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

IF 4.1 1区医学 Q1 OPHTHALMOLOGY

American Journal of Ophthalmology Pub Date : 2025-02-20 DOI:10.1016/j.ajo.2025.02.022

ZAID KHAN , ABHAY M GAIDHANE , MAHENDRA SINGH , SUBBULAKSHMI GANESAN , MANDEEP KAUR , GIRISH CHANDRA SHARMA , POOJA RANI , RSK SHARMA , SHAILENDRA THAPLIYAL , MONAM KUSHWAHA , HARISH KUMAR , RAJAT KUMAR AGARWAL , MUHAMMED SHABIL , LOKESH VERMA , AMRITPAL SIDHU , NORHAFIZAH BINTI AB MANAN , GANESH BUSHI , RACHANA MEHTA , SANJIT SAH , PRAKASINI SATAPATHY , SHAILESH KUMAR SAMAL

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引用次数: 0

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.

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来源期刊

American Journal of Ophthalmology 医学-眼科学

CiteScore

9.20

自引率

7.10%

发文量

406

审稿时长

36 days

期刊介绍： The American Journal of Ophthalmology is a peer-reviewed, scientific publication that welcomes the submission of original, previously unpublished manuscripts directed to ophthalmologists and visual science specialists describing clinical investigations, clinical observations, and clinically relevant laboratory investigations. Published monthly since 1884, the full text of the American Journal of Ophthalmology and supplementary material are also presented online at www.AJO.com and on ScienceDirect. The American Journal of Ophthalmology publishes Full-Length Articles, Perspectives, Editorials, Correspondences, Books Reports and Announcements. Brief Reports and Case Reports are no longer published. We recommend submitting Brief Reports and Case Reports to our companion publication, the American Journal of Ophthalmology Case Reports. Manuscripts are accepted with the understanding that they have not been and will not be published elsewhere substantially in any format, and that there are no ethical problems with the content or data collection. Authors may be requested to produce the data upon which the manuscript is based and to answer expeditiously any questions about the manuscript or its authors.