Moorfields Eye Hospital NHS Foundation Trust

BACKGROUND: Contemporary data for causes of vision impairment and blindness form an important basis of recommendations in public health policies. Refreshment of the Global Vision Database with recently published data sources permitted modelling of cause of vision loss data from 1990 to 2015, further disaggregation by cause, and forecasts to 2020. METHODS: In this systematic review and meta-analysis, we analysed published and unpublished population-based data for the causes of vision impairment and blindness from 1980 to 2014. We identified population-based studies published before July 8, 2014, by searching online databases with no language restrictions (MEDLINE from Jan 1, 1946, and Embase from Jan 1, 1974, and the WHO Library Database). We fitted a series of regression models to estimate the proportion of moderate or severe vision impairment (defined as presenting visual acuity of <6/18 but ≥3/60 in the better eye) and blindness (presenting visual acuity of <3/60 in the better eye) by cause, age, region, and year. FINDINGS: We identified 288 studies of 3 983 541 participants contributing data from 98 countries. Among the global population with moderate or severe vision impairment in 2015 (216·6 million [80% uncertainty interval 98·5 million to 359·1 million]), the leading causes were uncorrected refractive error (116·3 million [49·4 million to 202·1 million]), cataract (52·6 million [18·2 million to 109·6 million]), age-related macular degeneration (8·4 million [0·9 million to 29·5 million]), glaucoma (4·0 million [0·6 million to 13·3 million]), and diabetic retinopathy (2·6 million [0·2 million to 9·9 million]). Among the global population who were blind in 2015 (36·0 million [12·9 million to 65·4 million]), the leading causes were cataract (12·6 million [3·4 million to 28·7 million]), uncorrected refractive error (7·4 million [2·4 million to 14·8 million]), and glaucoma (2·9 million [0·4 million to 9·9 million]). By 2020, among the global population with moderate or severe vision impairment (237·1 million [101·5 million to 399·0 million]), the number of people affected by uncorrected refractive error is anticipated to rise to 127·7 million (51·0 million to 225·3 million), by cataract to 57·1 million (17·9 million to 124·1 million), by age-related macular degeneration to 8·8 million (0·8 million to 32·1 million), by glaucoma to 4·5 million (0·5 million to 15·4 million), and by diabetic retinopathy to 3·2 million (0·2 million to 12·9 million). By 2020, among the global population who are blind (38·5 million [13·2 million to 70·9 million]), the number of patients blind because of cataract is anticipated to rise to 13·4 million (3·3 million to 31·6 million), because of uncorrected refractive error to 8·0 million (2·5 million to 16·3 million), and because of glaucoma to 3·2 million (0·4 million to 11·0 million). Cataract and uncorrected refractive error combined contributed to 55% of blindness and 77% of vision impairment in adults aged 50 years and older in 2015. World regions varied markedly in the causes of blindness and vision impairment in this age group, with a low prevalence of cataract (<22% for blindness and 14·1-15·9% for vision impairment) and a high prevalence of age-related macular degeneration (>14% of blindness) as causes in the high-income subregions. Blindness and vision impairment at all ages in 2015 due to diabetic retinopathy (odds ratio 2·52 [1·48-3·73]) and cataract (1·21 [1·17-1·25]) were more common among women than among men, whereas blindness and vision impairment due to glaucoma (0·71 [0·57-0·86]) and corneal opacity (0·54 [0·43-0·66]) were more common among men than among women, with no sex difference related to age-related macular degeneration (0·91 [0·70-1·14]). INTERPRETATION: The number of people affected by the common causes of vision loss has increased substantially as the population increases and ages. Preventable vision loss due to cataract (reversible with surgery) and refractive error (reversible with spectacle correction) continue to cause most cases of blindness and moderate or severe vision impairment in adults aged 50 years and older. A large scale-up of eye care provision to cope with the increasing numbers is needed to address avoidable vision loss. FUNDING: Brien Holden Vision Institute.

This review describes a scheme for diagnosis of glaucoma in population based prevalence surveys. Cases are diagnosed on the grounds of both structural and functional evidence of glaucomatous optic neuropathy. The scheme also makes provision for diagnosing glaucoma in eyes with severe visual loss where formal field testing is impractical, and for blind eyes in which the optic disc cannot be seen because of media opacities.

