Remote follow-up after cataract surgery (CORE-RCT): study protocol of a randomized controlled trial.

BACKGROUND: Cataract surgery has become one of the most performed surgical procedures worldwide. Postoperative management consists of routine clinical examinations to assess post-operative visual function and detect possible adverse events. Due to the low incidence of complications, the majority of clinic visits after cataract surgery are uneventful. Nonetheless, valuable time and hospital resources are consumed. We hypothesize that remote post-operative follow-up involving teleconsultations and self-assessments of visual function and health status, could be a valid alternative to face-to-face clinical examinations in selected patient groups. The practice of remote follow-up after cataract surgery has not yet been evaluated. The aim of this study is to investigate the validity, safety and cost-effectiveness of remote cataract surgery follow-up, and to report on the patients' experiences with remotely self-assessing visual function. METHODS: This study is a multicenter, open-label, randomized controlled trial. Patients planned for cataract surgery on both eyes, without ocular comorbidities, are eligible for participation. Participants will be allocated (1:1) into one of the two study groups: 'telemonitoring' or 'usual care'. Participants in the 'telemonitoring' group will perform in-home assessments after cataract surgery (remote web-based eye exams and digital questionnaires on their own devices). Participants in the 'usual care' group will have regular post-operative consultations, according to the study site's regular practice. Outcome measures include accuracy of the web-based eye exam for assessing visual acuity and refraction, patient-reported outcome measures (visual function and quality of life), adverse events, and cost aspects. DISCUSSION: Investigating remote follow-up after cataract surgery fits the current trends of digitization of health care. We believe that remote self-care can be a promising avenue to comply with the increasing demands of cataract care. This randomized controlled trial provides scientific evidence on this unmet need and delivers the desired insights on (cost)effectiveness of remote follow-up after cataract surgery. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04809402. Date of registration: March 22, 2021.

Diagnostic Reliability of Optical Coherence Tomography Biomarkers for Postsurgical Success in Visual Acuity in Patients with Idiopathic Epiretinal Membranes. / Diagnostische Reliabilität von optischen Kohärenztomografie-Biomarkern für postoperativen Erfolg bei idiopathischen epiretinalen Membranen.

INTRODUCTION: Several optical coherence tomography (OCT) biomarkers for postsurgical success in patients with idiopathic epiretinal membranes (iERMs) have been described in single predictor analyses. The aim of this study was to assess the reliability of diagnosis of OCT biomarkers and to calculate their impact on postsurgical visual acuity by applying multiple regression analysis. METHODS: This retrospective study included patients scheduled for pars plana vitrectomy with membrane peeling for iERMs. Presurgical OCT scans were analyzed for the presence of OCT biomarkers by two reviewers. Intra- and interobserver reliability was calculated with the Kuder-Richardson 20 test. RESULTS: Among the 136 patients included, intra-/interobserver reliability of the OCT biomarkers was 0.89/0.70 for ectopic inner foveal layer (EIFL), 0.82/0.53 for disorganization of retinal inner layer (DRIL), 0.93/0.89 for intraretinal cystoid changes, 0.84/0.78 for alterations of the ellipsoid zone, 0.84/0.72 for cotton ball sign, 0.68/0.58 for hyperreflective foci, 0.55/0.47 for epimacular membrane rips (EMM-rips), and 0.87/0.60 for retinal contraction. Only DRIL and central subfield macular thickness (CMT) were significant predictors for BCVA 3 months after surgery in a multiple regression analysis. CONCLUSION: Intraobserver reliability of OCT biomarkers was higher than interobserver reliability, reflecting both clinical and grading experience with respect to OCT biomarker evaluation. DRIL and CMT were shown to be significant predictors in a multiple regression analysis, with potential for negative influence on final BCVA after vitrectomy with membrane peeling for iERMs.

Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges.

The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the development of deep learning models tailored for specific imaging tasks. Additionally, the advent of multimodal foundational models, capable of generating images, text and videos, presents a broad spectrum of applications within ophthalmology. These range from enhancing diagnostic accuracy to improving patient education and training healthcare professionals. Despite the promising potential, this area of technology is still in its infancy, and there are several challenges to be addressed, including data bias, safety concerns and the practical implementation of these technologies in clinical settings.

