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The Metaverse has gained wide attention for being the application interface for the next generation of Internet. The potential of the Metaverse is growing, as Web 3·0 development and adoption continues to advance medicine and healthcare. We define the next generation of interoperable healthcare ecosystem in the Metaverse. We examine the existing literature regarding the Metaverse, explain the technology framework to deliver an immersive experience, along with a technical comparison of legacy and novel Metaverse platforms that are publicly released and in active use. The potential applications of different features of the Metaverse, including avatar-based meetings, immersive simulations, and social interactions are examined with different roles from patients to healthcare providers and healthcare organizations. Present challenges in the development of the Metaverse healthcare ecosystem are discussed, along with potential solutions including capabilities requiring technological innovation, use cases requiring regulatory supervision, and sound governance. This proposed concept and framework of the Metaverse could potentially redefine the traditional healthcare system and enhance digital transformation in healthcare. Similar to AI technology at the beginning of this decade, real-world development and implementation of these capabilities are relatively nascent. Further pragmatic research is needed for the development of an interoperable healthcare ecosystem in the Metaverse., Competing Interests: Declaration of competing interest Author DVG reports investment in DoctorBell (acquired by MaNaDr, Mobile Health), AskDr, VISRE, Healthlink, and Shyfts. He reports serving as senior lecturer and faculty advisor to the medical innovation program of NUS, and appointment as physician leader (telemedicine) and general practitioner at Raffles Medical Group (RMG, SGX:$BSL)., (© 2023 The Authors. Published by Elsevier B.V. on behalf of Chang Gung University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Background: The growing global burden of visual impairment necessitates better population eye screening for early detection of eye diseases. However, accessibility to testing is often limited and centralized at in-hospital settings. Furthermore, many eye screening programs were disrupted by the COVID-19 pandemic, presenting an urgent need for out-of-hospital solutions., Objective: This study investigates the performance of a novel remote perimetry application designed in a virtual reality metaverse environment to enable functional testing in community-based and primary care settings., Methods: This was a prospective observational study investigating the performance of a novel remote perimetry solution in comparison with the gold standard Humphrey visual field (HVF) perimeter. Subjects received a comprehensive ophthalmologic assessment, HVF perimetry, and remote perimetry testing. The primary outcome measure was the agreement in the classification of overall perimetry result normality by the HVF (Swedish interactive threshold algorithm-fast) and testing with the novel algorithm. Secondary outcome measures included concordance of individual testing points and perimetry topographic maps., Results: We recruited 10 subjects with an average age of 59.6 (range 28-81) years. Of these, 7 (70%) were male and 3 (30%) were female. The agreement in the classification of overall perimetry results was high (9/10, 90%). The pointwise concordance in the automated classification of individual test points was 83.3% (8.2%; range 75%-100%). In addition, there was good perimetry topographic concordance with the HVF in all subjects., Conclusions: Remote perimetry in a metaverse environment had good concordance with gold standard perimetry using the HVF and could potentially avail functional eye screening in out-of-hospital settings., (©Kang-An Wong, Bryan Chin Hou Ang, Dinesh Visva Gunasekeran, Rahat Husain, Joewee Boon, Krishna Vikneson, Zyna Pei Qi Tan, Gavin Siew Wei Tan, Tien Yin Wong, Rupesh Agrawal. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.10.2023.)

Purpose: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery. Chatbots could fill a pivotal role in the dissemination and easy accessibility of accurate information in a pandemic. In this study, we developed a multi-lingual NLP-based AI chatbot, DR-COVID, which responds accurately to open-ended, COVID-19 related questions. This was used to facilitate pandemic education and healthcare delivery., Methods: First, we developed DR-COVID with an ensemble NLP model on the Telegram platform (https://t.me/drcovid_nlp_chatbot). Second, we evaluated various performance metrics. Third, we evaluated multi-lingual text-to-text translation to Chinese, Malay, Tamil, Filipino, Thai, Japanese, French, Spanish, and Portuguese. We utilized 2,728 training questions and 821 test questions in English. Primary outcome measurements were (A) overall and top 3 accuracies; (B) Area Under the Curve (AUC), precision, recall, and F1 score. Overall accuracy referred to a correct response for the top answer, whereas top 3 accuracy referred to an appropriate response for any one answer amongst the top 3 answers. AUC and its relevant matrices were obtained from the Receiver Operation Characteristics (ROC) curve. Secondary outcomes were (A) multi-lingual accuracy; (B) comparison to enterprise-grade chatbot systems. The sharing of training and testing datasets on an open-source platform will also contribute to existing data., Results: Our NLP model, utilizing the ensemble architecture, achieved overall and top 3 accuracies of 0.838 [95% confidence interval (CI): 0.826-0.851] and 0.922 [95% CI: 0.913-0.932] respectively. For overall and top 3 results, AUC scores of 0.917 [95% CI: 0.911-0.925] and 0.960 [95% CI: 0.955-0.964] were achieved respectively. We achieved multi-linguicism with nine non-English languages, with Portuguese performing the best overall at 0.900. Lastly, DR-COVID generated answers more accurately and quickly than other chatbots, within 1.12-2.15 s across three devices tested., Conclusion: DR-COVID is a clinically effective NLP-based conversational AI chatbot, and a promising solution for healthcare delivery in the pandemic era., Competing Interests: The 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 © 2023 Yang, Ng, Lei, Tan, Wang, Yan, Pargi, Zhang, Lim, Gunasekeran, Tan, Lee, Yeo, Tan, Ho, Tan, Wong, Kwek, Goh, Liu and Ting.)

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract., Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning., Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83., Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology., Competing Interests: DG reports appointment as Physician Leader (Telemedicine) for Raffles Medical Group (SGX:$BSL.SI) and investments in digital health start-ups AskDr, Doctorbell (acquired by MaNaDr), Shyfts, and VISRE. JC reports appointment as a consultant to Boston AI labs. AYL reports grants from Santen, personal fees from Genentech, US FDA, Johnson and Johnson, grants from Carl Zeiss Meditec, personal fees from Topcon, Gyroscope, non-financial support from Microsoft, grants from Regeneron, outside the submitted work; This article does not reflect the views of the US FDA. PK reports having acted as a consultant for DeepMind, Roche, Novartis, Apellis, and BitFount and is an equity owner in Big Picture Medical. He has received speaker fees from Heidelberg Engineering, Topcon, Allergan, and Bayer. AF reports honoraria, advisory board and grant funding from Alcon, Bayer, Novartis, Allergan, Roche, and Syneos Health. AL reports grants from Roche and Novartis, and appointment as a consultant to NotalVision, Allergan, Bayer, WebMD, and Beyeonics. AG reports appointment to provide lectures for Pfizer, Thea, and Polpharma. TS reports appointment as a consultant & advisory board for Bayer Yakuhin, Boehringer-Ingelheim, Novartis, Chugai, Senju, and Santen. DM reports funding support from the Singapore National Medical Research Council (NMRC-CIRG18Nov-0013), and the Duke-NUS Medical School, Singapore (ACP 05/FY2019/P2/06-A60). DM also reports appointment as consultant and Advisory Board Member of Optomed, Finland. TW reports appointment as the deputy group chief executive officer (research and education) of Singapore Health Services, a consultant & advisory board for Allergan, Bayer, Boehringer-Ingelheim, Genentech, Merck, Novartis, Oxurion (formerly ThromboGenics), Roche, and co-founder of Plano. DT reports funding from the following grants for research about AI in healthcare: National Medical Research Council, Singapore (NMRC/HSRG/0087/2018; MOH-000655-00), National Health Innovation Center, Singapore (NHIC-COV19-2005017), SingHealth Fund Limited Foundation (SHF/HSR113/2017), Duke-NUS Medical School, Singapore (Duke-NUS/RSF/2021/0018; 05/FY2020/EX/15-A58), and Agency for Science, Technology and Research (ASTAR), Singapore (A20H4g2141 and A20H4g2141). DT, GL, and TW also report being the co-inventors of a deep learning system for retinal diseases and co-founders of related start-up Eyris; potential conflicts of interests are managed according to institutional policies of the Singapore Health System (SingHealth) and the National University of Singapore (NUS). 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 © 2022 Gunasekeran, Zheng, Lim, Chong, Zhang, Ng, Keel, Xiang, Park, Park, Chandra, Wu, Campbel, Lee, Keane, Denniston, Lam, Fung, Chan, Sadda, Loewenstein, Grzybowski, Fong, Wu, Bachmann, Zhang, Yam, Cheung, Pongsachareonnont, Ruamviboonsuk, Raman, Sakamoto, Habash, Girard, Milea, Ang, Tan, Schmetterer, Cheng, Lamoureux, Lin, van Wijngaarden, Wong and Ting.)