BACKGROUND: Deep learning offers considerable promise for medical diagnostics. We aimed to evaluate the diagnostic accuracy of deep learning algorithms versus health-care professionals in classifying diseases using medical imaging. METHODS: In this systematic review and meta-analysis, we searched Ovid-MEDLINE, Embase, Science Citation Index, and Conference Proceedings Citation Index for studies published from Jan 1, 2012, to June 6, 2019. Studies comparing the diagnostic performance of deep learning models and health-care professionals based on medical imaging, for any disease, were included. We excluded studies that used medical waveform data graphics material or investigated the accuracy of image segmentation rather than disease classification. We extracted binary diagnostic accuracy data and constructed contingency tables to derive the outcomes of interest: sensitivity and specificity. Studies undertaking an out-of-sample external validation were included in a meta-analysis, using a unified hierarchical model. This study is registered with PROSPERO, CRD42018091176. FINDINGS: Our search identified 31 587 studies, of which 82 (describing 147 patient cohorts) were included. 69 studies provided enough data to construct contingency tables, enabling calculation of test accuracy, with sensitivity ranging from 9·7% to 100·0% (mean 79·1%, SD 0·2) and specificity ranging from 38·9% to 100·0% (mean 88·3%, SD 0·1). An out-of-sample external validation was done in 25 studies, of which 14 made the comparison between deep learning models and health-care professionals in the same sample. Comparison of the performance between health-care professionals in these 14 studies, when restricting the analysis to the contingency table for each study reporting the highest accuracy, found a pooled sensitivity of 87·0% (95% CI 83·0-90·2) for deep learning models and 86·4% (79·9-91·0) for health-care professionals, and a pooled specificity of 92·5% (95% CI 85·1-96·4) for deep learning models and 90·5% (80·6-95·7) for health-care professionals. INTERPRETATION: Our review found the diagnostic performance of deep learning models to be equivalent to that of health-care professionals. However, a major finding of the review is that few studies presented externally validated results or compared the performance of deep learning models and health-care professionals using the same sample. Additionally, poor reporting is prevalent in deep learning studies, which limits reliable interpretation of the reported diagnostic accuracy. New reporting standards that address specific challenges of deep learning could improve future studies, enabling greater confidence in the results of future evaluations of this promising technology. FUNDING: None.

Eye health and vision have widespread and profound implications for many aspects of life, health, sustainable development, and the economy.Yet nowadays, many people, families, and populations continue to suffer the consequences of poor access to high-quality, affordable eye care, leading to vision impairment and blindness.In 2020, an estimated 596 million people had distance vision impairment worldwide, of whom 43 million were blind.Another 510 million people had uncorrected near vision impairment, simply because of not having reading spectacles.A large proportion of those affected (90%), live in low-income and middle-income countries (LMICs).However, encouragingly, more than 90% of people with vision impairment have a preventable or treatable cause with existing highly cost-effective interventions.Eye conditions affect all stages of life, with young children and older people being particularly affected.Crucially, women, rural populations, and ethnic minority groups are more likely to have vision impairment, and this pervasive inequality needs to be addressed.By 2050, population ageing, growth, and urbanisation might lead to an estimated 895 million people with distance vision impairment, of whom 61 million will be blind.Action to prioritise eye health is needed now.This Commission defines eye health as maximised vision, ocular health, and functional ability, thereby contributing to overall health and wellbeing, social inclusion, and quality of life.Eye health is essential to achieve many of the Sustainable Development Goals (SDGs).Poor eye health and impaired vision have a negative effect on quality of life and restrict equitable access to and achievement in education and the workplace.Vision loss has substantial financial implications for affected individuals, families, and communities.Although high-quality data for global economic estimates are scarce, particularly for LMICs, conservative assessments based on the latest prevalence figures for 2020 suggest that annual global productivity loss from vision impairment is approximately US$410•7 billion purchasing power parity.Vision impairment reduces mobility, affects mental wellbeing, exacerbates risk of dementia, increases likelihood of falls and road traffic crashes, increases the need for social care, and ultimately leads to higher mortality rates.By contrast, vision facilitates many daily life activities, enables better educational outcomes, and increases work productivity, reducing inequality.An increasing amount of evidence shows the potential for vision to advance the SDGs, by contributing towards poverty reduction, zero hunger, good health and wellbeing, quality education, gender equality, and decent work.Eye health is a global public priority, transforming lives in both poor and wealthy communities.Therefore, eye health needs to be reframed as a development as well as a health issue and given greater prominence within the global development and health agendas.Vision loss has many causes that require promotional, preventive, treatment, and rehabilitative interventions.Cataract, uncorrected refractive error, glaucoma, agerelated macular degeneration, and diabetic retinopathy www.thelancet.

