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Artificial intelligence (AI) health technologies are increasingly available for use in real-world care. This emerging opportunity is accompanied by a need for decision makers and practitioners across healthcare systems to evaluate the safety and effectiveness of these interventions against the needs of their own setting. To meet this need, high-quality evidence regarding AI-enabled interventions must be made available, and decision makers in varying roles and settings must be empowered to evaluate that evidence within the context in which they work. This article summarizes good practices across four stages of evidence generation for AI health technologies: study design, study conduct, study reporting, and study appraisal.

Background: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack of knowledge of how to report AEs, and a general culture of nonreporting. The introduction of artificial intelligence as a medical device (AIaMD) requires a robust safety monitoring environment that recognizes both generic risks of a medical device and some of the increasingly recognized risks of AIaMD (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems and explore potential mechanisms for how AEs could be detected, attributed, and reported with a view to improving the early detection of safety signals., Objective: The systematic review outlined in this protocol aims to yield insights into the frequency and severity of AEs while characterizing the events using existing regulatory guidance., Methods: Publicly accessible AE databases will be searched to identify AE reports for AIaMD. Scoping searches have identified 3 regulatory territories for which public access to AE reports is provided: the United States, the United Kingdom, and Australia. AEs will be included for analysis if an artificial intelligence (AI) medical device is involved. Software as a medical device without AI is not within the scope of this review. Data extraction will be conducted using a data extraction tool designed for this review and will be done independently by AUK and a second reviewer. Descriptive analysis will be conducted to identify the types of AEs being reported, and their frequency, for different types of AIaMD. AEs will be analyzed and characterized according to existing regulatory guidance., Results: Scoping searches are being conducted with screening to begin in April 2024. Data extraction and synthesis will commence in May 2024, with planned completion by August 2024. The review will highlight the types of AEs being reported for different types of AI medical devices and where the gaps are. It is anticipated that there will be particularly low rates of reporting for indirect harms associated with AIaMD., Conclusions: To our knowledge, this will be the first systematic review of 3 different regulatory sources reporting AEs associated with AIaMD. The review will focus on real-world evidence, which brings certain limitations, compounded by the opacity of regulatory databases generally. The review will outline the characteristics and frequency of AEs reported for AIaMD and help regulators and policy makers to continue developing robust safety monitoring processes., International Registered Report Identifier (irrid): PRR1-10.2196/48156., (©Aditya U Kale, Riya Dattani, Ashley Tabansi, Henry David Jeffry Hogg, Russell Pearson, Ben Glocker, Su Golder, Justin Waring, Xiaoxuan Liu, David J Moore, Alastair K Denniston. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 11.07.2024.)

Purpose: To assess the efficacy of treatment on acute posterior multifocal placoid pigment epitheliopathy (APMPPE) and relentless placoid chorioretinopathy (RPC)., Methods: Cases were identified from three UK uveitis centers. Retrospective analysis of visual acuity recovery; OCT structural outcomes; and retinal lesion quantification in observed and treated cases of APMPPE/RPC., Results: There were nine APMPPE and three RPC cases. Out of 12 patients, six were female. Median age: 26.5 years (range, 20-57 years). Four cases (six eyes) were observed, and eight cases (15 eyes) received corticosteroids ± immunosuppression. 4/4 observed and 6/10 treated foveal involving eyes regained 0.00 LogMAR vision. Observed lesions achieved more favorable anatomical outcomes. New lesions post-presentation developed in 1/6 (16%) observed eye versus 10/15 (66%) treated eyes. In three cases, a delayed, rebound lesion occurrence was observed post-high-dose corticosteroids., Conclusions: While subject to potential treatment bias, in this small case series, natural history alone appears non-inferior to corticosteroid treatment.

Background: Artificial intelligence (AI) medical devices have the potential to transform existing clinical workflows and ultimately improve patient outcomes. AI medical devices have shown potential for a range of clinical tasks such as diagnostics, prognostics, and therapeutic decision-making such as drug dosing. There is, however, an urgent need to ensure that these technologies remain safe for all populations. Recent literature demonstrates the need for rigorous performance error analysis to identify issues such as algorithmic encoding of spurious correlations (eg, protected characteristics) or specific failure modes that may lead to patient harm. Guidelines for reporting on studies that evaluate AI medical devices require the mention of performance error analysis; however, there is still a lack of understanding around how performance errors should be analyzed in clinical studies, and what harms authors should aim to detect and report., Objective: This systematic review will assess the frequency and severity of AI errors and adverse events (AEs) in randomized controlled trials (RCTs) investigating AI medical devices as interventions in clinical settings. The review will also explore how performance errors are analyzed including whether the analysis includes the investigation of subgroup-level outcomes., Methods: This systematic review will identify and select RCTs assessing AI medical devices. Search strategies will be deployed in MEDLINE (Ovid), Embase (Ovid), Cochrane CENTRAL, and clinical trial registries to identify relevant papers. RCTs identified in bibliographic databases will be cross-referenced with clinical trial registries. The primary outcomes of interest are the frequency and severity of AI errors, patient harms, and reported AEs. Quality assessment of RCTs will be based on version 2 of the Cochrane risk-of-bias tool (RoB2). Data analysis will include a comparison of error rates and patient harms between study arms, and a meta-analysis of the rates of patient harm in control versus intervention arms will be conducted if appropriate., Results: The project was registered on PROSPERO in February 2023. Preliminary searches have been completed and the search strategy has been designed in consultation with an information specialist and methodologist. Title and abstract screening started in September 2023. Full-text screening is ongoing and data collection and analysis began in April 2024., Conclusions: Evaluations of AI medical devices have shown promising results; however, reporting of studies has been variable. Detection, analysis, and reporting of performance errors and patient harms is vital to robustly assess the safety of AI medical devices in RCTs. Scoping searches have illustrated that the reporting of harms is variable, often with no mention of AEs. The findings of this systematic review will identify the frequency and severity of AI performance errors and patient harms and generate insights into how errors should be analyzed to account for both overall and subgroup performance., Trial Registration: PROSPERO CRD42023387747; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=387747., International Registered Report Identifier (irrid): PRR1-10.2196/51614., (©Aditya U Kale, Henry David Jeffry Hogg, Russell Pearson, Ben Glocker, Su Golder, April Coombe, Justin Waring, Xiaoxuan Liu, David J Moore, Alastair K Denniston. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 28.06.2024.)

Introduction: The diagnosis of neovascular age-related macular degeneration (nAMD), the leading cause of visual impairment in the developed world, relies on the interpretation of various imaging tests of the retina. These include invasive angiographic methods, such as Fundus Fluorescein Angiography (FFA) and, on occasion, Indocyanine-Green Angiography (ICGA). Newer, non-invasive imaging modalities, predominately Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), have drastically transformed the diagnostic approach to nAMD. The aim of this study is to undertake a comprehensive diagnostic accuracy assessment of the various imaging modalities used in clinical practice for the diagnosis of nAMD (OCT, OCTA, FFA and, when a variant of nAMD called Polypoidal Choroidal Vasculopathy is suspected, ICGA) both alone and in various combinations., Methods and Analysis: This is a non-inferiority, prospective, randomised diagnostic accuracy study of 1067 participants. Participants are patients with clinical features consistent with nAMD who present to a National Health Service secondary care ophthalmology unit in the UK. Patients will undergo OCT as per standard practice and those with suspicious features of nAMD on OCT will be approached for participation in the study. Patients who agree to take part will also undergo both OCTA and FFA (and ICGA if indicated). Interpretation of the imaging tests will be undertaken by clinicians at recruitment sites. A randomised design was selected to avoid bias from consecutive review of all imaging tests by the same clinician. The primary outcome of the study will be the difference in sensitivity and specificity between OCT+OCTA and OCT+FFA (±ICGA) for nAMD detection as interpreted by clinicians at recruitment sites., Ethics and Dissemination: The study has been approved by the South Central-Oxford B Research Ethics Committee with reference number 21/SC/0412.Dissemination of study results will involve peer-review publications, presentations at major national and international scientific conferences., Trial Registration Number: ISRCTN18313457., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Objective: To evaluate the associations between socioeconomic deprivation and sight-threatening diabetic retinopathy (STDR) in individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D)., Research Design and Methods: Data from 175,628 individuals with diabetes in the Health Improvement Network were used to assess the risk of STDR across Townsend Deprivation Index quantiles using Cox proportional hazard regression., Results: Among individuals with T1D, the risk of STDR was three times higher (adjusted hazard ratio [aHR] 2.67, 95% CI 1.05-7.78) in the most deprived quintile compared with the least deprived quintile. In T2D, the most deprived quintile had a 28% higher risk (aHR 1.28; 95% CI 1.15-1.43) than the least deprived quintile., Conclusions: Increasing socioeconomic deprivation is associated with a higher risk of developing STDR in people with diabetes. This underscores persistent health disparities linked to poverty, even within a country offering free universal health care. Further research is needed to address health equity concerns in socioeconomically deprived regions., (© 2024 by the American Diabetes Association.)