Abstract: The outbreak of the coronavirus disease 2019 has further increased the urgent need for digital transformation within the health care settings, with the use of artificial intelligence/deep learning, internet of things, telecommunication network/virtual platform, and blockchain. The recent advent of metaverse, an interconnected online universe, with the synergistic combination of augmented, virtual, and mixed reality described several years ago, presents a new era of immersive and real-time experiences to enhance human-to-human social interaction and connection. In health care and ophthalmology, the creation of virtual environment with three-dimensional (3D) space and avatar, could be particularly useful in patient-fronting platforms (eg, telemedicine platforms), operational uses (eg, meeting organization), digital education (eg, simulated medical and surgical education), diagnostics, and therapeutics. On the other hand, the implementation and adoption of these emerging virtual health care technologies will require multipronged approaches to ensure interoperability with real-world virtual clinical settings, user-friendliness of the technologies and clinical efficiencies while complying to the clinical, health economics, regulatory, and cybersecurity standards. To serve the urgent need, it is important for the eye community to continue to innovate, invent, adapt, and harness the unique abilities of virtual health care technology to provide better eye care worldwide., Competing Interests: The authors have no funding or conflicts of interest to declare., (Copyright © 2022 Asia-Pacific Academy of Ophthalmology. Published by Wolters Kluwer Health, Inc. on behalf of the Asia-Pacific Academy of Ophthalmology.)

Background: Social media platforms have numerous potential benefits and drawbacks on public health, which have been described in the literature. The COVID-19 pandemic has exposed our limited knowledge regarding the potential health impact of these platforms, which have been detrimental to public health responses in many regions., Objective: This review aims to highlight a brief history of social media in health care and report its potential negative and positive public health impacts, which have been characterized in the literature., Methods: We searched electronic bibliographic databases including PubMed, including Medline and Institute of Electrical and Electronics Engineers Xplore, from December 10, 2015, to December 10, 2020. We screened the title and abstracts and selected relevant reports for review of full text and reference lists. These were analyzed thematically and consolidated into applications of social media platforms for public health., Results: The positive and negative impact of social media platforms on public health are catalogued on the basis of recent research in this report. These findings are discussed in the context of improving future public health responses and incorporating other emerging digital technology domains such as artificial intelligence. However, there is a need for more research with pragmatic methodology that evaluates the impact of specific digital interventions to inform future health policy., Conclusions: Recent research has highlighted the potential negative impact of social media platforms on population health, as well as potentially useful applications for public health communication, monitoring, and predictions. More research is needed to objectively investigate measures to mitigate against its negative impact while harnessing effective applications for the benefit of public health., (©Dinesh Visva Gunasekeran, Alton Chew, Eeshwar K Chandrasekar, Priyanka Rajendram, Vasundhara Kandarpa, Mallika Rajendram, Audrey Chia, Helen Smith, Choon Kit Leong. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.04.2022.)

Ocular involvement is a rare manifestation of tuberculosis. Four key issues historically faced by clinicians when diagnosing and treating ocular tuberculosis - diagnostic uncertainty, naturally heterogeneous presentations, limitations of existing laboratory diagnostic tools, and non-uniform treatment guidelines - continue to test today's physicians. Unparalleled scientific and clinical developments over the past century have greatly expanded the knowledge surrounding this challenging ophthalmic condition. Experience with large volumes of cases at tuberculosis-endemic centres has led to recent growth in knowledge and physician experience, perhaps more so in developing countries. Looking forward, the role of diverse new technologies, including artificial intelligence and proteomics, will advance ocular tuberculosis research. Efforts have been made to address the lack of standardized nomenclature, diagnostic uncertainty, and unvalidated, geographically variable treatment guidelines.

Ophthalmic trauma is a leading cause of preventable monocular blindness worldwide. The prevalence of ophthalmic trauma varies considerably based on geographic location, socio-economic status, age groups, occupation, and cultural practices such as firework celebrations. Clinical registries are known to be valuable in guiding the diagnosis, management, and prognostication of complex diseases. However, there is currently a lack of a centralized international data repository for ophthalmic trauma. We draw lessons from past and existing clinical registries related to ophthalmology and propose a new suitable international multicenter clinical registry for ophthalmic trauma: the International Globe and Adnexal Trauma Epidemiology Study (IGATES). IGATES is hosted on a secure web-based platform which exhibits user-friendly smart features, an integrated Ocular Trauma Score (OTS) prognosis calculator, efficient data collection points, and schematic graphical software. IGATES currently has 37 participating centers globally. The data collected through IGATES will be primarily used to develop a more robust and improved ophthalmic trauma prognostic classification system, the Ocular Trauma Score-2 (OTS-2), which builds on previous systems such as the Birmingham Eye Trauma Terminology System (BETTS) and Ocular Trauma Score (OTS). Furthermore, IGATES will act as a springboard for further research into the epidemiology, diagnosis, and management of ophthalmic trauma. Ultimately, IGATES serves to advance the field of ophthalmic trauma and improve the care that patients with ophthalmic trauma receive., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To explore the all-cause mortality in patients with acquired immune deficiency syndrome (AIDS) and Cytomegalovirus (CMV) retinitis., Methods: A retrospective cohort study of patients with CMV retinitis (CMVR) presented to a tertiary referral center in Singapore from January 1, 2004, through December 31, 2015., Results: A total of 144 patients were studied (87 survived, 11 lost to follow up, 46 died). Patients with bilateral CMVR and six-month follow up CD4 + T cell count < 50 cells/mm 3 have shorter time to mortality, compared to patients with CD4 + T cell count > 50 cells/mm 3 ( p < .001) and unilateral disease ( p = .043). Baseline CD4 + T cell count, size and zone of initial primary retinitis lesions, recurrences of retinitis, and timing of combined antiretroviral therapy (cART) are not significantly associated with mortality., Conclusion: Bilateral ocular involvement and lack of immune recovery in patients with AIDS and CMVR are associated with shorter survival time.