The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.

Primary open-angle glaucoma (POAG) affects 33 million individuals worldwide and is a leading cause of blindness. In a study of 54 families with autosomal dominantly inherited adult-onset POAG, we identified the causative gene on chromosome 10p14 and designated it OPTN (for "optineurin"). Sequence alterations in OPTN were found in 16.7% of families with hereditary POAG, including individuals with normal intraocular pressure. The OPTN gene codes for a conserved 66-kilodalton protein of unknown function that has been implicated in the tumor necrosis factor-alpha signaling pathway and that interacts with diverse proteins including Huntingtin, Ras-associated protein RAB8, and transcription factor IIIA. Optineurin is expressed in trabecular meshwork, nonpigmented ciliary epithelium, retina, and brain, and we speculate that it plays a neuroprotective role.

Abstract Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders1. However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications2. Here, we present RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6 million unlabelled retinal images by means of self-supervised learning and then adapted to disease detection tasks with explicit labels. We show that adapted RETFound consistently outperforms several comparison models in the diagnosis and prognosis of sight-threatening eye diseases, as well as incident prediction of complex systemic disorders such as heart failure and myocardial infarction with fewer labelled data. RETFound provides a generalizable solution to improve model performance and alleviate the annotation workload of experts to enable broad clinical AI applications from retinal imaging.

Gonçalo Abecasis and colleagues report a large-scale meta-analysis of genome-wide association studies for age-related macular degeneration (AMD), including over 17,100 advanced cases and 60,000 controls. They identify seven loci newly associated with AMD and report pathway analysis that shows enrichment in the complement system and atherosclerosis signaling. Age-related macular degeneration (AMD) is a common cause of blindness in older individuals. To accelerate the understanding of AMD biology and help design new therapies, we executed a collaborative genome-wide association study, including >17,100 advanced AMD cases and >60,000 controls of European and Asian ancestry. We identified 19 loci associated at P < 5 × 10−8. These loci show enrichment for genes involved in the regulation of complement activity, lipid metabolism, extracellular matrix remodeling and angiogenesis. Our results include seven loci with associations reaching P < 5 × 10−8 for the first time, near the genes COL8A1-FILIP1L, IER3-DDR1, SLC16A8, TGFBR1, RAD51B, ADAMTS9 and B3GALTL. A genetic risk score combining SNP genotypes from all loci showed similar ability to distinguish cases and controls in all samples examined. Our findings provide new directions for biological, genetic and therapeutic studies of AMD.

OBJECTIVE: We aimed to develop consensus-based recommendations for streamlining medical communication among various health care professionals, to improve accuracy of diagnosis and treatment, and to facilitate future investigations for mucous membrane pemphigoid. PARTICIPANTS: Because of the highly specific nature of this group of diseases, the 26 invited participants included either international scholars in the field of mucous membrane pemphigoid or experts in cutaneous pharmacology representing the 3 medical disciplines ophthalmology, oral medicine, and dermatology. EVIDENCE: The first author (L.S.C.) conducted a literature search. Based on the information obtained, international experts who had contributed to the literature in the clinical care, diagnosis, and laboratory investigation for mucous membrane pemphigoid were invited to participate in a consensus meeting aimed at developing a consensus statement. CONSENSUS PROCESS: A consensus meeting was convened and conducted on May 10, 1999, in Chicago, Ill, to discuss the relevant issues. The first author drafted the statement based on the consensus developed at the meeting and the participants' written comments. The draft was submitted to all participants for 3 separate rounds of review, and disagreements were reconciled based on literature evidence. The third and final statement incorporated all relevant evidence obtained in the literature search and the consensus developed by the participants. The final statement was approved and endorsed by all 26 participants. CONCLUSIONS: Specific consensus-based recommendations were made regarding the definition, diagnostic criteria, pathogenic factors, medical treatment, and prognostic indicators for mucous membrane pemphigoid. A system of standard reporting for these patients was proposed to facilitate a uniform data collection.