Optical coherence tomography angiography (OCTA) is widely used for non-invasive retinal vascular imaging, but the OCTA methods used to assess retinal perfusion vary. We evaluated the different methods used to assess retinal perfusion between OCTA studies. MEDLINE and Embase were searched from 2014 to August 2021. We included prospective studies including ≥ 50 participants using OCTA to assess retinal perfusion in either global retinal or systemic disorders. Risk of bias was assessed using the National Institute of Health quality assessment tool for observational cohort and cross-sectional studies. Heterogeneity of data was assessed by Q statistics, Chi-square test, and I 2  index. Of the 5974 studies identified, 191 studies were included in this evaluation. The selected studies employed seven OCTA devices, six macula volume dimensions, four macula subregions, nine perfusion analyses, and five vessel layer definitions, totalling 197 distinct methods of assessing macula perfusion and over 7000 possible combinations. Meta-analysis was performed on 88 studies reporting vessel density and foveal avascular zone area, showing lower retinal perfusion in patients with diabetes mellitus than in healthy controls, but with high heterogeneity. Heterogeneity was lowest and reported vascular effects strongest in superficial capillary plexus assessments. Systematic review of OCTA studies revealed massive heterogeneity in the methods employed to assess retinal perfusion, supporting calls for standardisation of methodology., (© 2024. Crown.)

Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: support from the funding bodies listed above for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. GSC is a National Institute for Health and Care Research (NIHR) senior investigator, the director of the UK EQUATOR Centre, editor-in-chief of BMC Diagnostic and Prognostic Research, and a statistics editor for The BMJ. KGMM is director of Health Innovation Netherlands and editor-in-chief of BMC Diagnostic and Prognostic Research. RDR is an NIHR senior investigator, a statistics editor for The BMJ, and receives royalties from textbooks Prognosis Research in Healthcare and Individual Participant Data Meta-Analysis. AKD is an NIHR senior investigator. EWL is the head of research at The BMJ. BG is a part time employee of HeartFlow and Kheiron Medical Technologies and holds stock options with both as part of the standard compensation package. SR receives royalties from Springer for the textbooks Targeted Learning: Causal Inference for Observational and Experimental Data and Targeted Learning: Causal Inference for Complex Longitudinal Studies. JCC receives honorariums as a current lay member on the UK NICE covid-19 expert panel and a citizen partner on the COVID-END Covid-19 Evidence Network to support decision making; was a lay member on the UK NIHR AI AWARD panel in 2020-22 and is a current lay member on the UK NHS England AAC Accelerated Access Collaborative NHS AI Laboratory Evaluation Advisory Group; is a patient fellow of the European Patients’ Academy on Therapeutic Innovation and a EURORDIS rare disease alumni; reports grants from the UK National Institute for Health and Care Research, European Commission, UK Cell Gene Catapult, University College London, and University of East Anglia; reports patient speaker fees from MEDABLE, Reuters Pharma events, Patients as Partners Europe, and EIT Health Scandinavia; reports consultancy fees from Roche Global, GlaxoSmithKline, the FutureScience Group and Springer Healthcare (scientific publishing), outside of the scope of the present work; and is a strategic board member of the UK Medical Research Council IASB Advanced Pain Discovery Platform initiative, Plymouth Institute of Health, and EU project Digipredict Edge AI-deployed Digital Twins for covid-19 Cardiovascular Disease. ALB is a paid consultant for Generate Biomedicines, Flagship Pioneering, Porter Health, FL97, Tessera, FL85; has an equity stake in Generate Biomedicines; and receives research funding support from GlaxoSmithKline, National Heart, Lung, and Blood Institute, and National Institute of Diabetes and Digestive and Kidney Diseases. No other conflicts of interests with this specific work are declared.

Introduction: Chimeric antigen receptor (CAR) T-cell therapies are novel, potentially curative therapies for haematological malignancies. CAR T-cell therapies are associated with severe toxicities, meaning patients require monitoring during acute and postacute treatment phases. Electronic patient-reported outcomes (ePROs), self-reports of health status provided via online questionnaires, can complement clinician observation with potential to improve patient outcomes. This study will develop and evaluate feasibility of a new ePRO system for CAR-T patients in routine care., Methods and Analysis: Multiphase, mixed-methods study involving multiple stakeholder groups (patients, family members, carers, clinicians, academics/researchers and policy-makers). The intervention development phase comprises a Delphi study to select PRO measures for the digital system, a codesign workshop and consensus meetings to establish thresholds for notifications to the clinical team if a patient reports severe symptoms or side effects. Usability testing will evaluate how users interact with the digital system and, lastly, we will evaluate ePRO system feasibility with 30 CAR-T patients (adults aged 18+ years) when used in addition to usual care. Feasibility study participants will use the ePRO system to submit self-reports of symptoms, treatment tolerability and quality of life at specific time points. The CAR-T clinical team will respond to system notifications triggered by patients' submitted responses with actions in line with standard clinical practice. Feasibility measures will be collected at prespecified time points following CAR T-cell infusion. A qualitative substudy involving patients and clinical team members will explore acceptability of the ePRO system., Ethics and Dissemination: Favourable ethical opinion was granted by the Health and Social Care Research Ethics Committee B(HSC REC B) (ref: 23/NI/0104) on 28 September 2023. Findings will be submitted for publication in high-quality, peer-reviewed journals. Summaries of results, codeveloped with the Blood and Transplant Research Unit Patient and Public Involvement and Engagement group, will be disseminated to all interested groups., Trial Registration Number: ISCTRN11232653., Competing Interests: Competing interests: MC is Director of the Birmingham Health Partners Centre for Regulatory Science and Innovation, Director of the Centre for the Centre for Patient Reported Outcomes Research and is a National Institute for Health Research (NIHR) Senior Investigator. MC receives funding from the National Institute for Health Research (NIHR), UK Research and Innovation (UKRI), NIHR Birmingham Biomedical Research Centre, the NIHR Surgical Reconstruction and Microbiology Research Centre, NIHR ARC West Midlands, UK SPINE, European Regional Development Fund—Demand Hub and Health Data Research UK at the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, Innovate UK (part of UKRI), Macmillan Cancer Support, UCB Pharma, Anthony Nolan, GSK and Gilead. MJC has received personal fees from Astellas, Aparito, CIS Oncology, Takeda, Merck, Daiichi Sankyo, Glaukos, GSK and the Patient-Centered Outcomes Research Institute (PCORI) outside the submitted work. In addition, a family member owns shares in GSK. OLA receives funding from the NIHR Birmingham BRC, West Midlands, Birmingham, NIHR ARC West Midlands, NIHR BTRU, UKRI, Health Foundation, Anthony Nolan, Gilead Sciences, Sarcoma UK and GSK. He declares personal fees from Gilead Sciences, Merck and GSK outside the submitted work. SEH receives funding from the NIHR, UKRI, Rinri Therapeutics, Anthony Nolan and declares personal fees from Cochlear, Astra Zeneca, Pfizer, CIS Oncology and Aparito outside the submitted work. CM receives funding from NIHR Surgical Reconstruction and Microbiology Research Centre (SRMRC), UKRI, Anthony Nolan and declares personal fees from Aparito outside the submitted work., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Background: Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation., Objective: This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England., Methods: This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence's Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from "definitely exclude" to "definitely include," and suggest edits. The document will be iterated between rounds based on participants' feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote., Results: Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024., Conclusions: The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas., International Registered Report Identifier (irrid): DERR1-10.2196/50568., (©Trystan Macdonald, Jacqueline Dinnes, Gregory Maniatopoulos, Sian Taylor-Phillips, Bethany Shinkins, Jeffry Hogg, John Kevin Dunbar, Ameenat Lola Solebo, Hannah Sutton, John Attwood, Michael Pogose, Rosalind Given-Wilson, Felix Greaves, Carl Macrae, Russell Pearson, Daniel Bamford, Adnan Tufail, Xiaoxuan Liu, Alastair K Denniston. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 27.03.2024.)