Sight threatening diabetic retinopathy in patients with macular telangiectasia type 2.

PURPOSE: Although diabetes is highly prevalent in patients with MacTel, progression to severe non-proliferative (NPDR) and proliferative diabetic retinopathy (PDR) is rarely reported. We report multimodal imaging features of sight-threatening diabetic retinopathy (STDR) in eyes with macular telangiectasia type 2 (MacTel). METHODS: Retrospective case series of seven participants of the MacTel Study at the Moorfields Eye Hospital NHS Foundation Trust study site and one patient from the Institute of Retina and Vitreous of Londrina, Brazil. Sight threatening diabetic retinopathy was defined as severe NPDR, PDR or diabetic macular edema. RESULTS: We report imaging features of 16 eyes of eight patients (7/8, 87.5% female) with diagnoses of MacTel and type 2 diabetes mellitus with STDR. Mean (SD) age was 56 (8.3) years. Patients were followed-up for a mean time of 9.1 (4.7) years. A total of 10/16 (62.5%) eyes showed PDR and 2/16 (12.5%) eyes presented a macular epiretinal neovascularization. CONCLUSIONS: People with diabetes mellitus and MacTel may not be protected from STDR as previously reported. Although the two diseases rarely co-exist, regular monitoring for diabetic retinopathy progression is recommended according to baseline retinopathy severity grades in line with established international guidelines. The presence of MacTel may not modify extended screening intervals, but there is no current evidence. The limited case series in the literature support treatment for complications and should follow the standard of care for either condition. Due to dual pathology, reactivation may be difficult to diagnose on standard imaging and multimodal imaging is recommended.

Digital Exclusion, Social Deprivation, and Clinical Outcomes of Patients Undergoing Hyperacuity Home Monitoring.

INTRODUCTION: Digital exclusion is a growing challenge when deploying digital patient care pathways and a potential barrier to widespread implementation, especially in the field of smartphone-based self-monitoring of vision. This retrospective case series seeks to examine the characteristics of individuals who adhere to a smartphone home monitoring programme using the Alleye app for retinal disease, with a focus on digital exclusion, social deprivation and clinical outcomes. METHODS: We conducted a retrospective analysis of 89 patients with retinal pathologies including diabetic retinopathy and retinal vein occlusions at Moorfields Eye Hospital participating in an Alleye home monitoring programme between April 2020 and November 2022. Postcodes were used to determine the Digital Exclusion Risk Index (DERI) and the Index of Multiple Deprivation (IMD) rebased for London. Clinical information from the electronic patient record and Alleye app usage data were extracted for each patient. Associations between the DERI/IMD, clinical parameters and app use were examined using multivariable regression models. RESULTS: Mean DERI was 2.56 (standard deviation [SD] = 0.36), IMD was 6.25 (SD = 2.79), visual acuity (VA) in the better eye at study entry was 83.28 Early Treatment Diabetic Retinopathy Study (ETDRS) letters (SD = 7.92), and mean follow-up was 344.46 days (SD = 260.13). During the observation period, 36% received an intravitreal injection (IVI) and VA fell by at least ten letters in approximately one in four patients. In 87.5% of patients requiring IVI, the use of the app increased. We found no association between clinical parameters and programme adherence for DERI or IMD. CONCLUSIONS: We found no association between high digital exclusion risk and high social deprivation with monitoring adherence to smartphone-based self-monitoring of vision, contrary to the currently available evidence. This suggests that smartphone-based self-monitoring of vision is accessible to population groups of varying digital exclusion and social deprivation risk, and can be safely employed to monitor clinical progression.

Exploring Patient Demographics and Presence of Retinal Vascular Disease in Paracentral Acute Middle Maculopathy.

