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Background: Planned gene therapies for retinitis pigmentosa (RP) depend on viable photoreceptors for efficacy. Understanding disease severity at presentation, and drivers that influence time to presentation is important when planning interventions. We examined features that influence RP severity at initial presentation., Methods: Multi-centre retrospective cohort study of RP patients at initial presentation. Disease severity was scored using ellipsoid zone (EZ) width on SD-OCT and logistic regression used to determine risk factors for advanced disease at presentation., Results: A total of 146 unrelated RP patients were included. Median age at onset and presentation was 40.5 (range 1-74) and 50.1 (range 3.9-81.8), respectively. Severe disease (<5° of remaining EZ width) was present in 28.1% of cases at presentation. Patients with family history of RP had greater odds of severe disease (OR 3.29, 95% CI 1.56, 6.95; p = 0.002), while male gender, race, age, syndromic features, and socioeconomic status did not. Patients with affected siblings (median EZ width 6.2°; p = 0.01), but not affected parents (median EZ width 9.4°; p = 0.99), presented with severe EZ loss compared to patients without family history (median EZ width 13.1°). Patients with affected siblings had delayed presentation (≥5 years; OR 5.76, 95% CI 1.817, 18.262; p = 0.003) compared to patients without family history., Conclusions: Family history influences the stage of disease at which RP patients initially seek ophthalmology review. This has implications for patient counselling and the number of patients who may benefit from future therapies., (© 2024. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)

Background/aims: To compare the performance of generative versus retrieval-based chatbots in answering patient inquiries regarding age-related macular degeneration (AMD) and diabetic retinopathy (DR)., Methods: We evaluated four chatbots: generative models (ChatGPT-4, ChatGPT-3.5 and Google Bard) and a retrieval-based model (OcularBERT) in a cross-sectional study. Their response accuracy to 45 questions (15 AMD, 15 DR and 15 others) was evaluated and compared. Three masked retinal specialists graded the responses using a three-point Likert scale: either 2 (good, error-free), 1 (borderline) or 0 (poor with significant inaccuracies). The scores were aggregated, ranging from 0 to 6. Based on majority consensus among the graders, the responses were also classified as 'Good', 'Borderline' or 'Poor' quality., Results: Overall, ChatGPT-4 and ChatGPT-3.5 outperformed the other chatbots, both achieving median scores (IQR) of 6 (1), compared with 4.5 (2) in Google Bard, and 2 (1) in OcularBERT (all p ≤8.4×10 -3 ). Based on the consensus approach, 83.3% of ChatGPT-4's responses and 86.7% of ChatGPT-3.5's were rated as 'Good', surpassing Google Bard (50%) and OcularBERT (10%) (all p ≤1.4×10 -2 ). ChatGPT-4 and ChatGPT-3.5 had no 'Poor' rated responses. Google Bard produced 6.7% Poor responses, and OcularBERT produced 20%. Across question types, ChatGPT-4 outperformed Google Bard only for AMD, and ChatGPT-3.5 outperformed Google Bard for DR and others., Conclusion: ChatGPT-4 and ChatGPT-3.5 demonstrated superior performance, followed by Google Bard and OcularBERT. Generative chatbots are potentially capable of answering domain-specific questions outside their original training. Further validation studies are still required prior to real-world implementation., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Patients requiring coronary artery bypass grafting (CABG) have multiple co-morbidities which need to be considered in totality when determining surgical risks. The objective of this study is to evaluate short-term and long-term mortality rates of CABG surgery, as well as to identify the most significant risk factors for mortality after isolated CABG., Methods: All patients with complete dataset who underwent isolated CABG between January 2008 and December 2017 were included. Univariate and multivariate Cox regression was performed to determine the risk factors for all-cause mortality. Classification and regression tree analysis was performed to identify the relative importance of these risk factors., Results: 3,573 patients were included in the study. Overall mortality rate was 25.7%. In-hospital mortality rate was 1.62% overall. 30-day, 1-year, 5-year, 10-year and 14.5-year mortality rates were 1.46%, 2.94%, 9.89%, 22.79% and 36.30% respectively. Factors associated with death after adjustment for other risk factors were older age, lower body mass index (BMI), hypertension, diabetes mellitus, chronic obstructive pulmonary disease, pre-operative renal failure on dialysis, higher last pre-operative creatinine level, lower estimated glomerular filtration rate (eGFR), heart failure, lower left ventricular ejection fraction and New York Heart Association class II, III and IV. Additionally, female gender and logistic EuroSCORE were associated with death on univariate Cox analysis, but not associated with death after adjustment with multivariate Cox analysis. Using CART analysis, the strongest predictor of mortality was pre-operative eGFR < 46.9, followed by logistic EuroSCORE ≥ 2.4., Conclusion: Poorer renal function, quantified by a lower eGFR, is the best predictor of post-CABG mortality. Amongst other risk factors, logistic EuroSCORE, age, diabetes and BMI had a relatively greater impact on mortality. Patients with chronic kidney disease stage 3B and above are at highest risk for mortality. We hope these findings heighten awareness to optimise current medical therapy in preserving renal function upon diagnosis of any atherosclerotic disease and risk factors contributing to coronary artery disease., (© 2024. The Author(s).)