Purpose: To detail the methodology for a novel ocular trauma registry and utilize the registry to determine the demographics, nature of injury, and associations of severe visual loss for open globe injuries (OGI)., Methods: Thirteen hospitals in 7 countries used International Globe and Adnexal Trauma Epidemiology Study (IGATES) platform. Patients presenting between April 2009 and 2020 with OGI (with or without) adnexal involvement or intraocular foreign body (IOFB) were included., Results: Analyses of presenting and final VA, using "severe vision loss" (VA ≤ 6/60) and "no severe loss" (VA > 6/60), were performed. Four hundred fifty-four (64%) patients had VA < 6/60 at presentation and 327 (44.8%) at final follow-up, with a highly significant association between presenting and final VA (p < 0.0001). From the cohort of 746 patients, 37 were missing VA at presentation and 16 at follow-up and complete clinical data was available for 354 patients. The male to female ratio is 6:1, and mean age 36.0 ± 20.0 years old. Relative afferent pupillary defect (RAPD), zone III injury, IOFB, and eyelid injury at presentation were recorded in 50 (6.7%), 55 (7.8%), 97 (13%), and 87 (11.7%) patients, respectively, and were significantly associated with VA < 6/60 at follow-up. Older age, ≥ 61 years, was associated with 3.39 times (95% CI: 1.95-5.89) higher risk than ≤20-year-old patients (p < 0.0001) and males 0.424 times (95% CI: 0.27-0.70) lower risk than female (p = 0.0001) of severe vision loss (SVL)., Conclusion: In OGIs from 13 hospitals, female gender, older age, zone III injury, eyelid injury, and IOFB were associated with higher risk of visual outcome of SVL., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garnered significant attention due to the availability of large amounts of data and digitized ocular images. Currently, AI in Ophthalmology is mainly focused on improving disease classification and supporting decision-making when treating ophthalmic diseases such as diabetic retinopathy, age-related macular degeneration (AMD), glaucoma and retinopathy of prematurity (ROP). However, most of the DL systems (DLSs) developed thus far remain in the research stage and only a handful are able to achieve clinical translation. This phenomenon is due to a combination of factors including concerns over security and privacy, poor generalizability, trust and explainability issues, unfavorable end-user perceptions and uncertain economic value. Overcoming this challenge would require a combination approach. Firstly, emerging techniques such as federated learning (FL), generative adversarial networks (GANs), autonomous AI and blockchain will be playing an increasingly critical role to enhance privacy, collaboration and DLS performance. Next, compliance to reporting and regulatory guidelines, such as CONSORT-AI and STARD-AI, will be required to in order to improve transparency, minimize abuse and ensure reproducibility. Thirdly, frameworks will be required to obtain patient consent, perform ethical assessment and evaluate end-user perception. Lastly, proper health economic assessment (HEA) must be performed to provide financial visibility during the early phases of DLS development. This is necessary to manage resources prudently and guide the development of DLS., (© 2021 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

Competing Interests: Author DG reports directly relevant equity investment in AskDr, an online health community (OHC). 22 Author DG reports other equity investments in Doctorbell (acquired by MaNaDr, Mobile Health), VISRE, and Shyfts that are not relevant to the content of this manuscript. Author DG also reports appointment as Physician Leader (Telemedicine) at Raffles Medical Group, and serving as an advisor to university-affiliated technology developers and start-up companies involved in the development of patient engagement systems in Southeast Asia. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

This study aimed to determine COVID-19-related awareness, knowledge, impact and preparedness among elderly Asians; and to evaluate their acceptance towards digital health services amidst the pandemic. 523 participants (177 Malays, 171 Indians, 175 Chinese) were recruited and underwent standardised phone interview during Singapore's lockdown period (07 April till 01 June 2020). Multivariable logistic regression models were performed to evaluate the associations between demographic, socio-economic, lifestyle, and systemic factors, with COVID-19 awareness, knowledge, preparedness, well-being and digital health service acceptance. The average perception score on the seriousness of COVID-19 was 7.6 ± 2.4 (out of 10). 75.5% of participants were aware that COVID-19 carriers can be asymptomatic. Nearly all (≥ 90%) were aware of major prevention methods for COVID-19 (i.e. wearing of mask, social distancing). 66.2% felt prepared for the pandemic, and 86.8% felt confident with government's handling and measures. 78.4% felt their daily routine was impacted. 98.1% reported no prior experience in using digital health services, but 52.2% felt these services would be helpful to reduce non-essential contact. 77.8% were uncomfortable with artificial intelligence software interpreting their medical results. In multivariable analyses, Chinese participants felt less prepared, and more likely felt impacted by COVID-19. Older and lower income participants were less likely to use digital health services. In conclusion, we observed a high level of awareness and knowledge on COVID-19. However, acceptance towards digital health service was low. These findings are valuable for examining the effectiveness of COVID-19 communication in Singapore, and the remaining gaps in digital health adoption among elderly.

Abstract: Artificial Intelligence (AI), in particular deep learning, has made waves in the health care industry, with several prominent examples shown in ophthalmology. Despite the burgeoning reports on the development of new AI algorithms for detection and management of various eye diseases, few have reached the stage of regulatory approval for real-world implementation. To better enable real-world translation of AI systems, it is important to understand the demands, needs, and concerns of both health care professionals and patients, as providers and recipients of clinical care are impacted by these solutions. This review outlines the advantages and concerns of incorporating AI in ophthalmology care delivery, from both the providers' and patients' perspectives, and the key enablers for seamless transition to real-world implementation., Competing Interests: The authors have no funding or conflicts of interest to declare., (Copyright © 2021 Asia-Pacific Academy of Ophthalmology. Published by Wolters Kluwer Health, Inc. on behalf of the Asia-Pacific Academy of Ophthalmology.)

Competing Interests: Competing interests: RL, BC and HYO are supported by grants from the National Youth Council (NYC) of Singapore and the Medical Grand Challenge (MGC) of the National University of Singapore (NUS). DVG reports investment in DoctorBell (acquired by MaNaDr, Mobile Health), VISRE, AskDr and Shyfts. He declares receipt of travel funding from the Mobile Health Education grant, Commonwealth Fellowship in Innovation award and National Youth Fund award, for clinical research training and collaborations at Oxford University and Stanford University. He reports serving as senior lecturer and faculty advisor to the medical innovation program of NUS.