PURPOSE: To investigate the sociodemographic profile, the association with retinal vascular diseases (RVD) and systemic comorbidities, and visual outcomes of patients with paracentral acute middle maculopathy (PAMM) in a large, ethnically diverse single-center cohort. DESIGN: Retrospective cohort study. METHODS: Electronic health record query for all patients presenting with PAMM at Moorfields Eye Hospital, London, was completed. Detailed demographic, clinical, and systemic information were collected and analyzed. RESULTS: A total of 78 eyes of 78 patients with confirmed PAMM were included in the study. Forty patients (51.3%) presented with no RVD, 20 patients (25.6%) with retinal vein occlusion (RVO), 16 patients (20.5%) with retinal artery occlusion (RAO), and 2 patients (2.6%) with concomitant RAO and RVO. Patients with PAMM+RAO were older than those with RVO (P = .02) and more likely to have a history of major adverse cardiovascular events (MACE) (P = .01), with a significantly worse presenting best corrected visual acuity (BCVA) (20/50) compared to patients with RVO (P = .02) and no RVD (P < .001). Individuals with isolated PAMM had a significantly higher prevalence of previous MACE (P = .04) and sickle cell disease (SCD) (P = .04) compared to those with RVO. At the last follow-up, 64 patients (85.3%) had a good BCVA (>20/32). CONCLUSIONS: The significant association of PAMM with RVD supports the hypothesis of an ischemic etiology. Individuals with isolated PAMM had a higher prevalence of MACE and SCD. Thus, it is important to prompt immediate referral for a comprehensive systemic evaluation. Across the whole cohort, PAMM was associated with good BCVA improvement during follow-up, indicating a good visual prognosis.

Determinants of non-attendance at face-to-face and telemedicine ophthalmic consultations.

BACKGROUND/AIMS: Evaluation of telemedicine care models has highlighted its potential for exacerbating healthcare inequalities. This study seeks to identify and characterise factors associated with non-attendance across face-to-face and telemedicine outpatient appointments. METHODS: A retrospective cohort study at a tertiary-level ophthalmic institution in the UK, between 1 January 2019 and 31 October 2021. Logistic regression modelled non-attendance against sociodemographic, clinical and operational exposure variables for all new patient registrations across five delivery modes: asynchronous, synchronous telephone, synchronous audiovisual and face to face prior to the pandemic and face to face during the pandemic. RESULTS: A total of 85 924 patients (median age 55 years, 54.4% female) were newly registered. Non-attendance differed significantly by delivery mode: (9.0% face to face prepandemic, 10.5% face to face during the pandemic, 11.7% asynchronous and 7.8%, synchronous during pandemic). Male sex, greater levels of deprivation, a previously cancelled appointment and not self-reporting ethnicity were strongly associated with non-attendance across all delivery modes. Individuals identifying as black ethnicity had worse attendance in synchronous audiovisual clinics (adjusted OR 4.24, 95% CI 1.59 to 11.28) but not asynchronous. Those not self-reporting their ethnicity were from more deprived backgrounds, had worse broadband access and had significantly higher non-attendance across all modes (all p<0.001). CONCLUSION: Persistent non-attendance among underserved populations attending telemedicine appointments highlights the challenge digital transformation faces for reducing healthcare inequalities. Implementation of new programmes should be accompanied by investigation into the differential health outcomes of vulnerable populations.

Paracentral acute middle maculopathy and risk of cardiovascular disease, stroke, and death: a longitudinal study.