Background: To establish topographic maps and determine fundus distribution patterns of ocular toxoplasmosis (OT) lesions., Methods: In this retrospective study, patients who presented with OT to ophthalmology clinics from four countries (Argentina, Turkey, UK, USA) were included. Size, shape and location of primary (1°)/recurrent (2°) and active/inactive lesions were converted into a two-dimensional retinal chart by a retinal drawing software. A final contour map of the merged image charts was then created using a custom Matlab programme. Descriptive analyses were performed., Results: 984 lesions in 514 eyes of 464 subjects (53% women) were included. Mean area of all 1° and 2° lesions was 5.96±12.26 and 5.21±12.77 mm 2 , respectively. For the subset group lesions (eyes with both 1° and 2° lesions), 1° lesions were significantly larger than 2° lesions (5.52±6.04 mm 2 vs 4.09±8.90 mm 2 , p=0.038). Mean distances from foveola to 1° and 2° lesion centres were 6336±4267 and 5763±3491 µm, respectively. The majority of lesions were found in temporal quadrant (p<0.001). Maximum overlap of all lesions was at 278 µm inferotemporal to foveola., Conclusion: The 1° lesions were larger than 2° lesions. The 2° lesions were not significantly closer to fovea than 1° lesions. Temporal quadrant and macular region were found to be densely affected underlining the vision threatening nature of the disease., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Despite significant advances in clinical care and understanding of the underlying pathophysiology, age-related macular degeneration (AMD)-a major cause of global blindness-lacks effective treatment to prevent the irreversible degeneration of photoreceptors leading to central vision loss. Limited studies suggest phosphodiesterase type 5 (PDE5) inhibitors, such as sildenafil, may prevent AMD by increasing retinal blood flow. This study explores the potential association between sildenafil use and AMD risk in men with erectile dysfunction using UK data., Methods and Analysis: Using the UK's IQVIA Medical Research Data, the study analysed 31 575 men prescribed sildenafil for erectile dysfunction and no AMD history from 2007 to 2015, matched with a comparator group of 62 155 non-sildenafil users in a 1:2 ratio, over a median follow-up of approximately three years., Results: The primary outcome was the incidence of AMD in the two groups. The study found no significant difference in AMD incidence between the sildenafil users and the non-users, with an adjusted hazard ratio (HR) of 0.99 (95% CI 0.84 to 1.16), after accounting for confounders such as age, ethnicity, Townsend deprivation quintile, body mass index category, and diagnosis of hypertension and type 2 diabetes., Conclusion: The study results indicated no significant association between sildenafil use and AMD prevention in UK men with erectile dysfunction, suggesting sildenafil's protective effect on AMD is likely insignificant., Competing Interests: Competing interests: NJA, KN and AKD reported a grant from Action Against Age-related Macular Degeneration during the conduct of the study. NJA reported receiving grants from Medical Research Council, and National Institute for Health Research outside the submitted work. KN reported receiving grants from Medical Research Council, National Institute for Health Research, AstraZeneca, MSD, Boehringer Ingelheim and Health Data Research UK and personal fees from Sanofi outside the submitted work. AKD reported receiving grant support from Health Data Research UK outside the submitted work. No other disclosures were reported., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Artificial intelligence as a medical device (AIaMD) has the potential to transform many aspects of ophthalmic care, such as improving accuracy and speed of diagnosis, addressing capacity issues in high-volume areas such as screening, and detecting novel biomarkers of systemic disease in the eye (oculomics). In order to ensure that such tools are safe for the target population and achieve their intended purpose, it is important that these AIaMD have adequate clinical evaluation to support any regulatory decision. Currently, the evidential requirements for regulatory approval are less clear for AIaMD compared to more established interventions such as drugs or medical devices. There is therefore value in understanding the level of evidence that underpins AIaMD currently on the market, as a step toward identifying what the best practices might be in this area. In this systematic scoping review, we will focus on AIaMD that contributes to clinical decision-making (relating to screening, diagnosis, prognosis, and treatment) in the context of ophthalmic imaging., Objective: This study aims to identify regulator-approved AIaMD for ophthalmic imaging in Europe, Australia, and the United States; report the characteristics of these devices and their regulatory approvals; and report the available evidence underpinning these AIaMD., Methods: The Food and Drug Administration (United States), the Australian Register of Therapeutic Goods (Australia), the Medicines and Healthcare products Regulatory Agency (United Kingdom), and the European Database on Medical Devices (European Union) regulatory databases will be searched for ophthalmic imaging AIaMD through a snowballing approach. PubMed and clinical trial registries will be systematically searched, and manufacturers will be directly contacted for studies investigating the effectiveness of eligible AIaMD. Preliminary regulatory database searches, evidence searches, screening, data extraction, and methodological quality assessment will be undertaken by 2 independent review authors and arbitrated by a third at each stage of the process., Results: Preliminary searches were conducted in February 2023. Data extraction, data synthesis, and assessment of methodological quality commenced in October 2023. The review is on track to be completed and submitted for peer review by April 2024., Conclusions: This systematic review will provide greater clarity on ophthalmic imaging AIaMD that have achieved regulatory approval as well as the evidence that underpins them. This should help adopters understand the range of tools available and whether they can be safely incorporated into their clinical workflow, and it should also support developers in navigating regulatory approval more efficiently., International Registered Report Identifier (irrid): DERR1-10.2196/52602., (©Ariel Yuhan Ong, Henry David Jeffry Hogg, Aditya U Kale, Priyal Taribagil, Ashley Kras, Eliot Dow, Trystan Macdonald, Xiaoxuan Liu, Pearse A Keane, Alastair K Denniston. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 14.03.2024.)

Patient-reported outcomes (PROs) are increasingly used in healthcare research to provide evidence of the benefits and risks of interventions from the patient perspective and to inform regulatory decisions and health policy. The use of PROs in clinical practice can facilitate symptom monitoring, tailor care to individual needs, aid clinical decision-making and inform value-based healthcare initiatives. Despite their benefits, there are concerns that the potential burden on respondents may reduce their willingness to complete PROs, with potential impact on the completeness and quality of the data for decision-making. We therefore conducted an initial literature review to generate a list of candidate recommendations aimed at reducing respondent burden. This was followed by a two-stage Delphi survey by an international multi-stakeholder group. A consensus meeting was held to finalize the recommendations. The final consensus statement includes 19 recommendations to address PRO respondent burden in healthcare research and clinical practice. If implemented, these recommendations may reduce PRO respondent burden., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond "White", "Black", "Asian", "Mixed" and "Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all., (© 2024. The Author(s).)

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77-94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines., (© 2024. The Author(s).)

Introduction: Globally, diabetic retinopathy (DR) is a major cause of blindness. Sub-Saharan Africa is projected to see the largest proportionate increase in the number of people living with diabetes over the next two decades. Screening for DR is recommended to prevent sight loss; however, in many low and middle-income countries, because of a lack of specialist eye care staff, current screening services for DR are not optimal. The use of artificial intelligence (AI) for DR screening, which automates the grading of retinal photographs and provides a point-of-screening result, offers an innovative potential solution to improve DR screening in Tanzania., Methods and Analysis: We will test the hypothesis that AI-supported DR screening increases the proportion of persons with true referable DR who attend the central ophthalmology clinic following referral after screening in a single-masked, parallel group, individually randomised controlled trial. Participants (2364) will be randomised (1:1 ratio) to either AI-supported or the standard of care DR screening pathway. Participants allocated to the AI-supported screening pathway will receive their result followed by point-of-screening counselling immediately after retinal image capture. Participants in the standard of care arm will receive their result and counselling by phone once the retinal images have been graded in the usual way (typically after 2-4 weeks). The primary outcome is the proportion of persons with true referable DR attending the central ophthalmology clinic within 8 weeks of screening. Secondary outcomes, by trial arm, include the proportion of persons attending the central ophthalmology clinic out of all those referred, sensitivity and specificity, number of false positive referrals, acceptability and fidelity of AI-supported screening., Ethics and Dissemination: The London School of Hygiene & Tropical Medicine, Kilimanjaro Christian Medical Centre and Tanzanian National Institute of Medical Research ethics committees have approved the trial. The results will be submitted to peer-reviewed journals for publication., Trial Registration Number: ISRCTN18317152., Competing Interests: Competing interests: CE has received fees from Heidelberg Engineering and Inozyme Pharma. AT has received fees from Annexon, Apellis, Bayer, Genentech, Iveric Bio, Novartis, Oxurion and Roche. PAK has acted as a consultant for Roche, Novartis, Boehringer Ingelheim, Adecco and Bitfount and is an equity owner in Big Picture Medical; has received speaker fees from Novartis, Gyroscope, Bayer, Thea, Boehringer Ingelheim, Apellis, AbbVie, Alimera, Roche, Genentech, Specsavers, Heidelberg Engineering, Topcon and Santen; has received travel support from Bayer, Topcon and Roche; and has attended advisory boards for Boehringer Ingelheim, RetinAI, Novartis, Apellis, AbbVie and Roche., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Adalimumab is an effective treatment for autoimmune non-infectious uveitis (ANIU), but it is currently only funded for a minority of patients with ANIU in the UK as it is restricted by the National Institute for Health and Care Excellence guidance. Ophthalmologists believe that adalimumab may be effective in a wider range of patients. The Adalimumab vs placebo as add-on to Standard Therapy for autoimmune Uveitis: Tolerability, Effectiveness and cost-effectiveness (ASTUTE) trial will recruit patients with ANIU who do and do not meet funding criteria and will evaluate the effectiveness and cost-effectiveness of adalimumab versus placebo as an add-on therapy to standard care., Methods and Analysis: The ASTUTE trial is a multicentre, parallel-group, placebo-controlled, pragmatic randomised controlled trial with a 16-week treatment run-in (TRI). At the end of the TRI, only responders will be randomised (1:1) to 40 mg adalimumab or placebo (both are the study investigational medicinal product) self-administered fortnightly by subcutaneous injection. The target sample size is 174 randomised participants. The primary outcome is time to treatment failure (TF), a composite of signs indicative of active ANIU. Secondary outcomes include individual TF components, retinal morphology, adverse events, health-related quality of life, patient-reported side effects and visual function, best-corrected visual acuity, employment status and resource use. In the event of TF, open-label drug treatment will be restarted as per TRI for 16 weeks, and if a participant responds again, allocation will be switched without unmasking and treatment with investigational medicinal product restarted., Ethics and Dissemination: The trial received Research Ethics Committee (REC) approval from South Central - Oxford B REC in June 2020. The findings will be presented at international meetings, by peer-reviewed publications and through patient organisations and newsletters to patients, where available., Trial Registration: ISRCTN31474800. Registered 14 April 2020., Competing Interests: Competing interests: CAR received support from the National Institute for Health and Care Research (NIHR) for the project associated with this manuscript, which was paid to the University of Bristol. KP, MH, LC, MPYL, SB and BCR received support from the NIHR for the project associated with this manuscript, which contributed to their salary. SW, TP, SMS, NAVB and AD received support from the NIHR for the project associated with this manuscript, which was paid to their institution. SMS is the chair of the NIHR Uveitis Clinical Study Group. PAK receives support from UK Research and Innovation and Moorfields Eye Charity. PAK reports payment for consulting for Novartis, Boehringer-Ingleheim, Apellis, Abbvie, Roche and Adecco. PAK reports payment or honoraria for educational events for Novartis, Gyroscope, Bayer, Thea, Boehringer-Ingleheim, Apellis, Abbvie and Alimera. PAK participates on an advisory board for RetinAI, Novartis, Boehringer-Ingleheim, Roche and Abbvie. PAK reports patents for Google US10198832B2 (issued) and Google US20220301152A1 (pending). PAK reports stock with Big Picture Medical (stocks) and Bitfount (stock options). NAVB receives support from Wellcome Trust and recently receives support from Indonesian Endowment Fund for Education paid to their institution. NAVB reports payments for consulting for Roche. NAVB reports payment or honoria for educational events for Alimera Sciences. NAVB is a member of the Scientific Committee of the Royal College of Ophthalmologists. AD receives support from NIHR Biomedical Research Centre, Janssen Pharmaceuticals, Macular Society, MRC Cluster Consortium Awards and Arthritis Research UK, which is paid to his institution. AD receives royalties from The Eye Basic Science in Practice (Elsevier). AD reports payment for consulting for Hovartis, Hubble Htz, Active Bio and Gilead. AD participates on an advisory board for Co-THEIA Randomised Controlled Trial in Spain. AD is a non-executive director at Moorfields NHS Foundation Trust. No other conflicts were reported., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Periodontitis, a ubiquitous severe gum disease affecting the teeth and surrounding alveolar bone, can heighten systemic inflammation. We investigated the association between very severe periodontitis and early biomarkers of age-related macular degeneration (AMD), in individuals with no eye disease., Design: Cross-sectional analysis of the prospective community-based cohort United Kingdom (UK) Biobank., Participants: Sixty-seven thousand three hundred eleven UK residents aged 40 to 70 years recruited between 2006 and 2010 underwent retinal imaging., Methods: Macular-centered OCT images acquired at the baseline visit were segmented for retinal sublayer thicknesses. Very severe periodontitis was ascertained through a touchscreen questionnaire. Linear mixed effects regression modeled the association between very severe periodontitis and retinal sublayer thicknesses, adjusting for age, sex, ethnicity, socioeconomic status, alcohol consumption, smoking status, diabetes mellitus, hypertension, refractive error, and previous cataract surgery., Main Outcome Measures: Photoreceptor layer (PRL) and retinal pigment epithelium-Bruch's membrane (RPE-BM) thicknesses., Results: Among 36 897 participants included in the analysis, 1571 (4.3%) reported very severe periodontitis. Affected individuals were older, lived in areas of greater socioeconomic deprivation, and were more likely to be hypertensive, diabetic, and current smokers (all P < 0.001). On average, those with very severe periodontitis were hyperopic (0.05 ± 2.27 diopters) while those unaffected were myopic (-0.29 ± 2.40 diopters, P < 0.001). Following adjusted analysis, very severe periodontitis was associated with thinner PRL (-0.55 μm, 95% confidence interval [CI], -0.97 to -0.12; P  = 0.022) but there was no difference in RPE-BM thickness (0.00 μm, 95% CI, -0.12 to 0.13; P  = 0.97). The association between PRL thickness and very severe periodontitis was modified by age ( P < 0.001). Stratifying individuals by age, thinner PRL was seen among those aged 60 to 69 years with disease (-1.19 μm, 95% CI, -1.85 to -0.53; P < 0.001) but not among those aged < 60 years., Conclusions: Among those with no known eye disease, very severe periodontitis is statistically associated with a thinner PRL, consistent with incipient AMD. Optimizing oral hygiene may hold additional relevance for people at risk of degenerative retinal disease., Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (© 2024 by the American Academy of Ophthalmology.)