The coronavirus disease 2019 (COVID-19) pandemic has overwhelmed healthcare services, faced with the twin challenges in acutely meeting the medical needs of patients with COVID-19 while continuing essential services for non-COVID-19 illnesses. The need to re-invent, re-organize and transform healthcare and co-ordinate clinical services at a population level is urgent as countries that controlled initial outbreaks start to experience resurgences. A wide range of digital health solutions have been proposed, although the extent of successful real-world applications of these technologies is unclear. This study aims to review applications of artificial intelligence (AI), telehealth, and other relevant digital health solutions for public health responses in the healthcare operating environment amidst the COVID-19 pandemic. A systematic scoping review was performed to identify potentially relevant reports. Key findings include a large body of evidence for various clinical and operational applications of telehealth (40.1%, n = 99/247). Although a large quantity of reports investigated applications of artificial intelligence (AI) (44.9%, n = 111/247) and big data analytics (36.0%, n = 89/247), weaknesses in study design limit generalizability and translation, highlighting the need for more pragmatic real-world investigations. There were also few descriptions of applications for the internet of things (IoT) (2.0%, n = 5/247), digital platforms for communication (DC) (10.9%, 27/247), digital solutions for data management (DM) (1.6%, n = 4/247), and digital structural screening (DS) (8.9%, n = 22/247); representing gaps and opportunities for digital public health. Finally, the performance of digital health technology for operational applications related to population surveillance and points of entry have not been adequately evaluated.

Background: The COVID-19 pandemic has led to urgent calls for the adoption of telehealth solutions. However, public interest and demand for telehealth during the pandemic remain unknown., Objective: We used an infodemiological approach to estimate the worldwide demand for telehealth services during COVID-19, focusing on the 50 most affected countries and comparing the demand for such services with the level of information and communications technology (ICT) infrastructure available., Methods: We used Google Trends, the Baidu Index (China), and Yandex Keyword Statistics (Russia) to extract data on worldwide and individual countries' telehealth-related internet searches from January 1 to July 7, 2020, presented as relative search volumes (RSV; range 0-100). Daily COVID-19 cases and deaths were retrieved from the World Health Organization. Individual countries' ICT infrastructure profiles were retrieved from the World Economic Forum Report., Results: Across the 50 countries, the mean RSV was 18.5 (SD 23.2), and the mean ICT index was 62.1 (SD 15.0). An overall spike in worldwide telehealth-related RSVs was observed from March 11, 2020 (RSV peaked to 76.0), which then tailed off in June-July 2020 (mean RSV for the period was 25.8), but remained higher than pre-March RSVs (mean 7.29). By country, 42 (84%) manifested increased RSVs over the evaluation period, with the highest observed in Canada (RSV=100) and the United States (RSV=96). When evaluating associations between RSV and the ICT index, both the United States and Canada demonstrated high RSVs and ICT scores (≥70.3). In contrast, European countries had relatively lower RSVs (range 3.4-19.5) despite high ICT index scores (mean 70.3). Several Latin American (Brazil, Chile, Colombia) and South Asian (India, Bangladesh, Pakistan) countries demonstrated relatively higher RSVs (range 13.8-73.3) but low ICT index scores (mean 44.6), indicating that the telehealth demand outstrips the current ICT infrastructure., Conclusions: There is generally increased interest and demand for telehealth services across the 50 countries most affected by COVID-19, highlighting the need to scale up telehealth capabilities, during and beyond the pandemic., (©Mark Yu Zheng Wong, Dinesh Visva Gunasekeran, Simon Nusinovici, Charumathi Sabanayagam, Khung Keong Yeo, Ching-Yu Cheng, Yih-Chung Tham. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 19.02.2021.)

The COVID-19 pandemic has resulted in massive disruptions within health care, both directly as a result of the infectious disease outbreak, and indirectly because of public health measures to mitigate against transmission. This disruption has caused rapid dynamic fluctuations in demand, capacity, and even contextual aspects of health care. Therefore, the traditional face-to-face patient-physician care model has had to be re-examined in many countries, with digital technology and new models of care being rapidly deployed to meet the various challenges of the pandemic. This Viewpoint highlights new models in ophthalmology that have adapted to incorporate digital health solutions such as telehealth, artificial intelligence decision support for triaging and clinical care, and home monitoring. These models can be operationalised for different clinical applications based on the technology, clinical need, demand from patients, and manpower availability, ranging from out-of-hospital models including the hub-and-spoke pre-hospital model, to front-line models such as the inflow funnel model and monitoring models such as the so-called lighthouse model for provider-led monitoring. Lessons learnt from operationalising these models for ophthalmology in the context of COVID-19 are discussed, along with their relevance for other specialty domains., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Tubercular intermediate uveitis (TIU) and panuveitis (TBP) are difficult to manage because of limitations in diagnostic tools and lack of evidence-based treatment guidelines. The Collaborative Ocular Tuberculosis Study (COTS) analyzed treatment regimens and therapeutic outcomes in patients with TIU and TBP. Methods: Multicentre retrospective analysis. Results A total of 138 TIU and 309 TBP patients were included. A total of 382 subjects received antitubercular therapy (ATT) (n = 382/447; 85.4%) and 382 received corticosteroids (n = 382/447; 85.4%). Treatment failure was observed in 78 individuals (n = 78/447; 17.4%), occurring less frequently in patients receiving ATT (n = 66/382; 17.2%) compared to those who did not (n = 12/65; 18.5%). The study did not show any statistically significant therapeutic effect of ATT in patients with TIU and TBP. Conclusion Taking into account the limitations of the retrospective, non-randomized study design, resultant reliance on reported data records, and unequal size of the samples, the current study cannot provide conclusive evidence on the therapeutic benefit of ATT in TIU and TBP.

Purpose : The Collaborative Ocular Tuberculosis Study (COTS) Group sought to address the diagnostic uncertainty through retrospective cohort analysis of treatment regimens and therapeutic outcomes for patients with tubercular Anterior Uveitis (TAU) across international centers. Methods : Multicentre retrospective analysis of patients diagnosed with TAU between January 2004 to December 2014 that had a minimum follow-up of 1 year. Results : One hundred and sixty-five patients were included. One hundred and seven subjects received antitubercular therapy (ATT) (n = 107/165; 64.9%) with all the patients receiving topical steroid therapy. Treatment failure was noted in 17 patients (n = 17/165; 10.3%), more frequently described in patients that received ATT (n = 13/107, 12.2%), than those that did not receive ATT (n = 4/58, 6.9%). Conclusion : In this retrospective study, addition of ATT did not have any statistically significant impact on outcome in patients with TAU.

Purpose: To examine disease profile of tubercular uveitis (TBU) in Paediatric population. Methods: Among 945 patients of the retrospective multinational study by the Collaborative Ocular Tuberculosis Study (COTS)-1, 29 Paediatric patients diagnosed with TBU were analyzed. Results: Mean age of disease presentation was 12.8 (range 4-18 years), with predominance of males (n = 14/20; 70.0%) and Asian ethnicity (n = 25/29; 86.2%). Posterior uveitis (n = 14/28; 50%) was the most frequent uveitis phenotype, with choroidal involvement occurring in 64.7% (n = 11/17). Incidence of optic disc edema and macular edema was higher in children (n = 8/18; 44.4% and n = 5/18; 27.8%, respectively) than in adults (n = 160/942; 16.9% and n = 135/942; 14.3%, respectively). Comparison of optic disc edema between subgroups showed a significant difference ( P =.006 ). All patients received oral corticosteroids, most of them with antitubercular therapy. Treatment failure developed in 4.8% (n = 1/21). Conclusions: Children have a more severe inflammatory response to the disease, and an intensive anti-inflammatory therapeutic regimen is required to achieve a positive treatment outcome.