PURPOSE: To evaluate the risk of acute cardiovascular events (CVE), including cardiovascular diseases, cerebrovascular diseases, and all-cause mortality in patients with paracentral acute middle maculopathy (PAMM). DESIGN: Retrospective cohort study METHODS: We studied 43 individuals with optical coherence tomography -documented PAMM attending Moorfields Eye Hospital between January 2014 and June 2021. We excluded patients with preceding (< 2 years) major adverse cardiac events. We stratified patients by age (<50 years & ≥50 years) and whether associated with retinal vascular diseases (RVD) or isolated (iPAMM). We assessed risk factors, clinical characteristics, and visual prognosis of the patients. CVE risk was estimated using Kaplan-Meier curves, the log-rank test, and Cox proportional hazards regression. RESULTS: In young patients with iPAMM patients (n=12), underlying predisposing factors included six (50%) sickle cell disease and five (41.6%) others, including breakthrough bleeding in pregnancy, migraine, genetic cardiomyopathy, amphetamine use; among those with PAMM+RVD (n=12) one (9%) had a vascular disorder, and four (44.4%) oral contraceptive use. In the older group of 20 patients, 15 (75%) had at least one coronary risk factor. During a median follow-up of 14 months (range 12-54), older subjects with iPAMM had a higher risk of developing CVE than those with PAMM+RVD (p<0.001). Notably, iPAMM displayed a significantly earlier peak in peri-PAMM CVE risk compared to PAMM+RVD (median: 1 month, range 1-40 months vs. 36 months, range 12-54 months). Relative to those with PAMM+RVD, risk of CVE was significantly higher in patients with iPAMM, adjusted for age and sex (hazard ratio: 6.37, 95% Confidence Interval 1.68-24.14, p=0.017). No young patients experienced adverse CVE. At baseline, older iPAMM patients mean best corrected visual acuity of 0.7 (0-1.8) LogMAR, which improved significantly to 0.2 (0-1.30) LogMAR at the latest visit (p=0.033). CONCLUSION: Young individuals with iPAMM have a higher prevalence of predisposing factors compared to those presenting with combined PAMM+RVD. Older patients with iPAMM had a higher risk of CVE than those with PAMM+RVD, especially in the peri-onset timeframe. This suggests the need for a prompt cardiovascular assessment to rule out systemic etiologies and optimize cardiovascular risk factors, in addition to ongoing ophthalmology input.

Exudative Progression of Treatment-Naïve Nonexudative Macular Neovascularization in Age-Related Macular Degeneration: A Systematic Review With Meta-Analyses.

PURPOSE: To systematically review and report the rate of exudative progression over time in patients with nonexudative macular neovascularization (MNV) in age-related macular degeneration (AMD). DESIGN: Systematic review with prevalence meta-analyses and individual participant meta-analysis. METHODS: We searched 10 literature databases on March 26, 2023, for studies of consecutive patients with treatment-naïve nonexudative MNV in AMD. The primary outcome of interest was time from diagnosis to exudative progression. We conducted meta-analyses on the prevalence of exudative progression at 1 and 2 years. Where possible, we extracted individual participant data from studies and conducted an individual participant meta-analysis and explored the exudative progression using a time-to-event curve. RESULTS: We identified 16 eligible studies with a total of 384 eyes with nonexudative MNV. Exudative progression had occurred in 20.9% (95% CI 13.1%-29.8%) of eyes at 1 year and in 30.7% (95% CI 21.8%-40.4%) at 2 years. Similar results were observed in the individual participant meta-analysis, showing exudative progression in 18.9% (95% CI 13.5%-26.3%) of eyes at 1 year and 31.3% (95% CI 24.2%-40.0%) at 2 years. Risk factors for a fast exudative progression were the presence of subretinal lipid globules, large MNV areas, rapid MNV growth, growth in pigment epithelium detachment height and width, appearance of a branching pattern, and development of a hyporeflective halo around the MNV. CONCLUSIONS: Nonexudative MNVs in AMD are at high risk of exudative progression. Recognition of these lesions may allow for better individualized follow-up regimens in which closer monitoring may facilitate earlier diagnosis of exudative progression.

Periodontitis and Outer Retinal Thickness: a Cross-Sectional Analysis of the United Kingdom Biobank Cohort.

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.

Teleophthalmology and retina: a review of current tools, pathways and services.

Telemedicine, the use of telecommunication and information technology to deliver healthcare remotely, has evolved beyond recognition since its inception in the 1970s. Advances in telecommunication infrastructure, the advent of the Internet, exponential growth in computing power and associated computer-aided diagnosis, and medical imaging developments have created an environment where telemedicine is more accessible and capable than ever before, particularly in the field of ophthalmology. Ever-increasing global demand for ophthalmic services due to population growth and ageing together with insufficient supply of ophthalmologists requires new models of healthcare provision integrating telemedicine to meet present day challenges, with the recent COVID-19 pandemic providing the catalyst for the widespread adoption and acceptance of teleophthalmology. In this review we discuss the history, present and future application of telemedicine within the field of ophthalmology, and specifically retinal disease. We consider the strengths and limitations of teleophthalmology, its role in screening, community and hospital management of retinal disease, patient and clinician attitudes, and barriers to its adoption.