Background: Diabetic retinopathy (DR) is the most frequent complication of type 2 diabetes and remains the leading cause of preventable blindness. Current clinical decisions regarding the administration of antidiabetic drugs do not sufficiently incorporate the risk of DR due to the inconclusive evidence from preceding meta-analyses. This umbrella review aimed to systematically evaluate the effects of antidiabetic drugs on DR in people with type 2 diabetes., Methods: A systematic literature search was undertaken in Medline, Embase, and the Cochrane Library (from inception till 17th May 2022) without language restrictions to identify systematic reviews and meta-analyses of randomized controlled trials or longitudinal studies that examined the association between antidiabetic drugs and DR in people with type 2 diabetes. Two authors independently extracted data and assessed the quality of included studies using the AMSTAR-2 (A MeaSurement Tool to Assess Systematic Reviews) checklist, and evidence assessment was performed using the GRADE (Grading of recommendations, Assessment, Development and Evaluation). Random-effects models were applied to calculate relative risk (RR) or odds ratios (OR) with 95% confidence intervals (CI). This study was registered with PROSPERO (CRD42022332052)., Results: With trial evidence from 11 systematic reviews and meta-analyses, we found that the use of glucagon-like peptide-1 receptor agonists (GLP-1 RA), sodium-glucose cotransporter-2 inhibitors (SGLT-2i), or dipeptidyl peptidase-4 inhibitors (DPP-4i) was not statistically associated with the risk of DR, compared to either placebo (RR: GLP-1 RA, 0.98, 0.89-1.08; SGLT-2i, 1.00, 95% CI 0.79-1.27; DPP-4i, 1.17, 0.99-1.39) or other antidiabetic drugs. Compared to other antidiabetic drugs, meglitinides (0.34, 0.01-8.25), SGLT-2i (0.73, 0.10-5.16), thiazolidinediones (0.92, 0.67-1.26), metformin (1.15, 0.81-1.63), sulphonylureas (1.24, 0.93-1.65), and acarbose (4.21, 0.44-40.43) were not statistically associated with the risk of DR. With evidence from longitudinal studies only, insulin was found to have a higher risk of DR than other antidiabetic drugs (OR: 2.47, 95% CI: 2.04-2.99)., Conclusion: Our results indicate that antidiabetic drugs are generally safe to prescribe regarding the risk of DR among people with type 2 diabetes. Further robust and large-scale trials investigating the effects of insulin, meglitinides, and acarbose on DR are warranted., Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display&#95;record.php?RecordID=332052, identifier CRD42022332052., 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 © 2024 Tan, Wang, Okoth, Toulis, Denniston, Singh, Crowe, Sainsbury, Wang and Nirantharakumar.)

Background: The glymphatic system removes neurodegenerative debris. The ocular glymphatic outflow is from the eye to the proximal optic nerve. In multiple sclerosis (MS), atrophy of the optic nerve increases the glymphatic outflow space. Here, we tested whether vitreous haze (VH) can provide novel insights into the relationship between neurodegeneration and the ocular glymphatic system in MS., Methods: This cross-sectional study comprised 315 persons with MS and 87 healthy controls (HCs). VH was quantified from optical coherence tomography (OCT) volume scans. Neurodegeneration was determined on three-dimensional T1 (3DT1) MRI, lesion detection on fluid-attenuated inversion (FLAIR), and layer thickness on OCT. Generalized estimating equations, corrected for age, were used to analyze associations between VH and metrics for neurodegeneration, demographics, and clinical scales. Group differences were determined between mild, moderate, and severe disability., Results: On the group level, VH scores were comparable between MS and control ( p = 0.629). In MS, VH scores declined with disease duration (β = -0.009, p = 0.004) and age (β = -0.007, p = 0.001). There was no relation between VH scores and higher age in HCs. In MS patients, VH was related to normalized gray (NGMV, β = 0.001, p = 0.011) and white matter volume (NWMV, β = 0.001, p = 0.003), macular ganglion cell-inner plexiform layer thickness (mGCIPL, β = 0.006, p < 0.001), and peripapillary retinal nerve fiber layer thickness (pRNFL, β = 0.004, p = 0.008). VH was significantly lower in severe compared to mild disability (mean difference -28.86%, p = 0.058)., Conclusions: There is a correlation between VH on OCT and disease duration, more severe disability and lower brain volumes in MS. Biologically, these relationships suggest accelerated glymphatic clearance with disease-related atrophy.

