Diagnostic Accuracy of IDX-DR for Detecting Diabetic Retinopathy: A Systematic Review and Meta-Analysis

Khan Z 1 , Gaidhane AM 2 , Singh M 3 , Ganesan S 4 , Kaur M 5 , Sharma GC 6 Show all authors , Rani P 7 , Sharma R 8 , Thapliyal S 9 , Kushwaha M 10 , Kumar H 11 , Agarwal RK 12 , Shabil M 13 , Verma L 14 , Sidhu A 15 , Manan NBA 16 , Bushi G 17 , Mehta R 18 , Sah S 19 , Satapathy P 20 , Samal SK 21

Affiliations 

  • 1 Evidence for Policy and Learning, Global Center for Evidence Synthesis (Z.K.), Chandigarh, Punjab, India
  • 2 Jawaharlal Nehru Medical College, and Global Health Academy (A.M.G), School of Epidemiology and Public Health, Datta Meghe Institute of Higher Education, Wardha, Maharashtra, India
  • 3 Center for Global Health Research (M.S.), Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
  • 4 Department of Chemistry and Biochemistry (S.G.), School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India
  • 5 Department of Allied Healthcare and Sciences (M.K.), Vivekananda Global University, Jaipur, Rajasthan, India
  • 6 Department of Endocrinology (G.C.S.), NIMS University, Jaipur, Rajasthan, India
  • 7 Chandigarh Pharmacy College (P.R.), Chandigarh Group of College, Mohali, Punjab, India
  • 8 Department of Chemistry (R.S.), Raghu Engineering College, Visakhapatnam, Andhra Pradesh, India
  • 9 Uttaranchal Institute of Technology (S.T.), Uttaranchal University, Uttarakhand, India
  • 10 IES Institute of Pharmacy (M.K.), IES University, Bhopal, Madhya Pradesh, India
  • 11 New Delhi Institute of Management (H.K.), Tughlakabad Institutional Area, New Delhi, India
  • 12 Department of Microbiology (R.K.A.), Graphic Era (Deemed to be University), Dehradun, Uttarakhand, India
  • 13 Noida Institute of Engineering and Technology (Pharmacy Institute) (M.S.), Greater Noida, Uttar Pradesh, India
  • 14 Centre of Research Impact and Outcome (L.V.), Chitkara University, Rajpura, Punjab, India
  • 15 Chitkara Centre for Research and Development (A.S.), Chitkara University, Himachal Pradesh, India
  • 16 University of Cyberjaya, Persiaran Bestari (N.B.A.M.), Cyber 11, Cyberjaya, Selangor Darul Ehsan, Malaysia
  • 17 School of Pharmaceutical Sciences (G.B.), Lovely Professional University, Phagwara, Punjab, India
  • 18 Clinical Microbiology (R.M.), RDC, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, India
  • 19 Department of Paediatrics (S.S.), Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India; Department of Public Health Dentistry (S.S.), Dr. D.Y. Patil Dental College and Hospital, Dr. D.Y. Patil Vidyapeeth, Pune, Maharashtra, India
  • 20 University Center for Research and Development (P.S.), Chandigarh University, Mohali, Punjab, India; Medical Laboratories Techniques Department (P.S.), AL-Mustaqbal University, Hillah, Babil, Iraq
  • 21 Evidence for Policy and Learning, Global Center for Evidence Synthesis (Z.K.), Chandigarh, Punjab, India; Unit of Immunology and Chronic Disease (S.K.S.), Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. Electronic address: samalshaileshkumar@gmail.com
Am J Ophthalmol, 2025 Feb 20;273:192-204.
PMID: 39986640 DOI: 10.1016/j.ajo.2025.02.022

Abstract

PURPOSE: Diabetic retinopathy (DR) is a leading cause of vision loss worldwide, making early detection critical to prevent blindness. IDX-DR, an FDA-approved autonomous artificial intelligence (AI) system, has emerged as an innovative solution to improve access to DR screening. This systematic review and meta-analysis aimed to evaluate the diagnostic accuracy of IDX-DR in detecting diabetic retinopathy.

DESIGN: Systematic review and meta-analysis.

METHODS: A comprehensive literature search was conducted across PubMed, Embase, Scopus and Web of Science, identifying studies published through October 5, 2024. Studies involving adult patients with Type 1 or Type 2 diabetes and reporting diagnostic metrics such as sensitivity and specificity were included. The primary outcomes were pooled sensitivity and specificity of IDX-DR. A bivariate random-effects model was used for meta-analysis, and summary receiver operating characteristic (SROC) curves were generated to assess diagnostic performance. Statistical analyses were performed using MetaDisc software version 2.0.

RESULTS: Thirteen studies involving 13,233 participants met the inclusion criteria. IDX-DR's pooled sensitivity was 0.95 (95% CI: 0.82-0.99), and its pooled specificity was 0.91 (95% CI: 0.84-0.95). The SROC curve confirmed IDX-DR's high diagnostic accuracy in detecting diabetic retinopathy across various clinical environments. The AUC value of 0.95 demonstrated high sensitivity and specificity, indicating a robust diagnostic performance for IDX-DR in detecting diabetic retinopathy.

CONCLUSION: IDX-DR is a highly effective diagnostic tool for diabetic retinopathy screening, with robust sensitivity and good specificity. Its integration into clinical practice, especially in resource-limited settings, can potentially improve early detection and reduce vision loss. However, careful implementation is needed to address challenges such as over-diagnosis and ensure the tool complements clinical judgment. Future studies should explore the long-term impacts of AI-based screening and address ethical considerations surrounding its use.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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