Purpose : To report the clinical findings, anatomical features, and treatment outcomes in subjects with ocular tuberculosis (OTB) at 24 months in the Collaborative Ocular Tuberculosis Study (COTS)-1. Methods : Of the 945 subjects included in COTS-1, those who completed a 24-month follow-up after completion of treatment were included. The main outcome measure was a number of patients with treatment failure (TF). Results : 228 subjects (120 males; mean age of 42.82 ± 14.73 years) were included. Most common phenotype of uveitis was posterior ( n = 81; 35.53%), and panuveitis ( n = 76; 33.33%). Fifty-two patients (22.81%) had TF. On univariable analysis, odds of high TF was observed with bilaterality (OR: 3.46, p = .003), vitreous haze (OR: 2.14, p = .018), and use of immunosuppressive therapies (OR: 5.45, p = .003). However, only bilaterality was significant in the multiple regression model (OR: 2.84; p = .02). Conclusions : Majority of subjects (>75%) achieved cure in the COTS-1 at 24-month follow-up. The concept of "cure" may be a valuable clinical endpoint in trials for OTB.

Objective: Aim of the study was to examine extent, natural history, and clinical features associated with visual impairment (VI) in patients diagnosed with ocular tuberculosis (OTB) by the Collaborative Ocular Tuberculosis Study (COTS)-1. Methods: Multi-center retrospective cohort study. Main outcomes were VI. Results: A total of 302 patients were included in the study, including 175 patients whose data related to BCVA were available throughout the 2 years of follow up. Mean BCVA grossly improved at 12, 18, and 24 months of follow-up ( p < .001). Mean BCVA was worse at 12-18th month follow-up for patients treated with ATT versus patients who were not treated with ATT, but patients treated with ATT had a statistically significant improvement in BCVA at the 24-month endpoint. Conclusions: OTB is associated with significant visual morbidity, future well-designed prospective studies are warranted to establish the causal association between OTB and visual loss.

Purpose : To contribute a global description of the spectrum of choroidal involvement in tubercular uveitis (TBU). Methods : Retrospective cohort study of TBU patients with choroidal involvement from 25 centers between January 2004 and December 2014. Medical records of patients with a minimum follow-up of 1 year were reviewed. Results : 245 patients were included. The phenotypic variations included serpiginous-like choroiditis (SLC) (46%), tuberculoma (13.5%), multifocal choroiditis (MFC) (9.4%), ampiginous choroiditis (9%), among others. 219 patients were treated with anti-tubercular therapy (ATT) ( n  = 219/245, 89.38%), 229 patients with steroids ( n  = 229/245, 93.47%) and 28 patients with immunosuppressive agents ( n  = 28/245, 11.42%). Treatment failure was noted in 38 patients ( n  = 38/245, 15.5%). Patients with SLC and ampiginous choroiditis appeared to have superior outcomes on survival analysis ( p  = 0.06). Conclusion : This study provides a comprehensive description of choroidal involvement in TBU. Patients with SLC and ampiginous choroiditis may have better clinical outcomes.

Purpose : There is controversy regarding the diagnosis and management of ocular tuberculosis (TB) due to lack of robust evidence. The Collaborative Ocular Tuberculosis Study (COTS) was conducted in stages to enable swift, accurate data collection across 25 participating centers. Method : Data collection was facilitated by a cloud-based data aggregation platform with programmed logic based on anecdotal evidence from uveitis experts corroborated with literature review. Results : The platform enabled standardization of interpretation and collection of data from patient medical records. The pre-programmed logic also ensured the platform only prompted the entry of relevant data based on initial data entered for each unit of analysis. This enabled collection of the vast amounts of data without compromising either of the breadth nor the depth of data collection. Conclusion : The final output from this effort was an in-depth retrospective analysis to facilitate the design of future prospective investigations on ocular TB and develop best practice guidelines.

Background: Tuberculosis (TB) is a major infection that can affect the eye as first and sole presentation without features of systemic disease. Controversy exists regarding diagnosis and management of tubercular uveitis (TBU), further compounded by regional variations in disease expression. Purpose: Collaborative Ocular Tuberculosis Study (COTS)-1 aims to address knowledge deficits through collaboration amongst uveitis specialists across the globe by sharing the data of patients with TBU presented at participating centers from January 2004 to December 2014. Methods: Data collection was facilitated by a novel method of real-time encrypted web-based data entry allowing regular updates as new data and recommendations become available. Results: Information on clinical features, investigation findings, management, and treatment outcomes were reviewed to get an idea about real world scenario. Conclusion: The current review aims to focus on methodology and briefing of published reports from COTS group in COTS-1 study to highlight key messages from this large data.

An international, expert led consensus initiative was set up by the Collaborative Ocular Tuberculosis Study (COTS) group to develop systematic, evidence, and experience-based recommendations for the treatment of ocular TB using a modified Delphi technique process. In the first round of Delphi, the group identified clinical scenarios pertinent to ocular TB based on five clinical phenotypes (anterior uveitis, intermediate uveitis, choroiditis, retinal vasculitis, and panuveitis). Using an interactive online questionnaires, guided by background knowledge from published literature, 486 consensus statements for initiating ATT were generated and deliberated amongst 81 global uveitis experts. The median score of five was considered reaching consensus for initiating ATT. The median score of four was tabled for deliberation through Delphi round 2 in a face-to-face meeting. This report describes the methodology adopted and followed through the consensus process, which help elucidate the guidelines for initiating ATT in patients with choroidal TB.

Purpose of Review: Diabetic retinopathy is the most common specific complication of diabetes mellitus. Traditional care for patients with diabetes and diabetic retinopathy is fragmented, uncoordinated and delivered in a piecemeal nature, often in the most expensive and high-resource tertiary settings. Transformative new models incorporating digital technology are needed to address these gaps in clinical care., Recent Findings: Artificial intelligence and telehealth may improve access, financial sustainability and coverage of diabetic retinopathy screening programs. They enable risk stratifying patients based on individual risk of vision-threatening diabetic retinopathy including diabetic macular edema (DME), and predicting which patients with DME best respond to antivascular endothelial growth factor therapy., Summary: Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening, including artificial intelligence applications in 'real-world settings' and cost-effectiveness studies are summarized. Furthermore, the initial research on the use of artificial intelligence models for diabetic retinopathy risk stratification and management of DME are outlined along with potential future directions. Finally, the need for artificial intelligence adoption within ophthalmology in response to coronavirus disease 2019 is discussed. Digital health solutions such as artificial intelligence and telehealth can facilitate the integration of community, primary and specialist eye care services, optimize the flow of patients within healthcare networks, and improve the efficiency of diabetic retinopathy management.