Background: Diabetic retinopathy (DR) and diabetic macular edema (DME) are major causes of visual impairment that challenge global vision health. New strategies are needed to tackle these growing global health problems, and the integration of artificial intelligence (AI) into ophthalmology has the potential to revolutionize DR and DME management to meet these challenges., Main Text: This review discusses the latest AI-driven methodologies in the context of DR and DME in terms of disease identification, patient-specific disease profiling, and short-term and long-term management. This includes current screening and diagnostic systems and their real-world implementation, lesion detection and analysis, disease progression prediction, and treatment response models. It also highlights the technical advancements that have been made in these areas. Despite these advancements, there are obstacles to the widespread adoption of these technologies in clinical settings, including regulatory and privacy concerns, the need for extensive validation, and integration with existing healthcare systems. We also explore the disparity between the potential of AI models and their actual effectiveness in real-world applications., Conclusion: AI has the potential to revolutionize the management of DR and DME, offering more efficient and precise tools for healthcare professionals. However, overcoming challenges in deployment, regulatory compliance, and patient privacy is essential for these technologies to realize their full potential. Future research should aim to bridge the gap between technological innovation and clinical application, ensuring AI tools integrate seamlessly into healthcare workflows to enhance patient outcomes., (© 2024. The Author(s).)

Color fundus photography (CFP) and Optical coherence tomography (OCT) images are two of the most widely used modalities in the clinical diagnosis and management of retinal diseases. Despite the widespread use of multimodal imaging in clinical practice, few methods for automated diagnosis of eye diseases utilize correlated and complementary information from multiple modalities effectively. This paper explores how to leverage the information from CFP and OCT images to improve the automated diagnosis of retinal diseases. We propose a novel multimodal learning method, named geometric correspondence-based multimodal learning network (GeCoM-Net), to achieve the fusion of CFP and OCT images. Specifically, inspired by clinical observations, we consider the geometric correspondence between the OCT slice and the CFP region to learn the correlated features of the two modalities for robust fusion. Furthermore, we design a new feature selection strategy to extract discriminative OCT representations by automatically selecting the important feature maps from OCT slices. Unlike the existing multimodal learning methods, GeCoM-Net is the first method that formulates the geometric relationships between the OCT slice and the corresponding region of the CFP image explicitly for CFP and OCT fusion. Experiments have been conducted on a large-scale private dataset and a publicly available dataset to evaluate the effectiveness of GeCoM-Net for diagnosing diabetic macular edema (DME), impaired visual acuity (VA) and glaucoma. The empirical results show that our method outperforms the current state-of-the-art multimodal learning methods by improving the AUROC score 0.4%, 1.9% and 2.9% for DME, VA and glaucoma detection, respectively.