Clinician-Driven AI: Code-Free Self-Training on Public Data for Diabetic Retinopathy Referral.

Importance: Democratizing artificial intelligence (AI) enables model development by clinicians with a lack of coding expertise, powerful computing resources, and large, well-labeled data sets. Objective: To determine whether resource-constrained clinicians can use self-training via automated machine learning (ML) and public data sets to design high-performing diabetic retinopathy classification models. Design, Setting, and Participants: This diagnostic quality improvement study was conducted from January 1, 2021, to December 31, 2021. A self-training method without coding was used on 2 public data sets with retinal images from patients in France (Messidor-2 [n = 1748]) and the UK and US (EyePACS [n = 58 689]) and externally validated on 1 data set with retinal images from patients of a private Egyptian medical retina clinic (Egypt [n = 210]). An AI model was trained to classify referable diabetic retinopathy as an exemplar use case. Messidor-2 images were assigned adjudicated labels available on Kaggle; 4 images were deemed ungradable and excluded, leaving 1744 images. A total of 300 images randomly selected from the EyePACS data set were independently relabeled by 3 blinded retina specialists using the International Classification of Diabetic Retinopathy protocol for diabetic retinopathy grade and diabetic macular edema presence; 19 images were deemed ungradable, leaving 281 images. Data analysis was performed from February 1 to February 28, 2021. Exposures: Using public data sets, a teacher model was trained with labeled images using supervised learning. Next, the resulting predictions, termed pseudolabels, were used on an unlabeled public data set. Finally, a student model was trained with the existing labeled images and the additional pseudolabeled images. Main Outcomes and Measures: The analyzed metrics for the models included the area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, and F1 score. The Fisher exact test was performed, and 2-tailed P values were calculated for failure case analysis. Results: For the internal validation data sets, AUROC values for performance ranged from 0.886 to 0.939 for the teacher model and from 0.916 to 0.951 for the student model. For external validation of automated ML model performance, AUROC values and accuracy were 0.964 and 93.3% for the teacher model, 0.950 and 96.7% for the student model, and 0.890 and 94.3% for the manually coded bespoke model, respectively. Conclusions and Relevance: These findings suggest that self-training using automated ML is an effective method to increase both model performance and generalizability while decreasing the need for costly expert labeling. This approach advances the democratization of AI by enabling clinicians without coding expertise or access to large, well-labeled private data sets to develop their own AI models.

Diagnostic Accuracy of the Amsler Grid Test for Detecting Neovascular Age-Related Macular Degeneration: A Systematic Review and Meta-analysis.

Importance: Patients with nonneovascular age-related macular degeneration (AMD) are encouraged to use the Amsler grid test for self-assessment to facilitate early diagnosis. The test is widely recommended, suggesting a belief that it signals worsening AMD, warranting its use in home monitoring. Objective: To systematically review studies of the diagnostic test accuracy of the Amsler grid in the diagnosis of neovascular AMD and to perform diagnostic test accuracy meta-analyses. Data Sources: A systematic literature search was conducted in 12 databases for relevant titles from database inception until May 7, 2022. Study Selection: Studies included those with groups defined as having (1) neovascular AMD and (2) either healthy eyes or eyes with nonneovascular AMD. The index test was the Amsler grid. The reference standard was ophthalmic examination. After removal of obviously irrelevant reports, 2 authors (J.B. and M.S.) independently screened the remaining references in full text for potential eligibility. Disagreements were resolved by a third author (Y.S.). Data Extraction and Synthesis: Two authors (J.B. and I.P.) independently extracted all data and evaluated quality and applicability of eligible studies using the Quality Assessment of Diagnostic Accuracy Studies 2. Disagreements were resolved by a third author (Y.S.). Main Outcomes and Measures: Sensitivity and specificity of the Amsler grid for detecting neovascular AMD with comparators being either healthy control participants or patients with nonneovascular AMD. Results: Of 523 records screened, 10 studies were included with a total of 1890 eyes (mean participant age ranging from 62 to 83 years). Sensitivity and specificity to diagnose neovascular AMD were 67% (95% CI, 51%-79%) and 99% (95% CI, 85%-100%), respectively, when comparators were healthy control participants and 71% (95% CI, 60%-80%) and 63% (95% CI, 49%-51%), respectively, when control participants were patients with nonneovascular AMD. Overall, potential sources of bias were low across studies. Conclusions and Relevance: Although the Amsler grid is easy and inexpensive to use for detection of metamorphopsia, its sensitivity may be at levels typically not recommended for monitoring. Coupling this lower sensitivity with only moderate specificity to identify neovascular AMD in a population at risk, these findings suggest that such patients typically should be encouraged to undergo ophthalmic examination regularly, regardless of any results of Amsler grid self-assessment.