Background: Uveitis comprises a range of conditions that result in intraocular inflammation. Most sight-threatening uveitis falls into the broad category known as Non-infectious Posterior Segment-Involving Uveitis (PSIU). To evaluate treatments, trialists and clinicians must select outcome measures. The aim of this study was to understand healthcare professionals' perspectives on what outcomes are important to adult patients with PSIU and their carers., Methods: Twelve semi-structured telephone interviews were undertaken to understand the perspectives of healthcare professionals. Interviews were audio recorded, transcribed and thematically analysed. Findings were compared with the views of patients and carers and outcomes abstracted from a previously published systematic review., Results: Eleven core domains were identified as important to healthcare professionals: (1) visual function, (2) symptoms, (3) functional ability, (4) impact on relationships, (5) financial impact, (6) psychological morbidity and emotional well-being (7) psychosocial adjustment to uveitis, (8) doctor / patient / interprofessional relationships and access to health care, (9) treatment burden, (10) treatment side effects, (11) disease control. Healthcare professionals recognised a similar range of domains to patients and carers but placed more emphasis on certain outcomes, particularly in the disease control domain. In contrast the range of outcomes identified via the systematic review was limited., Conclusion: Healthcare professionals recognise all of the published outcome domains as patients/carers in the previous publication but with subtly differing emphasis within some domains and with a priority for certain types of measures. Healthcare professionals discussed the disease control and side effects/complications to a greater degree than patients and carers in the focus groups., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Tallouzi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Objectives: Cadaveric studies have shown disease-related neurodegeneration and other morphological abnormalities in the retina of individuals with Parkinson disease (PD); however, it remains unclear whether this can be reliably detected with in vivo imaging. We investigated inner retinal anatomy, measured using optical coherence tomography (OCT), in prevalent PD and subsequently assessed the association of these markers with the development of PD using a prospective research cohort., Methods: This cross-sectional analysis used data from 2 studies. For the detection of retinal markers in prevalent PD, we used data from AlzEye, a retrospective cohort of 154,830 patients aged 40 years and older attending secondary care ophthalmic hospitals in London, United Kingdom, between 2008 and 2018. For the evaluation of retinal markers in incident PD, we used data from UK Biobank, a prospective population-based cohort where 67,311 volunteers aged 40-69 years were recruited between 2006 and 2010 and underwent retinal imaging. Macular retinal nerve fiber layer (mRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layer (INL) thicknesses were extracted from fovea-centered OCT. Linear mixed-effects models were fitted to examine the association between prevalent PD and retinal thicknesses. Hazard ratios for the association between time to PD diagnosis and retinal thicknesses were estimated using frailty models., Results: Within the AlzEye cohort, there were 700 individuals with prevalent PD and 105,770 controls (mean age 65.5 ± 13.5 years, 51.7% female). Individuals with prevalent PD had thinner GCIPL (-2.12 μm, 95% CI -3.17 to -1.07, p = 8.2 × 10 -5 ) and INL (-0.99 μm, 95% CI -1.52 to -0.47, p = 2.1 × 10 -4 ). The UK Biobank included 50,405 participants (mean age 56.1 ± 8.2 years, 54.7% female), of whom 53 developed PD at a mean of 2,653 ± 851 days. Thinner GCIPL (hazard ratio [HR] 0.62 per SD increase, 95% CI 0.46-0.84, p = 0.002) and thinner INL (HR 0.70, 95% CI 0.51-0.96, p = 0.026) were also associated with incident PD., Discussion: Individuals with PD have reduced thickness of the INL and GCIPL of the retina. Involvement of these layers several years before clinical presentation highlight a potential role for retinal imaging for at-risk stratification of PD., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Background: Electronic patient-reported outcome (ePRO) systems are increasingly used in clinical trials to provide evidence of efficacy and tolerability of treatment from the patient perspective. The aim of this study is twofold: (1) to describe how we developed an electronic platform for patients to report their symptoms, and (2) to develop and undertake usability testing of an ePRO solution for use in a study of cell therapy seeking to provide early evidence of efficacy and tolerability of treatment and test the feasibility of the system for use in later phase studies., Methods: An ePRO system was designed to be used in a single arm, multi-centre, phase II basket trial investigating the safety and activity of the use of ORBCEL-C™ in the treatment of patients with inflammatory conditions. ORBCEL-C™ is an enriched Mesenchymal Stromal Cells product isolated from human umbilical cord tissue using CD362+ cell selection. Usability testing sessions were conducted using cognitive interviews and the 'Think Aloud' method with patient advisory group members and Research Nurses to assess the usability of the system., Results: Nine patient partners and seven research nurses took part in one usability testing session. Measures of fatigue and health-related quality of life, the PRO-CTCAE™ and FACT-GP5 global tolerability question were included in the ePRO system. Alert notifications to the clinical team were triggered by PRO-CTCAE™ and FACT-GP5 scores. Patient participants liked the simplicity and responsiveness of the patient-facing app. Two patients were unable to complete the testing session, due to technical issues. Research Nurses suggested minor modifications to improve functionality and the layout of the clinician dashboard and the training materials., Conclusion: By testing the effectiveness, efficiency, and satisfaction of our novel ePRO system (PROmics R ), we learnt that most people with an inflammatory condition found it easy to report their symptoms using an app on their own device. Their experiences using the PROmics R ePRO system within a trial environment will be further explored in our upcoming feasibility testing. Research nurses were also positive and found the clinical dashboard easy-to-use. Using ePROs in early phase trials is important in order to provide evidence of therapeutic responses and tolerability, increase the evidence based, and inform methodology development., Trial Registration: ISRCTN, ISRCTN80103507. Registered 01 April 2022, https://www.isrctn.com/ISRCTN80103507., (© 2023. International Society for Quality of Life Research (ISOQOL).)

Objective: To search for and critically appraise the psychometric quality of patient-reported outcome measures (PROMs) developed or validated in optic neuritis, in order to support high-quality research and care., Methods: We systematically searched MEDLINE(Ovid), Embase(Ovid), PsycINFO(Ovid) and CINAHLPlus(EBSCO), and additional grey literature to November 2021, to identify PROM development or validation studies applicable to optic neuritis associated with any systemic or neurologic disease in adults. We included instruments developed using classic test theory or Rasch analysis approaches. We used established quality criteria to assess content development, validity, reliability, and responsiveness, grading multiple domains from A (high quality) to C (low quality)., Results: From 3142 screened abstracts we identified five PROM instruments potentially applicable to optic neuritis: three differing versions of the National Eye Institute (NEI)-Visual Function Questionnaire (VFQ): the 51-item VFQ; the 25-item VFQ and a 10-item neuro-ophthalmology supplement; and the Impact of Visual Impairment Scale (IVIS), a constituent of the Multiple Sclerosis Quality of Life Inventory (MSQLI) handbook, derived from the Functional Assessment of Multiple Sclerosis (FAMS). Psychometric appraisal revealed the NEI-VFQ-51 and 10-item neuro module had some relevant content development but weak psychometric development, and the FAMS had stronger psychometric development using Rasch Analysis, but was only somewhat relevant to optic neuritis. We identified no content or psychometric development for IVIS., Conclusion: There is unmet need for a PROM with strong content and psychometric development applicable to optic neuritis for use in virtual care pathways and clinical trials to support drug marketing authorisation., (© 2023. The Author(s).)

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 disorders 1 . However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications 2 . 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., (© 2023. The Author(s).)

Purpose: Retinal vein occlusion (RVO) is the second leading cause of visual loss due to retinal disease. Retinal vein occlusion increases the risk of cardiovascular mortality and the risk of stroke. This article describes the data contained within the INSIGHT eye health data set for RVO and cardiovascular disease., Design: Data set descriptor for routinely collected eye and systemic disease data., Participants: All people who had suffered an RVO aged ≥ 18 years old, attending the Ophthalmology Clinic at Queen Elizabeth Hospital, University Hospitals Birmingham (UHB) National Health Service (NHS) Trust were included., Methods: The INSIGHT Health Data Research Hub for Eye Health is an NHS-led ophthalmic bioresource. It provides researchers with safe access to anonymized routinely collected data from contributing NHS hospitals to advance research for patient benefit. This report describes the INSIGHT UHB RVO and major adverse cardiovascular events data set, a data set of ophthalmology and systemic data derived from the United Kingdom's largest acute care trust., Main Outcome Measures: This data set consists of routinely collected data from the hospital's electronic patient records. The data set primarily includes structured data (relating to their hospital eye care and any cardiovascular data held for the individual) and OCT ocular images. Further details regarding the available data points are available in the supplementary information., Results: At the time point of this analysis (September 30, 2022) the data set was composed of clinical data from 1521 patients, from Medisoft records inception. The data set includes 2196 occurrences of RVO affecting 2026 eyes, longitudinal eye follow-up clinical parameters, over 6217 eye-related procedures, and 982 encountered complications. The data set contains information on 2534 major adverse cardiovascular event occurrences, their subtype, number experienced per patient, and chronological relation to RVO event. Longitudinal follow-up data including laboratory results, regular medications, and all-cause mortality are also available within the data set., Conclusions: This data set descriptor article summarizes the data set contents, the process of its curation, and potential uses. The data set is available through the structured application process that ensures research studies are for patient benefit. Further information regarding the data repository and contact details can be found at https://www.insight.hdrhub.org/., Financial Disclosures: Proprietary or commercial disclosure may be found after the references., (© 2023 by the American Academy of Ophthalmology.)

Patient and public involvement and engagement (PPIE) can provide valuable insights into the experiences of those living with and affected by a disease or health condition. Inclusive collaboration between patients, the public and researchers can lead to productive relationships, ensuring that health research addresses patient needs. Guidelines are available to support effective PPIE; however, evaluation of the impact of PPIE strategies in health research is limited. In this Review, we evaluate the impact of PPIE in the 'Therapies for Long COVID in non-hospitalised individuals' (TLC) Study, using a combination of group discussions and interviews with patient partners and researchers. We identify areas of good practice and reflect on areas for improvement. Using these insights and the results of a survey, we synthesize two checklists of considerations for PPIE, and we propose that research teams use these checklists to optimize the impact of PPIE for both patients and researchers in future studies., (© 2023. Springer Nature America, Inc.)