Importance: Glaucoma is the most common cause of irreversible blindness worldwide. Many patients with glaucoma are asymptomatic early in the disease course. Primary care clinicians should know which patients to refer to an eye care professional for a complete eye examination to check for signs of glaucoma and to determine what systemic conditions or medications can increase a patient's risk of glaucoma. Open-angle and narrow-angle forms of glaucoma are reviewed, including a description of the pathophysiology, risk factors, screening, disease monitoring, and treatment options. Observations: Glaucoma is a chronic progressive optic neuropathy, characterized by damage to the optic nerve and retinal nerve fiber layer, that can lead to permanent loss of peripheral or central vision. Intraocular pressure is the only known modifiable risk factor. Other important risk factors include older age, nonwhite race, and a family history of glaucoma. Several systemic medical conditions and medications including corticosteroids, anticholinergics, certain antidepressants, and topiramate may predispose patients to glaucoma. There are 2 broad categories of glaucoma, open-angle and angle-closure glaucoma. Diagnostic testing to assess for glaucoma and to monitor for disease progression includes measurement of intraocular pressure, perimetry, and optical coherence tomography. Treatment of glaucoma involves lowering intraocular pressure. This can be achieved with various classes of glaucoma medications as well as laser and incisional surgical procedures. Conclusions and Relevance: Vision loss from glaucoma can be minimized by recognizing systemic conditions and medications that increase a patient's risk of glaucoma and referring high-risk patients for a complete ophthalmologic examination. Clinicians should ensure that patients remain adherent with taking glaucoma medications and should monitor for adverse events from medical or surgical interventions used to treat glaucoma.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

BACKGROUND: Treatments for open-angle glaucoma aim to prevent vision loss through lowering of intraocular pressure, but to our knowledge no placebo-controlled trials have assessed visual function preservation, and the observation periods of previous (unmasked) trials have typically been at least 5 years. We assessed vision preservation in patients given latanoprost compared with those given placebo. METHODS: In this randomised, triple-masked, placebo-controlled trial, we enrolled patients with newly diagnosed open-angle glaucoma at ten UK centres (tertiary referral centres, teaching hospitals, and district general hospitals). Eligible patients were randomly allocated (1:1) with a website-generated randomisation schedule, stratified by centre and with a permuted block design, to receive either latanoprost 0·005% (intervention group) or placebo (control group) eye drops. Drops were administered from identical bottles, once a day, to both eyes. The primary outcome was time to visual field deterioration within 24 months. Analyses were done in all individuals with follow-up data. The Data and Safety Monitoring Committee (DSMC) recommended stopping the trial on Jan 6, 2011 (last patient visit July, 2011), after an interim analysis, and suggested a change in primary outcome from the difference in proportions of patients with incident progression between groups to time to visual field deterioration within 24 months. This trial is registered, number ISRCTN96423140. FINDINGS: We enrolled 516 individuals between Dec 1, 2006, and March 16, 2010. Baseline mean intraocular pressure was 19·6 mm Hg (SD 4·6) in 258 patients in the latanoprost group and 20·1 mm Hg (4·8) in 258 controls. At 24 months, mean reduction in intraocular pressure was 3·8 mm Hg (4·0) in 231 patients assessed in the latanoprost group and 0·9 mm Hg (3·8) in 230 patients assessed in the placebo group. Visual field preservation was significantly longer in the latanoprost group than in the placebo group: adjusted hazard ratio (HR) 0·44 (95% CI 0·28-0·69; p=0·0003). We noted 18 serious adverse events, none attributable to the study drug. INTERPRETATION: This is the first randomised placebo-controlled trial to show preservation of the visual field with an intraocular-pressure-lowering drug in patients with open-angle glaucoma. The study design enabled significant differences in vision to be assessed in a relatively short observation period. FUNDING: Pfizer, UK National Institute for Health Research Biomedical Research Centre.