Background: The benefits of telemedicine include cost savings and decentralized care. Video consultation is one form that enables early detection of deteriorating patients and promotion of self-efficacy in patients who are well but anxious. Abdominal pain is a common symptom presented by patients in emergency departments. These patients could benefit from video consultation, as it enables remote follow-up of patients who do not require admission and facilitates early discharge of patients from overcrowded hospitals., Objective: The study aimed to evaluate the safety and efficacy of the use of digital telereview in patients presenting with undifferentiated acute abdominal pain., Methods: The SAVED study was a prospective randomized controlled trial in which follow-up using existing telephone-based telereview (control) was compared with digital telereview (intervention). Patients with undifferentiated acute abdominal pain discharged from the emergency department observation ward were studied based on intention-to-treat. The control arm received routine, provider-scheduled telereview with missed reviews actively coordinated and rescheduled by emergency department staff. The intervention arm received access to a platform for digital telereview (asynchronous and synchronous format) that enabled patient-led appointment rescheduling. Patients were followed-up for 2 weeks for outcomes of service utilization, efficacy (compliance with their disposition plan), and safety (re-presentation for the same condition)., Results: A total of 70 patients participated, with patients randomly assigned to each arm (1:1 ratio). Patients were a mean age of 40.0 (SD 13.8; range 22-71) years, predominantly female (47/70, 67%), and predominantly of Chinese ethnicity (39/70, 56%). The telereview service was used by 32 patients in the control arm (32/35, 91%) and 18 patients in the intervention arm (18/35, 51%). Most patients in control (33/35, 94%; 95% CI 79.5%-99.0%) and intervention (34/35, 97%; 95% CI 83.4%-99.9%) arms were compliant with their final disposition. There was a low rate of re-presentation at 72 hours and 2 weeks for both control (72 hours: 2/35, 6%; 95% CI 1.0%-20.5%; 2 weeks: 2/35, 6%, 95% CI 1.0%-20.5%) and intervention (72 hours: 2/35, 6%; 95% CI 1.0%-20.5%; 2 weeks: 3/35, 9%, 95% CI 2.2%-24.2%) arms. There were no significant differences in safety (P>.99) and efficacy (P>.99) between the two groups., Conclusions: The application of digital telereview for the follow-up of patients with abdominal pain may be safe and effective. Future studies are needed to evaluate its cost-effectiveness and usefulness for broader clinical application., Trial Registration: ISRCTN Registry ISRCTN28468556; http://www.isrctn.com/ISRCTN28468556., (©Dinesh Visva Gunasekeran, Zhenghong Liu, Win Jim Tan, Joshua Koh, Chiu Peng Cheong, Lay Hong Tan, Chee Siang Lau, Gaik Kheng Phuah, Newsie Donnah A Manuel, Che Chong Chia, Gek Siang Seng, Nancy Tong, May Hang Huin, Suzette Villaluna Dulce, Susan Yap, Kishanti Ponampalam, Hao Ying, Marcus Eng Hock Ong, R Ponampalam. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.06.2020.)

Background: Deep learning is a novel machine learning technique that has been shown to be as effective as human graders in detecting diabetic retinopathy from fundus photographs. We used a cost-minimisation analysis to evaluate the potential savings of two deep learning approaches as compared with the current human assessment: a semi-automated deep learning model as a triage filter before secondary human assessment; and a fully automated deep learning model without human assessment., Methods: In this economic analysis modelling study, using 39 006 consecutive patients with diabetes in a national diabetic retinopathy screening programme in Singapore in 2015, we used a decision tree model and TreeAge Pro to compare the actual cost of screening this cohort with human graders against the simulated cost for semi-automated and fully automated screening models. Model parameters included diabetic retinopathy prevalence rates, diabetic retinopathy screening costs under each screening model, cost of medical consultation, and diagnostic performance (ie, sensitivity and specificity). The primary outcome was total cost for each screening model. Deterministic sensitivity analyses were done to gauge the sensitivity of the results to key model assumptions., Findings: From the health system perspective, the semi-automated screening model was the least expensive of the three models, at US$62 per patient per year. The fully automated model was $66 per patient per year, and the human assessment model was $77 per patient per year. The savings to the Singapore health system associated with switching to the semi-automated model are estimated to be $489 000, which is roughly 20% of the current annual screening cost. By 2050, Singapore is projected to have 1 million people with diabetes; at this time, the estimated annual savings would be $15 million., Interpretation: This study provides a strong economic rationale for using deep learning systems as an assistive tool to screen for diabetic retinopathy., Funding: Ministry of Health, Singapore., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Systematic screening for diabetic retinopathy (DR) has been widely recommended for early detection in patients with diabetes to address preventable vision loss. However, substantial manpower and financial resources are required to deploy opportunistic screening and transition to systematic DR screening programs. The advent of artificial intelligence (AI) technologies may improve access and reduce the financial burden for DR screening while maintaining comparable or enhanced clinical effectiveness. To deploy an AI-based DR screening program in a real-world setting, it is imperative that health economic assessment (HEA) and patient safety analyses are conducted to guide appropriate allocation of resources and design safe, reliable systems. Few studies published to date include these considerations when integrating AI-based solutions into DR screening programs. In this article, we provide an overview of the current state-of-the-art of AI technology (focusing on deep learning systems), followed by an appraisal of existing literature on the applications of AI in ophthalmology. We also discuss practical considerations that drive the development of a successful DR screening program, such as the implications of false-positive or false-negative results and image gradeability. Finally, we examine different plausible methods for HEA and safety analyses that can be used to assess concerns regarding AI-based screening., Competing Interests: Disclosure: Y. Xie, None; D.V. Gunasekeran, None; K. Balaskas, None; P.A. Keane, None; D.A. Sim, None; L.M. Bachmann, None; C. Macrae, None; D.S.W. Ting, Deep learning system for retinal diseases (P), (Copyright 2020 The Authors.)

Background: Developments in information technology (IT) have driven a push in healthcare innovation in the emergency department (ED). Many of these applications rely on mobile technology (MT) such as smartphones but not everyone is comfortable with MT usage. Our study aims to characterize the technology usage behavior of users in the ED so as to guide the implementation of IT interventions in the ED., Methods: A cross-sectional survey was conducted in the emergency department of a tertiary hospital. Patients and their caregivers aged 21 and above were recruited. The survey collected demographic information, technology usage patterns, and participant reported comfort level in the usage of MT. We performed descriptive statistics and multivariate logistic regression to identify factors differentially associated with comfort in usage of MT., Results: A total of 498 participants were recruited, and 299 (60%) were patients. English was the most commonly written and read language (66.9%) and 64.2% reported a comfort level of 3/5 or more in using MT. Factors that were associated with being comfortable in using MT include having a tertiary education, being able to read and write English, as well as being a frequent user of IT. Caregivers were more likely to display these characteristics., Conclusion: A large proportion of ED patients are not comfortable in the usage of MT. Factors that predicted comfort level in the usage of MT were common amongst caregivers. Future interventions should take this into consideration in the design of MT interventions., Competing Interests: Conflicts of interests: ZL, RP, KP, LHH and MN report no conflict of interest. DVG has received grant funding through the Commonwealth Fellowship in Innovation award. DVG reports stock ownership in DoctorBell and VISRE that produce products relevant to the subject material. DVG reports advisory as Head of Web/Big data protocol to the Collaborative Ocular Tuberculosis Study (COTS) group, an international initiative utilising cloud computing to investigate ocular tuberculosis (TB) as an early opportunity to address asymptomatic carriage of pulmonary TB., (Copyright: © 2020 World Journal of Emergency Medicine.)

