Pivotal trial to evaluate an Artificial intelligence (AI) diabetic retinopathy grading classifier in the New Zealand population undergoing regular screening for diabetic retinopathy.
Not Applicable
- Conditions
- DiabetesDiabetic retinopathyMetabolic and Endocrine - DiabetesEye - Diseases / disorders of the eye
- Registration Number
- ACTRN12620000488909
- Lead Sponsor
- Dr David Squirrell
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot yet recruiting
- Sex
- All
- Target Recruitment
- 1000
Inclusion Criteria
All patients with diabetes who are attending a DHB funded diabetic retinopathy screening program.
Exclusion Criteria
Vulnerable patients who are unable to give their consent.
Study & Design
- Study Type
- Interventional
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method To compare the accuracy of the grades issued by trained human graders against those issued by the artificial intelligence system. <br>The grades used in this study are those issued by the MoH in their guidance Diabetic Retinal Screening, Grading, Monitoring and Referral Guidance published 2006. Found at https://www.health.govt.nz/system/files/documents/publications/diabetic-retinal-screening-grading-monitoring-referral-guidance-mar16.pdf[4 months]
- Secondary Outcome Measures
Name Time Method To assess the attitudes of patients with diabetes to the concept of having their images being graded by an AI classifier, <br>This will be assessed using the questionnaire developed by Ongena YP,et al (Patients’ views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire. http://link.springer.com/article/10.1007/s00330-019-06486-0) but reading diabetic eye screening rather than radiology. <br>[This outcome will be assessed as the patient is waiting for their retinal screening to be performed and the questionnaire will be collected as they leave the clinic. ]