Background: In diabetic retinopathy, early detection and intervention are crucial in preventing vision loss and improving patient outcomes. In the era of artificial intelligence (AI) and machine learning, new promising diagnostic tools have emerged. The IDX-DR machine (Digital Diagnostics, Coralville, IA, USA) represents a diagnostic tool that combines advanced imaging techniques, AI algorithms, and deep learning methodologies to identify and classify diabetic retinopathy. Methods: All patients that participated in our AI-based DR screening were considered for this study. For this study, all retinal images were additionally reviewed retrospectively by two experienced retinal specialists. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for the IDX-DR machine compared to the graders’ responses. Results: We included a total of 2282 images from 1141 patients who were screened between January 2021 and January 2023 at the Jules Gonin Eye Hospital in Lausanne, Switzerland. Sensitivity was calculated to be 100% for ‘no DR’, ‘mild DR’, and ‘moderate DR’. Specificity for no DR’, ‘mild DR’, ‘moderate DR’, and ‘severe DR’ was calculated to be, respectively, 78.4%, 81.2%, 93.4%, and 97.6%. PPV was calculated to be, respectively, 36.7%, 24.6%, 1.4%, and 0%. NPV was calculated to be 100% for each category. Accuracy was calculated to be higher than 80% for ‘no DR’, ‘mild DR’, and ‘moderate DR’. Conclusions: In this study, based in Jules Gonin Eye Hospital in Lausanne, we compared the autonomous diagnostic AI system of the IDX-DR machine detecting diabetic retinopathy to human gradings established by two experienced retinal specialists. Our results showed that the ID-x DR machine constantly overestimates the DR stages, thus permitting the clinicians to fully trust negative results delivered by the screening software. Nevertheless, all fundus images classified as ‘mild DR’ or greater should always be controlled by a specialist in order to assert whether the predicted stage is truly present.

Background/Objectives: Discrepancies in diabetic retinopathy (DR) grading are well-documented, with retinal non-perfusion (RNP) quantification posing greater challenges. This study assessed intergrader agreement in DR evaluation, focusing on qualitative severity grading and quantitative RNP measurement. We aimed to improve agreement through structured consensus meetings. Methods: A retrospective analysis of 100 comparisons from 50 eyes (36 patients) was conducted. Two paired medical retina fellows graded ultra-widefield color fundus photographs (CFP) and fundus fluorescein angiography (FFA) images. CFP assessments included DR severity using the International Clinical Diabetic Retinopathy (ICDR) grading system, DR Severity Scale (DRSS), and predominantly peripheral lesions (PPL). FFA-based RNP was defined as capillary loss with grayscale matching the foveal avascular zone. Weekly adjudication by a senior specialist resolved discrepancies. Intergrader agreement was evaluated using Cohen’s kappa (qualitative DRSS) and intraclass correlation coefficients (ICC) (quantitative RNP). Bland–Altman analysis assessed bias and variability. Results: After eight consensus meetings, CFP grading agreement improved to excellent: kappa = 91% (ICDR DR severity), 89% (DRSS), and 89% (PPL). FFA-based PPL agreement reached 100%. For RNP, the non-perfusion index (NPI) showed moderate overall ICC (0.49), with regional ICCs ranging from 0.40 to 0.57 (highest in the nasal region, ICC = 0.57). Bland–Altman analysis revealed a mean NPI difference of 0.12 (limits: −0.11 to 0.35), indicating acceptable variability despite outliers. Conclusions: Structured consensus training achieved excellent intergrader agreement for DR severity and PPL grading, supporting the clinical reliability of ultra-widefield imaging. However, RNP measurement variability underscores the need for standardized protocols and automated tools to enhance reproducibility. This process is critical for developing robust AI-based screening systems.

The recent outbreak of the severe acute respiratory syndrome coronavirus-2 has been declared a worldwide pandemic by the WHO. Within various multi-organ involvements, several ocular manifestations have been described. We report the case of a patient diagnosed with COVID-19 who presented with a progressive increase of bilateral cotton wool spots over a 1-week period, despite quick and complete recovery of systemic signs of the disease and no ocular symptoms. We followed the evolution of such lesions over a 3-month period. Here, we underline the importance of retinal screening even if no ocular symptom is reported. Furthermore, we demonstrate the essential role of fundus examination as a reflection of systemic vascular changes.

The recent outbreak of the Coronavirus SARS-CoV-2 has been declared a worldwide pandemic. Within various multi-organ involvement, several ocular manifestations have been described, such as conjunctivitis and retinopathy. The prevalence and severity of retinal lesions and their relation to the severity of the systemic disease are unknown. We performed a prospective, observational study on 172 consecutively hospitalized patients with acute confirmed COVID-19 infection. All patients underwent screening widefield fundus photography at the time of hospital admission. Despite no ocular or vision-related symptoms, we found cotton wool spots (CWS) and/or hemorrhages in 19/172 patients (11%). Diabetes history, overweight, and elevated C-reactive protein were more frequently observed among patients with retinal abnormalities, while a history of systemic hypertension was more frequently observed among patients without retinal findings. At a 3-month follow-up visit, CWS had subsided in all patients.

Purpose: To demonstrate immediate closure of macular holes (MHs) with internal limiting membrane (ILM) plug placement and heavy silicone oil (SO) tamponade after pars plana vitrectomy (PPV). Method: A retrospective review was performed of 14 eyes undergoing MH repair with 23-gauge PPV, ILM plug placement, and heavy SO (Densiron Xtra) tamponade. Clinical examination findings, optical coherence tomography (OCT)-confirmed MH closure, and visual acuity (VA) outcomes were evaluated with a follow-up of at least 6 months. Results: Complete MH closure was achieved in all eyes within 24 hours, with total resolution of cysts. No postoperative macular edema or bridging fibrosis was observed. Mean VA improved from 0.25 preoperatively to 0.5 at the final follow-up. Anatomic closure was consistent across all MH subtypes. Conclusions: The ILM plug technique combined with heavy SO tamponade resulted in 100% early MH closure within 24 hours postoperatively, with excellent anatomic improvement and stability, in addition to significant improvement in VA. This approach may represent a viable surgical option in selected complex MH cases.