Purpose: Tubercular retinal vasculitis (TRV) is a heterogeneous disease that can be difficult to manage because of nonspecific presentation and limitations of confirmatory tests for tuberculosis. This is a big data analysis on phenotypes and treatment outcomes for TRV., Methods: Multicentre retrospective study of patients with TRV between January 2004 and December 2014 and a minimum follow-up of 1 year., Results: Two hundred and fifty-one patients with TRV with a mean age of 38.9 ± 14.4 years (range, 9-86 years) were included. The patients were predominantly males (n = 167/251; 66.5%) of Asian ethnicity (n = 174/246; 70.7%), and geographical origin (n = 137/251; 54.6%). Most patients had features of occlusive type of RV (n = 113/185; 61.1%) except Caucasians (n = 11; 28.2%). There was no significant difference in treatment failure whether patients received antitubercular therapy (ATT) (P = 0.29), although treatment failure was less frequent in patients who received ATT (13.6%; n = 31/228) compared with those who did not (21.7%, n = 5/23). Less treatment failures were observed in patients with occlusive type RV who received ATT; however, this was not significant on survival analysis (P = 0.09). Treatment with ATT was associated with higher failure rates in patients of Hispanic and African American race and those with TRV associated with panuveitis (compared with posterior uveitis)., Conclusion: In this multinational study of TRV, there was no significant therapeutic effect of ATT. However, a definitive conclusion about the role of ATT could not be made because of a few patients who did not receive ATT. Because this is a retrospective study with a limited 1-year follow-up, the effect of ATT may have been overestimated (or underestimated) in the duration of follow-up.

Purpose: The aim of this study was to examine regional variation management practices and outcomes for tubercular uveitis (TBU)., Methods: In this retrospective multinational cohort study, patients from 25 international eye care centers diagnosed with TBU with a minimum follow-up of 1 year were included. The geographic variation in treatment outcomes on survival analysis in patients with TBU were analyzed. Treatment failure is defined as a persistence or recurrence of inflammation within 6 months of completing antitubercular therapy, the inability to taper oral corticosteroids to less than 10 mg/d or topical corticosteroid drops to less than 2 drops daily, and/or recalcitrant inflammation necessitating corticosteroid-sparing immunosuppressive therapy., Results: Records of 945 patients (1485 eyes) with TBU were analyzed. The mean age was 41.3 ± 15.0 years (range, 4-90 years), with more males (52.9%, n = 500/945) and predominant Asian ethnicity (74.4%, n = 690/927). Most patients had no symptoms (92.0%, n = 655/712) or history (76.7%, n = 604/787) suggestive of pulmonary tuberculosis (TB). Some patients had evidence of inactive pulmonary TB on chest X-rays (26.9%, n = 189/702) or chest computed tomography (68.6%, n = 109/159). Patients with western geographic origin (log-rank = 6.47, P = 0.010), African or Hispanic ethnicity (log-rank = 19.9, P < 0.001), and positive immigrant status (log-rank = 4.89, P = 0.027) had poorer survival outcomes., Conclusions: This is a first-ever multinational analysis of TBU that highlights regional differences in treatment outcomes for this elusive form of extrapulmonary TB. Our findings will help in the design of future collaborative studies together with internists to develop best practice guidelines for this early opportunity to address TB infection and strategies to target at-risk groups such as immigrants.

Purpose: To describe the visual morbidity associated with intraocular tuberculosis (TB) and to report ocular complications of intraocular TB., Methods: Retrospective cohort study of patients diagnosed with intraocular TB at a tertiary referral eye care hospital in central London. Data on baseline and final best-corrected visual acuity (BCVA) along with ocular complications were collected and analyzed., Results: In total, 354 patients with intraocular TB were included in this study. Mean age was 48.45 years (range 19-94) and follow-up was 22.56 ± 7.44 (range 6-30) months post cessation of therapy. Blindness as defined by the World Health Organization was reported in 11 (3.11%) patients at baseline and 13 (3.67%) patients at follow-up. The most common ocular complications were cystoid macular edema (n = 107, 30.5%) and glaucoma (n = 99, 28.12%)., Conclusion: Intraocular TB can be associated with significant ocular morbidity. Early recognition, treatment, and regular follow-up of this complex disease may help to reduce visual morbidity and ocular complications.

Background: To evaluate the contribution made to the diagnostic work-up for patients with suspected ocular tuberculosis (TB) by QuantiFERON-TB Gold In-Tube (QFT) tests using latent class analysis model., Methods: A single centre retrospective cohort study. A Bayesian latent class model was constructed on the basis of demographics, phenotypes and test results from patients attending a tertiary referral center in the UK. This estimated the probability of ocular TB for each patient in two versions, first with and then without QFT. The estimated probability of ocular TB was compared with treatment failure., Results: From a database of 365 patients with clinical signs suggestive of ocular TB, 267 patients who had QFT and complete data were evaluated. Mean age was 45.0 ± 15.4 years with 141 (52.9%) male and 148 (50.5%) of Asian ethnicity. QFT was positive in 208 (70.1%) patients and ATT was instituted in 145 (49.5%) patients with 100 (34.1%) patients also having concurrent systemic corticosteroid therapy. The best estimate of a QFT level separating TB-positive and TB-negative patients was extremely low. This weak discrimination between TB and non-TB groups was reflected in poor positive and negative predictive values for treatment failure., Conclusions: The latent class model did not successfully predict treatment failure, despite taking all variables into account. The threshold between TB and non-TB in QFT values was implausibly low and removing QFT from the model made prediction slightly worse. A larger prospective study is required to establish the role of all tests, demographics and phenotypes in diagnosis.

Importance: Eradication of systemic tuberculosis (TB) has been limited by neglected populations and the HIV pandemic. Whereas ocular TB often presents as uveitis without any prior evidence of systemic TB, the existing uncertainty in the diagnosis of TB uveitis may perpetuate missed opportunities to address systemic TB., Objective: To examine the clinical features of TB uveitis and the associations with response to antitubercular therapy (ATT)., Design, Setting, and Participants: This retrospective multinational cohort study included patients from 25 ophthalmology referral centers diagnosed with TB uveitis and treated with ATT from January 1, 2004, through December 31, 2014, with a minimum follow-up of 1 year., Main Outcomes and Measures: Treatment failure, defined as a persistence or recurrence of inflammation within 6 months of completing ATT, inability to taper oral corticosteroids to less than 10 mg/d or topical corticosteroid drops to less than 2 drops daily, and/or recalcitrant inflammation necessitating corticosteroid-sparing immunosuppressive therapy., Results: A total of 801 patients (1272 eyes) were studied (mean [SD] age, 40.5 [14.8] years; 413 [51.6%] male and 388 [48.4%] female; 577 [73.6%] Asian). Most patients had no known history (498 of 661 [75.3%]) of systemic TB. Most patients had bilateral involvement (471 of 801 [58.8%]). Common clinical signs reported include vitreous haze (523 of 1153 [45.4%]), retinal vasculitis (374 of 874 [42.8%]), and choroidal involvement (419 of 651 [64.4%]). Treatment failure developed in 102 of the 801 patients (12.7%). On univariate regression analysis, the hazard ratios (HRs) associated with intermediate uveitis (HR, 2.21; 95% CI, 1.07-4.55; P = .03), anterior uveitis (HR, 2.68; 95% CI, 1.32-2.35; P = .006), and panuveitis (HR, 3.28; 95% CI, 1.89-5.67; P < .001) were significantly higher compared with posterior distribution. The presence of vitreous haze had a statistically significant association (HR, 1.95; 95% CI, 1.26-3.02; P = .003) compared with absence of vitreous haze. Bilaterality had an associated HR of 1.50 (95% CI, 0.96-2.35) compared with unilaterality (HR, 1 [reference]), although this finding was not statistically significant (P = .07). On multivariate Cox proportional hazards regression analysis, the presence of vitreous haze had an adjusted HR of 2.98 (95% CI, 1.50-5.94; P = .002), presence of snow banking had an adjusted HR of 3.71 (95% CI, 1.18-11.62; P = .02), and presence of choroidal involvement had an adjusted HR of 2.88 (95% CI, 1.22-6.78; P = .02)., Conclusions and Relevance: A low treatment failure rate occurred in patients with TB uveitis treated with ATT. Phenotypes and test results are studied whereby patients with panuveitis having vitreous and choroidal involvement had a higher risk of treatment failure. These findings are limited by retrospective methods. A prospectively derived composite clinical risk score might address this diagnostic uncertainty through holistic and standardized assessment of the combinations of clinical features and investigation results that may warrant diagnosis of TB uveitis and treatment with ATT.

