of a patient to the inclusion/ non-inclusion criteria, 1 (one) image of skin area of interest, conclusion on presence or absence of CVD or any other pathologic condition(s) made as a result of objective/ instrumental examination. In case there will be any information related to safety of a Servier drug provided, investigating physician will also collect the information and fill in the PV form (Appendix 1).
Age
18 - No limit years
Sex
ALL
Healthy Volunteers
No
Pirogov Russian National Research Medical University
Moscow, Russia
Start Date
December 1, 2022
Primary Completion Date
June 1, 2023
Completion Date
April 1, 2024
Last Updated
September 25, 2024
433
ACTUAL participants
to estimate Sensitivity and Specificity AIVARIX app in detecting C1 and C2 classes of CVD
OTHER
Lead Sponsor
Servier Russia
NCT06813911
NCT07270887
NCT06595784
Data Source & Attribution
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Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.
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