ArticleClinical ophthalmology (Auckland, N.Z.)2025
Comparison of the Aireen System with Telemedicine Evaluation by an Ophthalmologist - A Real-World Study.
Article in Clinical ophthalmology (Auckland, N.Z.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Artificial Intelligence-Based Medical Devices for Diabetic Retinopathy Screening in the European Union.Ophthalmology and therapy · 2026Review
- Systematic review and meta-analysis of regulator-approved deep learning systems for fundus diabetic retinopathy detections.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aimed to compare general ophthalmologists, retina specialists, and Aireen AI screening system with the clinical reference standard of a three-member high-level expert committee for diabetic retinopathy (DR) in the evaluation of fundus images for DR. Patients and Methods: The study was designed as a diagnostic, multicenter, cross-sectional, non-randomized diagnostic study. The cohort included in the clinical investigation consisted of 1274 patients with diabetes mellitus (DM) type I or II. Each patient underwent one-field fundus photography using a non-mydriatic camera to assess findings of DR. One hundred and nineteen subjects (9.3%) were excluded from the clinical investigation based on Aireen system assessment. In the clinical investigation, all images were assessed at three independent levels of evaluation: 1) general ophthalmologists (GO) - without subspecialty training in the retina; 2) retina specialists (RS); and 3) system Aireen. In cases where there may be disagreements amongst groups, the image is referred for assessment by the Diabetic Retinopathy Board (DRB). Results: The overall prevalence of any DR was 31.9% (368 cases out of 1154 DM), according to the DRB. Overall concordance between AI system Aireen and GO and RS assessments in the detection of DR from fundus photography occurred in 734 cases (63.6%). The number of disagreements between Aireen system, GO and RS evaluation occurred in 420 (36.4%) cases. Sensitivity for GO was 87.0% (95% CI: 83.6; 90.4), for RS was 82.9% (95% CI: 79.1; 86.7), and for AI system Aireen was 92.1% (95% CI: 89.3; 94.9). Specificity was 76.5% (95% CI: 73.5; 79.5), 81.2% (95% CI: 78.5; 83.9), and 90.7% (95% CI: 88.7; 92.7) for GO, RS and AI system Aireen, respectively. Conclusion: This real-world study illustrates the potential use of AI system Aireen in screening for DR. It exhibits higher sensitivity and specificity compared to telemedicine evaluation of one field fundus image.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.