FULL DETAILS (Read-only)  -> Click Here to Create PDF for Current Dataset of Trial
CTRI Number  CTRI/2026/03/106486 [Registered on: 18/03/2026] Trial Registered Prospectively
Last Modified On: 26/05/2026
Post Graduate Thesis  No 
Type of Trial  Observational 
Type of Study   Cross Sectional Study 
Study Design  Other 
Public Title of Study   Clinical validation of DR AI software 
Scientific Title of Study   Clinical Validation of an Autonomous Online AI-based diagnostic system for the Detection of Diabetic Retinopathy 
Trial Acronym  NIL 
Secondary IDs if Any  
Secondary ID  Identifier 
NIL  NIL 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Dr Lavanya KC 
Designation  Medical Director 
Affiliation  Ravi Superspeciality Eye Hospital, A Unit of Oculus Eye Organisation, Bangalore  
Address  Amrutahalli, Ravi Superspeciality Eye Hospital, A Unit of Oculus Eye Organisation, Bangalore

Bangalore
KARNATAKA
560092
India 
Phone  9449136311  
Fax    
Email  lavanyakc4686@gmail.com  
 
Details of Contact Person
Scientific Query
 
Name  Aparna Gunda 
Designation  Clinical Research Head 
Affiliation  Oivi Tech 
Address  B block, 3rd floor, Sree rama Deevena,
21, Ulsoor Rd, Yellappa Garden,
Bangalore
KARNATAKA
560008
India 
Phone  9966619702  
Fax    
Email  aparna@oivi.co  
 
Details of Contact Person
Public Query
 
Name  Khaleel Udyawar 
Designation  CTO and Co-Founder 
Affiliation  Oivi Tech 
Address  B block, 3rd floor, Sree rama Deevena,

Bangalore
KARNATAKA
560008
India 
Phone  919886925921  
Fax    
Email  khaleel@oivi.co  
 
Source of Monetary or Material Support  
Oivi Tech Pvt Ltd, Sree Rama Deevena - 3rd Floor B Block, No 21 Ulsoor Road, Bengaluru-560 008, Karnataka India  
 
Primary Sponsor  
Name  Oivi Tech Pvt Ltd 
Address  Oivi Tech Pvt Ltd, Sree Rama Deevena - 3rd Floor B Block, No 21 Ulsoor Road, Bengaluru 560 008, Karnataka India 
Type of Sponsor  Other [software] 
 
Details of Secondary Sponsor  
Name  Address 
NIL  NIL 
 
Countries of Recruitment     India  
Sites of Study  
No of Sites = 1  
Name of Principal Investigator  Name of Site  Site Address  Phone/Fax/Email 
Dr Lavanya KC  Ravi Superspeciality Eye Hospital, A unit of Oculus Eye Organisation, Bangalore  Amruthahalli
Bangalore
KARNATAKA 
09449136311

lavanyakc4686@gmail.com 
 
Details of Ethics Committee
Modification(s)  
No of Ethics Committees= 2  
Name of Committee  Approval Status 
Sri Sidhhartha Medical COllege   Approved 
Sri Venkateshware Hospital Ethics Committee  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Patients  (1) ICD-10 Condition: E089||Diabetes mellitus due to underlying condition without complications,  
 
Intervention / Comparator Agent  
Type  Name  Details 
Intervention  NIL  NIL 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  90.00 Year(s)
Gender  Both 
Details  1) Before enrollment, a documented diagnosis of diabetes mellitus, e.g.:
a) Documented diagnosis of Haemoglobin A1c (HbA1c) more than or equal to 6.5 percentage within 3 months of study initiation
OR
b) Fasting Plasma Glucose (FPG) more than or equal to 126 mg per dL (7.0 mmol per L) within 10 days of study initiation
2) Age 18 or older
3) Understand the study and volunteer to sign the informed consent
 
 
ExclusionCriteria 
Details  1) Diagnosed with radiation retinopathy or retinal vein occlusion.
2) Floaters
3) Participant is hypersensitive to light
4) Participant recently underwent photodynamic therapy
5) Participant is taking medication that causes photosensitivity
 
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
Measure of sensitivity and specificity for mtmDR against reference standards   Baseline 
 
Secondary Outcome  
Outcome  TimePoints 
NIL  NIL 
 
Target Sample Size   Total Sample Size="281"
Sample Size from India="281" 
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" 
Phase of Trial   N/A 
Date of First Enrollment (India)   30/03/2026 
Date of Study Completion (India) Applicable only for Completed/Terminated trials 
Date of First Enrollment (Global)  Date Missing 
Date of Study Completion (Global) Applicable only for Completed/Terminated trials 
Estimated Duration of Trial   Years="1"
Months="0"
Days="0" 
Recruitment Status of Trial (Global)
Modification(s)  
Open to Recruitment 
Recruitment Status of Trial (India)  Open to Recruitment 
Publication Details   N/A 
Individual Participant Data (IPD) Sharing Statement

Will individual participant data (IPD) be shared publicly (including data dictionaries)?  

Response - NO
Brief Summary  

Diabetes is a burning problem that is on rise worldwide. By 2050 it is estimated that 1.31 billion people will be living with Diabetes Mellitus (DM), most of them with type 2 DM. In 2021, 95.4% of older adult diabetics had disability-adjusted life years (DALYs).  DR is one of the major complications of DM and is the leading cause of vision impairment both in developed and developing countries.  In a recent cross-sectional study conducted in 2021 that investigated the prevalence of DR in DM patients aged above 40 years, it was estimated that an alarming 21 million have vision impairment and 2.4 million are blind due to DR. Interestingly, undiagnosed DM had an odd’s ratio of 2 for vision-threatening DR. A systematic DR screening would reduce this burden to a larger extent.  Although high-income countries have successfully implemented DR screening programs, in countries like India it is partial.  Many nations use 2–4 fields fundus images, this has proven effective with 80–98% sensitivity and 86–100% specificity compared to the traditional seven-field evaluation or dilated clinical examination for DR. 

While numerous DR algorithms exist, a majority have been validated using high-end, expensive fundus cameras. This reliance on costly equipment poses significant challenges, particularly in resource-limited settings and primary care centres, where access to such technology is often constrained. This limitation reduces patient participation in screening programs, hindering early detection efforts.

To address these barriers, the Oivi DR-AI system has been developed to work seamlessly with the Oivi fundus camera—a cost-effective alternative that can capture images quickly and efficiently.

 Every algorithm developed must be validated within the intended population to demonstrate its efficacy and identify associated risks. Validation studies are crucial to establishing the clinical utility of the device in real-world settings. The findings from this study build trust, instil confidence among clinicians, and ultimately encourage the adoption of such innovations, ensuring their effective integration into everyday practice.

 
Close