Purpose: Investigate the association between the optical coherence tomography angiography (OCTA) metrics derived from different analysis programs to understand the comparability of studies using these different approaches., Methods: Secondary analysis of a prospective observational study (March 2018-September 2021). Forty-four right eyes and 42 left eyes from 44 patients were included. Patients were either undergoing upper gastrointestinal surgery with a critical care stay planned or were already in the critical care unit with sepsis. OCTA scans were obtained in an ophthalmology department or critical care setting. Fourteen OCTA metrics were compared within and between the programs, and agreement was measured by Pearson's R coefficient and intraclass correlation coefficient., Results: Correlation was highest between all Heidelberg metrics and Fractalyse (all >0.84), and lowest between Matlab skeletonized or foveal avascular zone metrics and all other measures (e.g., skeletal fractal dimension and vessel density at -0.02). Agreement between eyes was moderate to excellent in all metrics (0.60-0.90)., Conclusions: The significant variability between metrics and programs used for OCTA analysis demonstrates that they are not interchangeable and supports a recommendation for perfusion density metrics to be reported as standard., Translational Relevance: Agreement between different OCTA analyses is variable and not interchangeable. The high agreement between non-skeletonized vessel density metrics suggests that these should be routinely reported.

Background: Age-related macular degeneration (AMD) in its late stages is a leading cause of sight loss in developed countries. Some previous studies have suggested that metformin may be associated with a reduced risk of developing AMD, but the evidence is inconclusive., Aims: To explore the relationship between metformin use and development of AMD among patients with type 2 diabetes in the UK., Methods: A large, population-based retrospective open cohort study with a time-dependent exposure design was carried out using IQVIA Medical Research Data, 1995-2019. Patients aged ≥40 with diagnosed type 2 diabetes were included.The exposed group was those prescribed metformin (with or without any other antidiabetic medications); the comparator (unexposed) group was those prescribed other antidiabetic medications only. The exposure status was treated as time varying, collected at 3-monthly time intervals.Extended Cox proportional hazards regression was used to calculate the adjusted HRs for development of the outcome, newly diagnosed AMD., Results: A total of 173 689 patients, 57% men, mean (SD) age 62.8 (11.6) years, with incident type 2 diabetes and a record of one or more antidiabetic medications were included in the study. Median follow-up was 4.8 (IQR 2.3-8.3, range 0.5-23.8) years. 3111 (1.8%) patients developed AMD. The adjusted HR for diagnosis of AMD was 1.02 (95% CI 0.92 to 1.12) in patients prescribed metformin (with or without other antidiabetic medications) compared with those prescribed any other antidiabetic medication only., Conclusion: We found no evidence that metformin was associated with risk of AMD in primary care patients requiring treatment for type 2 diabetes., Competing Interests: Competing interests: Drs Adderley, Nirantharakumar and Denniston reported a grant from Action Against Age-related Macular Degeneration during the conduct of the study. Dr Adderley reported receiving grants from MRC UKRI and NIHR RfPB outside the submitted work. Dr Nirantharakumar reported receiving grants from Medical Research Council, National Institute for Health Research, AstraZeneca, MSD, Boehringer Ingelheim, Vifor, and Health Data Research UK and personal fees from Sanofi outside the submitted work. Dr Denniston reported receiving grant support from Health Data Research UK outside the submitted work. Dr Braithwaite reported receiving salary support from the patient charity Olivia’s Vision. No other disclosures were reported., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background/aims: To establish a consensus in the nomenclature for reporting optical coherence tomography angiography (OCTA findings in uveitis., Methods: The modified Delphi process consisted of two rounds of electronic questionnaires, followed by a face-to-face meeting conducted virtually. Twenty-one items were included for discussion. The three main areas of discussion were: wide field OCTA (WF-OCTA), nomenclature of OCTA findings and OCTA signal attenuation assessment and measurement. Seventeen specialists in uveitis and retinal imaging were selected by the executive committee to constitute the OCTA nomenclature in Uveitis Delphi Study Group. The study endpoint was defined by the degree of consensus for each question: 'strong consensus' was defined as >90% agreement, 'consensus' as 85%-90% and 'near consensus' as >80% but <85%., Results: There was a strong consensus to apply the term 'wide field' to OCTA images measuring over 70° of field of view, to use the terms 'flow deficit' and 'non-detectable flow signal' to describe abnormal OCTA flow signal secondary to slow flow and to vessels displacement respectively, to use the terms 'loose' and 'dense' to describe the appearance of inflammatory choroidal neovascularisation, and to use the percentage of flow signal decrease to measure OCTA ischaemia with a threshold greater than or equal to 30% as a 'large area'., Conclusions: This study sets up consensus recommendations for reporting OCTA findings in uveitis by an expert panel, which may prove suitable for use in routine clinical care and clinical trials., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background/aims: Anterior segment optical coherence tomography (AS-OCT) assessment of anterior chamber inflammation is an emerging tool. We describe the performance of AS-OCT in a paediatric population., Methods: A mixed-methods prospective study, using routine clinical assessment as reference standard, and AS-OCT, with Tomey CASIA2 or Heidelberg Spectralis HS1, as index test, with data collected on patient perceptions of imaging. Repeatability, diagnostic indices, responsiveness to clinical change and clinical correlations of imaging-based metrics (image cell count, size, density and brightness) were assessed, with construction of receiver operated characteristic curves. Exploratory thematic analysis of responses from families was undertaken., Results: A total of 90 children (180 eyes) underwent imaging. Bland Altman limits of agreement for CASIA2 repeatability ranged from +17 cells (95% CI 13.6 to 21.1) to -19 cells (95% CI -15.6 to -23.2) and HS1 from +1 (95% CI 0.9 to 1.2) to -1.0 (-1.2 to -0.8) cells. CASIA2 imaging had higher sensitivity of 0.92 (95% CI 0.78 to 0.97) vs HS1 imaging 0.17 (95% CI 0.07 to 0.34), with positive correlation between clinical grade and CASIA2 cell count (coefficient 12.8, p=0.02, 95% CI 2.2 to 23.4). Change in clinical grade at follow-up examinations correlated with change in image based 'cell' count (r 2 =0.79, p<0.001). Patients reported a potential positive impact of seeing their disease activity., Conclusion: Our findings suggest that OCT-based imaging holds the promise of deeper understanding of disease, improved patient experience and more granular monitoring of activity with resultant improved outcomes, but further work is needed to refine acquisition and analysis protocols., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections play a key role in treating a range of macular diseases. The effectiveness of these therapies is dependent on patients' adherence (the extent to which a patient takes their medicines as per agreed recommendations from the healthcare provider) and persistence (continuation of the treatment for the prescribed duration) to their prescribed treatment regimens. The aim of this systematic review was to demonstrate the need for further investigation into the prevalence of, and factors contributing to, patient-led non-adherence and non-persistence, thus facilitating improved clinical outcomes., Methods: Systematic searches were conducted in Google Scholar, Web of Science, PubMed, MEDLINE, and the Cochrane Library. Studies in English conducted before February 2023 that reported the level of, and/or barriers to, non-adherence or non-persistence to intravitreal anti-VEGF ocular disease therapy were included. Duplicate papers, literature reviews, expert opinion articles, case studies, and case series were excluded following screening by two independent authors., Results: Data from a total of 409,215 patients across 52 studies were analysed. Treatment regimens included pro re nata, monthly and treat-and-extend protocols; study durations ranged from 4 months to 8 years. Of the 52 studies, 22 included a breakdown of reasons for patient non-adherence/non-persistence. Patient-led non-adherence varied between 17.5 and 35.0% depending on the definition used. Overall pooled prevalence of patient-led treatment non-persistence was 30.0% (P = 0.000). Reasons for non-adherence/non-persistence included dissatisfaction with treatment results (29.9%), financial burden (19%), older age/comorbidities (15.5%), difficulty booking appointments (8.5%), travel distance/social isolation (7.9%), lack of time (5.8%), satisfaction with the perceived improvement in their condition (4.4%), fear of injection (4.0%), loss of motivation (4.0%), apathy towards eyesight (2.5%), dissatisfaction with facilities 2.3%, and discomfort/pain (0.3%). Three studies found non-adherence rates between 51.6 and 68.8% during the COVID-19 pandemic, in part due to fear of exposure to COVID-19 and difficulties travelling during lockdown., Discussion: Results suggest high levels of patient-led non-adherence/non-persistence to anti-VEGF therapy, mostly due to dissatisfaction with treatment results, a combination of comorbidities, loss of motivation and the burden of travel. This study provides key information on prevalence and factors contributing to non-adherence/non-persistence in anti-VEGF treatment for macular diseases, aiding identification of at-risk individuals to improve real-world visual outcomes. Improvements in the literature can be achieved by establishing uniform definitions and standard timescales for what constitutes non-adherence/non-persistence., Systematic Review Registration: PROSPERO CRD42020216205., (© 2023. Crown.)