Purpose: To describe the early experiences of patients with neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV) whose treatment was switched to faricimab from other anti-vascular endothelial growth factor (VEGF) agents., Methods: This is a prospective cohort of eyes with nAMD and PCV that were previously treated with anti-VEGF agents other than faricimab. We evaluated visual acuity (VA), central subfield thickness (CST), macular volume (MV), pigment epithelial detachment (PED) height, and choroidal thickness (CT) after one administration of faricimab. Where present, fluid was further evaluated according to intraretinal fluid (IRF), subretinal fluid (SRF), or within PED., Results: Seventy-one eyes from 71 patients were included (45.07% PCV and 54.93% typical nAMD). The mean [standard deviation (± SD)] VA, CST, and MV improved from 0.50 logMAR (± 0.27 logMAR) to 0.46 logMAR (± 0.27 logMAR) ( p = 0.20), 383.35 µm (± 111.24 µm) to 322.46 µm (± 103.89 µm ( p < 0.01), and 9.40 mm 3 (± 1.52 mm 3 ) to 8.75 mm 3 (± 1.17 mm 3 ) ( p < 0.01) from switch to post switch visit, respectively. The CT reduced from 167 µm (± 151 µm) to 149 µm (± 113 µm) ( p < 0.01). There was also a significant reduction in the maximum PED height between visits [302.66 µm (± 217.97 µm)] and the post switch visit [236.66 µm (± 189.05 µm); p < 0.01]. This difference was greater in PEDs that were predominantly serous in nature. In the eyes with typical nAMD ( n = 39), improvements were significant for CST, MV, CT, and PED. In the eyes with PCV ( n = 32), only reductions in CT were statistically significant, while VA, CST, MV, and PED only showed numerically smaller improvements. One patient developed mild vitritis without vasculitis, which resolved with topical steroids with no sequelae., Conclusions: In our case series of Asian nAMD patients, switching to faricimab was associated with a stable VA and meaningful anatomical improvements, particularly with typical nAMD subtypes., Competing Interests: CMGC: Consultant/Speaker for Roche, Bayer, Boehringer Ingelheim; KT: Consultant for Roche, Novartis, Bayer; GT: Consultant for Roche, Novartis, Bayer; AT: Consultant/Advisor for Novartis, Bayer, Roche, Zeiss, Nidek. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ibrahim, Teo, Tan, Chan, Chandrasekaran, Lee, Tan, Mathur, Chan, Sim, Tan, Yeo and Cheung.)

Purpose: There are major gaps in our knowledge of hereditary ocular conditions in the Asia-Pacific population, which comprises approximately 60% of the world's population. Therefore, a concerted regional effort is urgently needed to close this critical knowledge gap and apply precision medicine technology to improve the quality of lives of these patients in the Asia-Pacific region., Design: Multi-national, multi-center collaborative network., Methods: The Research Standing Committee of the Asia-Pacific Academy of Ophthalmology and the Asia-Pacific Society of Eye Genetics fostered this research collaboration, which brings together renowned institutions and experts for inherited eye diseases in the Asia-Pacific region. The immediate priority of the network will be inherited retinal diseases (IRDs), where there is a lack of detailed characterization of these conditions and in the number of established registries., Results: The network comprises 55 members from 35 centers, spanning 12 countries and regions, including Australia, China, India, Indonesia, Japan, South Korea, Malaysia, Nepal, Philippines, Singapore, Taiwan, and Thailand. The steering committee comprises ophthalmologists with experience in consortia for eye diseases in the Asia-Pacific region, leading ophthalmologists and vision scientists in the field of IRDs internationally, and ophthalmic geneticists., Conclusions: The Asia Pacific Inherited Eye Disease (APIED) network aims to (1) improve genotyping capabilities and expertise to increase early and accurate genetic diagnosis of IRDs, (2) harmonise deep phenotyping practices and utilization of ontological terms, and (3) establish high-quality, multi-user, federated disease registries that will facilitate patient care, genetic counseling, and research of IRDs regionally and internationally., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)