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Purpose: Primary open-angle glaucoma (POAG) has been reported to occur more frequently in Africans, and to follow a more severe course compared to Europeans. We aimed to describe characteristics of POAG presentation and treatment across three ethnic groups from Africa and one from Europe., Methods: We ascertained 151 POAG patients from South African Coloured (SAC) and 94 South African Black (SAB) ethnicity from a university hospital in South Africa. In Tanzania, 310 patients were recruited from a university hospital and a referral hospital. In the Netherlands, 241 patients of European ancestry were included. All patients were over 35 years old and had undergone an extensive ophthalmic examination. Patients were diagnosed according to the ISGEO criteria. A biogeographic ancestry analysis was performed to estimate the proportion of genetic African ancestry (GAA)., Results: The biogeographic ancestry analysis showed that the median proportion of GAA was 97.6% in Tanzanian, 100% in SAB, 34.2% in SAC and 1.5% in Dutch participants. Clinical characteristics at presentation for Tanzanians, SAB, SAC and Dutch participants, respectively: mean age: 63, 57, 66, 70 years (p < 0.001); visual acuity in the worse eye: 1.78, 1.78, 0.3, 0.3 LogMAR (p < 0.001); maximum intraocular pressure of both eyes: 36, 34, 29, 29 mmHg (p anova  < 0.001); maximum vertical cup to disc ratio (VCDR) of both eyes: 0.90, 0.90, 0.84, 0.83 (p < 0.001); mean central corneal thickness: 506, 487, 511, 528 μm (p < 0.001). Fourteen percent of Tanzanian patients presented with blindness (<3/60 Snellen) in the better eye in contrast to only 1% in the Dutch., Conclusion: In this multi-ethnic comparative study, Sub-Saharan Africans present at a younger age with lower visual acuity, higher IOP, larger VCDR, than SAC and Dutch participants. This indicates the more progressive and destructive course in Sub-Saharan Africans., (© 2021 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Objectives: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic optic disc photographs, and to compare this performance to the performance of a large cohort of ophthalmologists and optometrists., Methods: A retrospective study evaluating the diagnostic performance of an AI software (Pegasus v1.0, Visulytix Ltd., London UK) and comparing it with that of 243 European ophthalmologists and 208 British optometrists, as determined in previous studies, for the detection of glaucomatous optic neuropathy from 94 scanned stereoscopic photographic slides scanned into digital format., Results: Pegasus was able to detect glaucomatous optic neuropathy with an accuracy of 83.4% (95% CI: 77.5-89.2). This is comparable to an average ophthalmologist accuracy of 80.5% (95% CI: 67.2-93.8) and average optometrist accuracy of 80% (95% CI: 67-88) on the same images. In addition, the AI system had an intra-observer agreement (Cohen's Kappa, κ) of 0.74 (95% CI: 0.63-0.85), compared with 0.70 (range: -0.13-1.00; 95% CI: 0.67-0.73) and 0.71 (range: 0.08-1.00) for ophthalmologists and optometrists, respectively. There was no statistically significant difference between the performance of the deep learning system and ophthalmologists or optometrists., Conclusion: The AI system obtained a diagnostic performance and repeatability comparable to that of the ophthalmologists and optometrists. We conclude that deep learning based AI systems, such as Pegasus, demonstrate significant promise in the assisted detection of glaucomatous optic neuropathy.

Purpose: To determine the diagnostic accuracy of judging optic disc photographs for glaucoma by ophthalmologists., Design: Evaluation of diagnostic test and technology., Participants: A total of 243 of 875 invited ophthalmologists in 11 European countries., Methods: We determined how well each participant classified 40 healthy eyes and 48 glaucomatous eyes with varying severity of the disease on stereoscopic slides. Duplicate slides were provided for determining intraobserver agreement. All eyes were also imaged with the GDx with variable corneal compensation (GDx-VCC) (Carl Zeiss Meditec AG, Jena, Germany) and the Heidelberg Retina Tomograph (HRT) I (Heidelberg Engineering GmbH, Heidelberg, Germany). Diagnostic accuracies of clinicians were compared with those of the best machine classifiers., Main Outcome Measures: Accuracy of classification, expressed as sensitivity, specificity, and overall accuracy. Intraobserver agreement (kappa)., Results: The overall diagnostic accuracy of ophthalmologists was 80.5% (standard deviation [SD], 6.8; range, 61.4%-94.3%). The machine classifiers outperformed most observers in diagnostic accuracy; the GDx-VCC nerve fiber indicator and the HRT's best classifier correctly classified 93.2% and 89.8% of eyes, respectively. The intraobserver agreement (kappa) varied between -0.13 and 1.0 and was on average good (0.7)., Conclusions: In general, ophthalmologists classify optic disc photographs moderately well for detecting glaucoma. There is, however, large variability in diagnostic accuracy among and agreement within clinicians. Common imaging devices outperform most clinicians in classifying optic discs., Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references., (Copyright 2010 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)