OBJECTIVES: To report on the causes of blindness certifications in England and Wales in working age adults (16-64 years) in 2009-2010; and to compare these with figures from 1999 to 2000. DESIGN: Analysis of the national database of blindness certificates of vision impairment (CVIs) received by the Certifications Office. SETTING AND PARTICIPANTS: Working age (16-64 years) population of England and Wales. MAIN OUTCOME MEASURES: Number and cause of blindness certifications. RESULTS: The Certifications Office received 1756 CVIs for blindness from persons aged between 16 and 64 inclusive between 1 April 2009 and 31 March 2010. The main causes of blindness certifications were hereditary retinal disorders (354 certifications comprising 20.2% of the total), diabetic retinopathy/maculopathy (253 persons, 14.4%) and optic atrophy (248 persons, 14.1%). Together, these three leading causes accounted for almost 50% of all blindness certifications. Between 1 April 1999 and 31 March 2000, the leading causes of blindness certification were diabetic retinopathy/maculopathy (17.7%), hereditary retinal disorders (15.8%) and optic atrophy (10.1%). CONCLUSIONS: For the first time in at least five decades, diabetic retinopathy/maculopathy is no longer the leading cause of certifiable blindness among working age adults in England and Wales, having been overtaken by inherited retinal disorders. This change may be related to factors including the introduction of nationwide diabetic retinopathy screening programmes in England and Wales and improved glycaemic control. Inherited retinal disease, now representing the commonest cause of certification in the working age population, has clinical and research implications, including with respect to the provision of care/resources in the NHS and the allocation of research funding.

The CONSORT 2010 (Consolidated Standards of Reporting Trials) statement provides minimum guidelines for reporting randomised trials. Its widespread use has been instrumental in ensuring transparency when evaluating new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes.The CONSORT-AI extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI. Both guidelines were developed through a staged consensus process, involving a literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed on in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants).The CONSORT-AI extension includes 14 new items, which were considered sufficiently important for AI interventions, that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and providing analysis of error cases.CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer-reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.

AIMS: To derive preliminary estimates for the number of adults in China suffering from glaucoma, and project the burden of visual morbidity attributable to primary and secondary glaucoma. METHODS: Age and sex specific data from two population surveys were applied to US Census Bureau population estimates for urban and rural China. It was assumed that data from Singapore were representative of urban China, and those from Mongolia were representative of rural China. RESULTS: It was estimated that 9.4 million people aged 40 years and older in China have glaucomatous optic neuropathy. Of this number, 5.2 million (55%) are blind in at least one eye and 1.7 million (18.1%) are blind in both eyes. Primary angle closure glaucoma (PACG) is responsible for the vast majority (91%) of bilateral glaucoma blindness in China. The number of people with the anatomical trait predisposing to PACG (an "occludable" drainage angle) is in the region of 28.2 million, and of these 9.1 million have significant angle closure, indicated by peripheral anterior synechiae or raised intraocular pressure. CONCLUSIONS: This extrapolation of data from two east Asian countries gives an approximate number of people in China suffering from glaucoma. It is unlikely that this crude statistical model is entirely accurate. However, the authors believe the visual morbidity from glaucoma in China is considerable. PACG is probably the leading cause of glaucoma blindness in both eyes, and warrants detailed investigation of strategies for prevention.

The data from 159 patients (217 eyes) with episscleritis and 207 patients (301 eyes) with scleritis have been investigated in detail and the results analysed with the help of a computer. Of these patients, 91 per cent were followed-up during a period of one to eight years. A new classification is presented which is as follows: Episcleritis (217 eyes) Simple episcleritis (170 eyes) Nodular episcleritis (47 eyes) Scleritis (301 eyes) Diffuse anterior scleritis (119 eyes) Nodular anterior scleritis (134 eyes) Necrotizing scleritis (42 eyes). Of these, 13 were regarded as scleromalacia perforans. Posterior scleritis (6 eyes) The diagnosis is based on an exact clinical examination which is fully described. Episcleritis has been shown to be a benign recurring condition, a mild keratitis being the only occasional complication. Episcleritis does not progress to scleritis, except in the case of herpes zoster which sometimes starts as an episcleritis with the vesicular stage of the eruption, to reappear three months later as a scleritis in the same site. No clear conclusions could be drawn as to the aetiology of episcleritis.