Switching of anti-vascular endothelial growth factor (VEGF) therapy in the management of poorly responsive exudative age-related macular degeneration (AMD) has had suggested benefits in individual reports that have yet to be consolidated. In this retrospective review, 24 studies published between 2009 and 2014 were identified. Reasons for switching included tachyphylaxis, health insurance coverage, cost issues, and nonresponse or inadequate response. Nine studies had data that could be used for comparison between studies. Median follow-up was 10.6 months (range: 4.2 months to 21.8 months). Mean baseline visual acuity (VA) ranged from 0.42 logMar to 0.94 logMar (standard deviation [SD] range: 0.05 logMar to 0.50 logMar) and mean VA on final follow-up ranged from 0.38 logMar to 0.78 logMar (SD range: 0.08 logMar to 0.50 logMar). Five of nine studies reported no statistically significant change in vision, and five of nine studies reported a statistically significant improvement in central retinal thickness. This review found that switching anti-VEGF did not confer significant improvement of VA, although it provided some anatomical improvement. Pertinent considerations for evaluating response following anti-VEGF therapy are also presented in this review. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:859-869.]., (Copyright 2017, SLACK Incorporated.)

Purpose: Describe the clinical features and outcomes of patients with peripheral retinal vasculitis (RV) and describe clinical characteristics of presumed tubercular RV in a nonendemic setting., Methods: Retrospective cohort study of 110 consecutive patients with peripheral RV at a tertiary referral eye care center in the United Kingdom. Retinal vasculitis was defined as RV with vitritis associated with peripheral retinal ischemia. Patients who also had positive Quantiferon Gold in Tube test, positive tuberculin skin test, and/or other evidence of systemic tuberculosis such as biopsy were labeled with presumed tubercular RV. Treatment success was defined as resolution of inflammation, and successful tapering of oral corticosteroids to less than 10 mg/day or topical steroids to less than twice a day., Results: Mean age of the study population was 42.69 ± 14.95 years. Patients were predominantly Asian (49.1%) and Male (67.0%). A total of 73.2% had bilateral involvement. Sixty-nine (62.72%) patients had presumed tubercular RV. A total of 52.8% patients received antitubercular therapy, 65.5% received oral corticosteroids, and 17.3% required steroid-sparing oral immunosuppressive agents. A total of 85.19% of patients with presumed tubercular RV achieved treatment success with concurrent antitubercular therapy as against 75.61% of patients with nontubercular RV., Conclusion: This is the largest study of the epidemiology, clinical features, and outcomes of both peripheral RV and presumed tubercular RV to date. Presumed tubercular RV commonly seems to affect young males of Asian descent and had vitreous hemorrhage as common clinical findings and also demonstrated a good treatment outcome with antitubercular therapy.

Intraocular tuberculosis remains a diagnostic and management conundrum for both ophthalmologists and pulmonologists. We analyze the efficacy and safety of anti-tubercular therapy (ATT) in patients with intraocular tuberculosis and factors associated with favorable outcome. Twenty-eight studies are included in this review, with a total of 1,917 patients. Nonrecurrence of inflammation was observed in pooled estimate of 84% of ATT-treated patients (95% CI 79-89). There was minimal difference in the outcome between patients treated with ATT alone (85% successful outcome; 95% CI 25-100) and those with concomitant systemic corticosteroid (82%; 95% CI 73-90). The use of ATT may be of benefit to patients with suspected intraocular tuberculosis; however, this conclusion is limited by the lack of control group analysis and standardized recruitment and treatment protocols. We propose further prospective studies to better establish the efficacy of ATT and ascertain the factors associated with favorable treatment outcomes., Competing Interests: There are no financial support and conflict of interest for any author., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: This study aims to perform comprehensive longitudinal immune factor analysis of aqueous humor in relation to the aqueous CMV viral load and systemic CD4 counts during treatment of patients with co-infection of HIV and CMVR., Methods: Aqueous humor samples were collected from 17 HIV-positive patients with CMVR scheduled to undergo weekly intravitreal ganciclovir therapy as part of the prospective CMV Retinitis Intravitreal Ganciclovir Singapore Study (CRIGSS) over the course of 1year. Full data across all the 4 time points was obtained and analyzed for CMV DNA viral load, 41 cytokine and chemokine factors using real-time PCR with the FlexMAP 3D (Luminex®) platform and assessed using the Milliplex Human Cytokine® kit., Results: The following immune factors (Spearman correlation coefficient r value in parenthesis, p<0.05) showed strong correlation with CMV DNA load in the aqueous - MCP-1 (0.80, IFN-g (0.83), IP-10 (0.82), IL-8 (0.81), fractalkine (0.73), RANTES (0.68) - while the following showed moderate correlation - PDGF-AA (0.58), Flt-3L (0.59) and G-CSF (0.53). Only PDGF-AA revealed a statistically significant negative correlation with serum CD4 levels (r=-0.74)., Conclusion: Immune factors that correlate with intraocular CMV DNA load are identified. They are indicative of a Th1 and monocyte-macrophage mediated response, and exhibit a decreasing trend longitudinally through the course of treatment. These factors may be an important new consideration in individualizing the treatment of patients with CMVR., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The data shows the aqueous humor cytokine profiling results acquired in a small cohort of 17 HIV patients clinically diagnosed with Cytomegalovirus retinitis using the FlexMAP 3D (Luminex®) platform using the Milliplex Human Cytokine® kit. Aqueous humor samples were collected from these patients at different time points (pre-treatment and at 4-weekly intervals through the 12-week course of intravitreal ganciclovir treatment) and 41 cytokine levels were analyzed at each time point. CMV DNA viral load was assessed in 8 patients at different time points throughout the course of ganciclovir treatment. The data described herein is related to the research article entitled "Aqueous humor immune factors and cytomegalovirus (CMV) levels in CMV retinitis through treatment - The CRIGSS study" (Iyer et al., 2016) [1]. Cytokine levels against the different time points which indicate the response to the given treatment and against the CMV viral load were analyzed.