Uveitis consists of a group of syndromes characterised by intraocular inflammation, accounting for up to 15% of visual loss in the western world and 10% worldwide. Assessment of intraocular inflammation has been limited to clinician-dependent, subjective grading. Developments in imaging technology, such as optical coherence tomography (OCT), have enabled the development of objective, quantitative measures of inflammatory activity. Important quantitative metrics including central macular thickness and vitreous signal intensity allow longitudinal monitoring of disease activity and can be used in conjunction with other imaging modalities enabling holistic assessment of ocular inflammation. Ongoing work into the validation of instrument-based measures alongside development of core outcome sets is crucial for standardisation of clinical trial endpoints and developing guidance for quantitative multi-modal imaging approaches. This review outlines methods of grading inflammation in the vitreous and retina, with a focus on the use of OCT as an objective measure of disease activity.

Importance: The potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts., Objective: To investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population., Design, Setting, and Participants: This cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022., Main Outcomes and Measures: Retinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers., Results: A total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (-4.05 μm, 95% CI, -5.40 to -2.69; P = 5.4 × 10-9), which persisted when investigating only patients without diabetes (-3.99 μm; 95% CI, -6.67 to -1.30; P = .004) or just those 55 years and younger (-2.90 μm; 95% CI, -5.55 to -0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (-0.14 units; 95% CI, -0.22 to -0.05; P = .001), although this was not present when excluding patients with diabetes., Conclusions and Relevance: In this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.

The extent to which patient-reported outcome measures (PROMs) are used in clinical trials for artificial intelligence (AI) technologies is unknown. In this systematic evaluation, we aim to establish how PROMs are being used to assess AI health technologies. We searched ClinicalTrials.gov for interventional trials registered from inception to Sept 20, 2022, and included trials that tested an AI health technology. We excluded observational studies, patient registries, and expanded access reports. We extracted data regarding the form, function, and intended use population of the AI health technology, in addition to the PROMs used and whether PROMs were incorporated as an input or output in the AI model. The search identified 2958 trials, of which 627 were included in the analysis. 152 (24%) of the included trials used one or more PROM, visual analogue scale, patient-reported experience measure, or usability measure as a trial endpoint. The type of AI health technologies used by these trials included AI-enabled smart devices, clinical decision support systems, and chatbots. The number of clinical trials of AI health technologies registered on ClinicalTrials.gov and the proportion of trials that used PROMs increased from registry inception to 2022. The most common clinical areas AI health technologies were designed for were digestive system health for non-PROM trials and musculoskeletal health (followed by mental and behavioural health) for PROM trials, with PROMs commonly used in clinical areas for which assessment of health-related quality of life and symptom burden is particularly important. Additionally, AI-enabled smart devices were the most common applications tested in trials that used at least one PROM. 24 trials tested AI models that captured PROM data as an input for the AI model. PROM use in clinical trials of AI health technologies falls behind PROM use in all clinical trials. Trial records having inadequate detail regarding the PROMs used or the type of AI health technology tested was a limitation of this systematic evaluation and might have contributed to inaccuracies in the data synthesised. Overall, the use of PROMs in the function and assessment of AI health technologies is not only possible, but is a powerful way of showing that, even in the most technologically advanced health-care systems, patients' perspectives remain central., Competing Interests: Declaration of interests SCR receives funding from UK SPINE and European Regional Development Fund DEMAND Hub and has received support to attend the Organisation for European Cancer Institutes 2022 conference as an invited speaker. MJC is Director of the Birmingham Health Partners Centre for Regulatory Science and Innovation, Director of the Centre for Patient Reported Outcomes Research, and is a National Institute for Health and Care Research (NIHR) Senior Investigator. MJC receives funding from the NIHR, UK Research and Innovation (UKRI), NIHR Birmingham Biomedical Research Centre, the NIHR Surgical Reconstruction and Microbiology Research Centre, NIHR, Applied Research Collaboration (ARC) West Midlands, UK SPINE, Research England, European Regional Development Fund DEMAND Hub at the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, and the NIHR Birmingham–Oxford Blood and Transplant Research Unit in Precision Transplant and Cellular Therapeutics. MJC also receives funding from Health Data Research UK, Innovate UK (part of UKRI), Macmillan Cancer Support, UCB Pharma, Janssen, GSK, Gilead Sciences, European Commission, European Federation of Pharmaceutical Industries and Associations, and The Brain Tumor Charity. MJC has received personal fees from Aparito, CIS Oncology, Takeda Pharmaceuticals, Merck, Daiichi Sankyo, Glaukos, GSK, the Patient-Centered Outcomes Research Institute, Genentech, and Vertex Pharmaceuticals, outside of the submitted work. MJC has received lecture fees from the University of Maastricht, Maastricht, Netherlands. In addition, a family member owns shares in GSK. The views expressed in this Review are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. All other authors declare no competing interests., (Copyright © 2023 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.)

Integration of patient-reported outcome measures (PROMs) in artificial intelligence (AI) studies is a critical part of the humanisation of AI for health. It allows AI technologies to incorporate patients' own views of their symptoms and predict outcomes, reflecting a more holistic picture of health and wellbeing and ultimately helping patients and clinicians to make the best health-care decisions together. By positioning patient-reported outcomes (PROs) as a model input or output we propose a framework to embed PROMs within the function and evaluation of AI health care. However, the integration of PROs in AI systems presents several challenges. These challenges include (1) fragmentation of PRO data collection; (2) validation of AI systems trained and validated against clinician performance, rather than outcome data; (3) scarcity of large-scale PRO datasets; (4) inadequate selection of PROMs for the target population and inadequate infrastructure for collecting PROs; and (5) clinicians might not recognise the value of PROs and therefore not prioritise their adoption; and (6) studies involving PRO or AI frequently present suboptimal design. Notwithstanding these challenges, we propose considerations for the inclusion of PROs in AI health-care technologies to avoid promoting survival at the expense of wellbeing., Competing Interests: Declaration of interests SCR receives funding from UK SPINE and European Regional Development Fund DEMAND Hub, and has received support to attend the Organisation for European Cancer Institutes 2022 conference as an invited speaker. MJC is Director of the Birmingham Health Partners Centre for Regulatory Science and Innovation, Director of the Centre for Patient Reported Outcomes Research, and is a National Institute for Health and Care Research (NIHR) Senior Investigator. MJC receives funding from the NIHR, UK Research and Innovation (UKRI), NIHR Birmingham Biomedical Research Centre, the NIHR Surgical Reconstruction and Microbiology Research Centre, NIHR, Applied Research Collaboration (ARC) West Midlands, UK SPINE, Research England, European Regional Development Fund DEMAND Hub at the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, and the NIHR Birmingham–Oxford Blood and Transplant Research Unit in Precision Transplant and Cellular Therapeutics. MJC also receives funding from Health Data Research UK, Innovate UK (part of UKRI), Macmillan Cancer Support, UCB Pharma, Janssen, GSK, Gilead Sciences, European Commission, European Federation of Pharmaceutical Industries and Associations, and The Brain Tumor Charity. MJC has received personal fees from Aparito, CIS Oncology, Takeda Pharmaceuticals, Merck, Daiichi Sankyo, Glaukos, GSK, the Patient-Centered Outcomes Research Institute, Genentech, and Vertex Pharmaceuticals outside the submitted work. MJC has received lecture fees from the University of Maastricht, Maastricht, Netherlands. In addition, a family member owns shares in GSK. The views expressed in this Viewpoint are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. SEH receives funding from the NIHRARC West Midlands, UKRI, and declares personal fees from Aparito and Cochlear outside the submitted work. SEH has received honoraria from the Cognitive Hearing Science for Communication 2019 (CHSCOM2019) and Implantable Auditory Prostheses. In addition, she has received support to attend the CHSCOM2019 and British Academy of Audiology Conference. SEH is a member of the trial steering committee of the Both EARS Study. All other authors declare no competing interests., (Copyright © 2023 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.)

Purpose: Diabetic retinopathy (DR) is the most common microvascular complication associated with diabetes mellitus (DM), affecting approximately 40% of this patient population. Early detection of DR is vital to ensure monitoring of disease progression and prompt sight saving treatments as required. This article describes the data contained within the INSIGHT Birmingham, Solihull, and Black Country Diabetic Retinopathy Dataset., Design: Dataset descriptor for routinely collected eye screening data., Participants: All diabetic patients aged 12 years and older, attending annual digital retinal photography-based screening within the Birmingham, Solihull, and Black Country Eye Screening Programme., Methods: The INSIGHT Health Data Research Hub for Eye Health is a National Health Service (NHS)-led ophthalmic bioresource that provides researchers with safe access to anonymized, routinely collected data from contributing NHS hospitals to advance research for patient benefit. This report describes the INSIGHT Birmingham, Solihull, and Black Country DR Screening Dataset, a dataset of anonymized images and linked screening data derived from the United Kingdom's largest regional DR screening program., Main Outcome Measures: This dataset consists of routinely collected data from the eye screening program. The data primarily include retinal photographs with the associated DR grading data. Additional data such as corresponding demographic details, information regarding patients' diabetic status, and visual acuity data are also available. Further details regarding available data points are available in the supplementary information, in addition to the INSIGHT webpage included below., Results: At the time point of this analysis (December 31, 2019), the dataset comprised 6 202 161 images from 246 180 patients, with a dataset inception date of January 1, 2007. The dataset includes 1 360 547 grading episodes between R0M0 and R3M1., Conclusions: This dataset descriptor article summarizes the content of the dataset, how it has been curated, and what its potential uses are. Data are available through a structured application process for research studies that support discovery, clinical evidence analyses, and innovation in artificial intelligence technologies for patient benefit. Further information regarding the data repository and contact details can be found at https://www.insight.hdrhub.org/., Financial Disclosures: Proprietary or commercial disclosure may be found after the references., (© 2023 by the American Academy of Ophthalmology.)