The full-field electroretinogram (ERG) is a mass electrophysiological response to diffuse flashes of light and is used widely to assess generalized retinal function. This document, from the International Society for Clinical Electrophysiology of Vision (ISCEV), presents an updated and revised ISCEV Standard for clinical ERG testing. Minimum protocols for basic ERG stimuli, recording methods and reporting are specified, to promote consistency of methods for diagnosis, monitoring and inter-laboratory comparisons, while also responding to evolving clinical practices and technology. The main changes in this updated ISCEV Standard for clinical ERGs include specifying that ERGs may meet the Standard without mydriasis, providing stimuli adequately compensate for non-dilated pupils. There is more detail about analysis of dark-adapted oscillatory potentials (OPs) and the document format has been updated and supplementary content reduced. There is a more detailed review of the origins of the major ERG components. Several tests previously tabulated as additional ERG protocols are now cited as published ISCEV extended protocols. A non-standard abbreviated ERG protocol is described, for use when patient age, compliance or other circumstances preclude ISCEV Standard ERG testing.

BACKGROUND: Primary open angle glaucoma and ocular hypertension are habitually treated with eye drops that lower intraocular pressure. Selective laser trabeculoplasty is a safe alternative but is rarely used as first-line treatment. We compared the two. METHODS: In this observer-masked, randomised controlled trial treatment-naive patients with open angle glaucoma or ocular hypertension and no ocular comorbidities were recruited between 2012 and 2014 at six UK hospitals. They were randomly allocated (web-based randomisation) to initial selective laser trabeculoplasty or to eye drops. An objective target intraocular pressure was set according to glaucoma severity. The primary outcome was health-related quality of life (HRQoL) at 3 years (assessed by EQ-5D). Secondary outcomes were cost and cost-effectiveness, disease-specific HRQoL, clinical effectiveness, and safety. Analysis was by intention to treat. This study is registered at controlled-trials.com (ISRCTN32038223). FINDINGS: Of 718 patients enrolled, 356 were randomised to the selective laser trabeculoplasty and 362 to the eye drops group. 652 (91%) returned the primary outcome questionnaire at 36 months. Average EQ-5D score was 0·89 (SD 0·18) in the selective laser trabeculoplasty group versus 0·90 (SD 0·16) in the eye drops group, with no significant difference (difference 0·01, 95% CI -0·01 to 0·03; p=0·23). At 36 months, 74·2% (95% CI 69·3-78·6) of patients in the selective laser trabeculoplasty group required no drops to maintain intraocular pressure at target. Eyes of patients in the selective laser trabeculoplasty group were within target intracoluar pressure at more visits (93·0%) than in the eye drops group (91·3%), with glaucoma surgery to lower intraocular pressure required in none versus 11 patients. Over 36 months, from an ophthalmology cost perspective, there was a 97% probability of selective laser trabeculoplasty as first treatment being more cost-effective than eye drops first at a willingness to pay of £20 000 per quality-adjusted life-year gained. INTERPRETATION: Selective laser trabeculoplasty should be offered as a first-line treatment for open angle glaucoma and ocular hypertension, supporting a change in clinical practice. FUNDING: National Institute for Health Research, Health and Technology Assessment Programme.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings.

BACKGROUND: Variation of fluorescence derived from lipofuscin in the retinal pigment epithelium has been recorded with age and in retinal diseases. Studies have been based largely on in vitro observations on eye bank eyes which has placed severe limitations on the data available. METHODS: A technique is described whereby in vivo imaging of autofluorescence of the fundus was achieved using a scanning laser ophthalmoscope. RESULTS: The optical characteristics, distribution, and variation with disease imply that the fluorescence is derived from lipofuscin in the pigment epithelium. Autofluorescence is shown to be abnormally high in certain inherited diseases, and low in the presence of retinal atrophy. CONCLUSION: This technique may be useful both in clinical practice and research. It may allow the detection of the abnormal phenotype in genetically determined disease at a time when other techniques may not. Longitudinal studies of age related macular disease would permit correlation between changes in the pigment epithelium and Bruch's membrane to be established.