Objective: Predicting the impact of neovascular age-related macular degeneration (nAMD) service disruption on visual outcomes following national lockdown in the UK to contain SARS-CoV-2., Methods and Analysis: This retrospective cohort study includes deidentified data from 2229 UK patients from the INSIGHT Health Data Research digital hub. We forecasted the number of treatment-naïve nAMD patients requiring anti-vascular endothelial growth factor (anti-VEGF) initiation during UK lockdown (16 March 2020 through 31 July 2020) at Moorfields Eye Hospital (MEH) and University Hospitals Birmingham (UHB). Best-measured visual acuity (VA) changes without anti-VEGF therapy were predicted using post hoc analysis of Minimally Classic/Occult Trial of the Anti-VEGF Antibody Ranibizumab in the Treatment of Neovascular AMD trial sham-control arm data (n=238)., Results: At our centres, 376 patients were predicted to require anti-VEGF initiation during lockdown (MEH: 325; UHB: 51). Without treatment, mean VA was projected to decline after 12 months. The proportion of eyes in the MEH cohort predicted to maintain the key positive visual outcome of ≥70 ETDRS letters (Snellen equivalent 6/12) fell from 25.5% at baseline to 5.8% at 12 months (UHB: 9.8%-7.8%). Similarly, eyes with VA <25 ETDRS letters (6/96) were predicted to increase from 4.3% to 14.2% at MEH (UHB: 5.9%-7.8%) after 12 months without treatment., Conclusions: Here, we demonstrate how combining data from a recently founded national digital health data repository with historical industry-funded clinical trial data can enhance predictive modelling in nAMD. The demonstrated detrimental effects of prolonged treatment delay should incentivise healthcare providers to support nAMD patients accessing care in safe environments., Trial Registration Number: NCT00056836., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: The rhetoric surrounding clinical artificial intelligence (AI) often exaggerates its effect on real-world care. Limited understanding of the factors that influence its implementation can perpetuate this., Objective: In this qualitative systematic review, we aimed to identify key stakeholders, consolidate their perspectives on clinical AI implementation, and characterize the evidence gaps that future qualitative research should target., Methods: Ovid-MEDLINE, EBSCO-CINAHL, ACM Digital Library, Science Citation Index-Web of Science, and Scopus were searched for primary qualitative studies on individuals' perspectives on any application of clinical AI worldwide (January 2014-April 2021). The definition of clinical AI includes both rule-based and machine learning-enabled or non-rule-based decision support tools. The language of the reports was not an exclusion criterion. Two independent reviewers performed title, abstract, and full-text screening with a third arbiter of disagreement. Two reviewers assigned the Joanna Briggs Institute 10-point checklist for qualitative research scores for each study. A single reviewer extracted free-text data relevant to clinical AI implementation, noting the stakeholders contributing to each excerpt. The best-fit framework synthesis used the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. To validate the data and improve accessibility, coauthors representing each emergent stakeholder group codeveloped summaries of the factors most relevant to their respective groups., Results: The initial search yielded 4437 deduplicated articles, with 111 (2.5%) eligible for inclusion (median Joanna Briggs Institute 10-point checklist for qualitative research score, 8/10). Five distinct stakeholder groups emerged from the data: health care professionals (HCPs), patients, carers and other members of the public, developers, health care managers and leaders, and regulators or policy makers, contributing 1204 (70%), 196 (11.4%), 133 (7.7%), 129 (7.5%), and 59 (3.4%) of 1721 eligible excerpts, respectively. All stakeholder groups independently identified a breadth of implementation factors, with each producing data that were mapped between 17 and 24 of the 27 adapted Nonadoption, Abandonment, Scale-up, Spread, and Sustainability subdomains. Most of the factors that stakeholders found influential in the implementation of rule-based clinical AI also applied to non-rule-based clinical AI, with the exception of intellectual property, regulation, and sociocultural attitudes., Conclusions: Clinical AI implementation is influenced by many interdependent factors, which are in turn influenced by at least 5 distinct stakeholder groups. This implies that effective research and practice of clinical AI implementation should consider multiple stakeholder perspectives. The current underrepresentation of perspectives from stakeholders other than HCPs in the literature may limit the anticipation and management of the factors that influence successful clinical AI implementation. Future research should not only widen the representation of tools and contexts in qualitative research but also specifically investigate the perspectives of all stakeholder HCPs and emerging aspects of non-rule-based clinical AI implementation., Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021256005; https://www.crd.york.ac.uk/prospero/display&#95;record.php?RecordID=256005., International Registered Report Identifier (irrid): RR2-10.2196/33145., (©Henry David Jeffry Hogg, Mohaimen Al-Zubaidy, Technology Enhanced Macular Services Study Reference Group, James Talks, Alastair K Denniston, Christopher J Kelly, Johann Malawana, Chrysanthi Papoutsi, Marion Dawn Teare, Pearse A Keane, Fiona R Beyer, Gregory Maniatopoulos. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.01.2023.)

Rigorous evaluation of artificial intelligence (AI) systems for image classification is essential before deployment into health-care settings, such as screening programmes, so that adoption is effective and safe. A key step in the evaluation process is the external validation of diagnostic performance using a test set of images. We conducted a rapid literature review on methods to develop test sets, published from 2012 to 2020, in English. Using thematic analysis, we mapped themes and coded the principles using the Population, Intervention, and Comparator or Reference standard, Outcome, and Study design framework. A group of screening and AI experts assessed the evidence-based principles for completeness and provided further considerations. From the final 15 principles recommended here, five affect population, one intervention, two comparator, one reference standard, and one both reference standard and comparator. Finally, four are appliable to outcome and one to study design. Principles from the literature were useful to address biases from AI; however, they did not account for screening specific biases, which we now incorporate. The principles set out here should be used to support the development and use of test sets for studies that assess the accuracy of AI within screening programmes, to ensure they are fit for purpose and minimise bias., Competing Interests: Declaration of interests BG reports receiving stock options given for a role as scientific adviser for Kheiron Medical Technologies outside the submitted work. FSe and GK were employed by the UK National Screening Committee, that was hosted by Public Health England, during the conduct of this study. ST-P has received funding from the UK National Institute for Health Research in the form of a development fellowship payment to her institution for a broad group of work in evaluating screening tests. SH is the Chair of the UK National Screening Committee Artificial Intelligence Task Group, which received institutional funding from the National Institute for Health and Care Research biomedical research centre. LW is a member of the Optimam Steering Group. AC declares reimbursement for paid consultancy from Paige AI outside the submitted work. AC and FSh report that as employees of King's Technology Evaluation Centre they received funding from the UK National Screening Committee to complete this study. All other authors declare no competing interests., (Copyright © 2022 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.)

Non-infectious uveitis represents a heterogenous group of immune-mediated ocular diseases, which can be associated with underlying systemic disease. While the initial choice of treatment of non-infectious uveitis depends on a number of factors such as anatomical location and degree of inflammation, topical therapies often remain the initial choice of non-invasive therapy. In this narrative review, we aim to describe the literature on non-infectious uveitis, with specific focus on the current perspective on topical anti-inflammatory therapy., Competing Interests: The authors report no conflicts of interest in this work., (© 2022 Balasubramaniam et al.)

Near-infrared (NIR) chemical fluorophores are promising tools for in-vivo imaging in real time but often succumb to rapid photodegradation. Indocyanine green (ICG) is the only NIR dye with regulatory approval for ocular imaging in humans; however, ICG, when employed for applications such as labelling immune cells, has limited sensitivity and does not allow precise detection of specific inflammatory events, for example leukocyte recruitment during uveitic flare-ups. We investigated the potential use of photostable novel triazole NIR cyanine (TNC) dyes for detecting and characterising activated T-cell activity within the eye. Three TNC dyes were evaluated for ocular cytotoxicity in-vitro using a MTT assay and optimised concentrations for intraocular detection within ex-vivo porcine eyes after topical application or intracameral injections of the dyes. TNC labelled T-cell tracking experiments and mechanistic studies were also performed in-vitro. TNC-1 and TNC-2 dyes exhibited greater fluorescence intensity than ICG at 10 μM, whereas TNC-3 was only detectable at 100 μM within the porcine eye. TNC dyes did not demonstrate any ocular cell toxicity at working concentrations of 10 μM. CD4 + T-cells labelled with TNC-1 or TNC-2 were detected within the porcine eye, with TNC-1 being brighter than TNC-2. Detection of TNC-1 and TNC-2 into CD4 + T-cells was prevented by prior incubation with dynole 34-2 (50 μM), suggesting active uptake of these dyes via dynamin-dependent processes. The present study provides evidence that TNC dyes are suitable to detect activated CD4 + T-cells within the eye with potential as a diagnostic marker for ocular inflammatory diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)