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior capsule opacification (PCO) and to discriminate between clinically significant and non-significant PCOs. METHODS AND ANALYSIS: For this retrospective registry study, three expert observers graded two independent datasets of 279 images three separate times with no PCO to severe PCO, providing binary labels for clinical significance. The CFDLS was trained and internally validated using 179 images of a training dataset and externally validated with 100 images. Model development was through Google Cloud AutoML Vision. Intraobserver and interobserver variabilities were assessed using Fleiss kappa (κ) coefficients and model performance through sensitivity, specificity and area under the curve (AUC). RESULTS: Intraobserver variability κ values for observers 1, 2 and 3 were 0.90 (95% CI 0.86 to 0.95), 0.94 (95% CI 0.90 to 0.97) and 0.88 (95% CI 0.82 to 0.93). Interobserver agreement was high, ranging from 0.85 (95% CI 0.79 to 0.90) between observers 1 and 2 to 0.90 (95% CI 0.85 to 0.94) for observers 1 and 3. On internal validation, the AUC of the CFDLS was 0.99 (95% CI 0.92 to 1.0); sensitivity was 0.89 at a specificity of 1. On external validation, the AUC was 0.97 (95% CI 0.93 to 0.99); sensitivity was 0.84 and specificity was 0.92. CONCLUSION: This CFDLS provides highly accurate discrimination between clinically significant and non-significant PCO equivalent to human expert graders. The clinical value as a potential decision support tool in different models of care warrants further research.

Re-evaluating diabetic papillopathy using optical coherence tomography and inner retinal sublayer analysis.

BACKGROUND/OBJECTIVES: To re-evaluate diabetic papillopathy using optical coherence tomography (OCT) for quantitative analysis of the peripapillary retinal nerve fibre layer (pRNFL), macular ganglion cell layer (mGCL) and inner nuclear layer (mINL) thickness. SUBJECTS/METHODS: In this retrospective observational case series between June 2008 and July 2019 at Moorfields Eye hospital, 24 eyes of 22 patients with diabetes and optic disc swelling with confirmed diagnosis of NAION or diabetic papillopathy by neuro-ophthalmological assessment were included for evaluation of the pRNFL, mGCL and mINL thicknesses after resolution of optic disc swelling. RESULTS: The mean age of included patients was 56.5 (standard deviation (SD) ± 14.85) years with a mean follow-up duration of 216 days. Thinning of pRNFL (mean: 66.26, SD ± 31.80 µm) and mGCL (mean volume: 0.27 mm3, SD ± 0.09) were observed in either group during follow-up, the mINL volume showed no thinning with 0.39 ± 0.05 mm3. The mean decrease in visual acuity was 4.13 (SD ± 14.27) ETDRS letters with a strong correlation between mGCL thickness and visual acuity (rho 0.74, p < 0.001). CONCLUSION: After resolution of acute optic disc swelling, atrophy of pRNFL and mGCL became apparent in all cases of diabetic papillopathy and diabetic NAION, with preservation of mINL volumes. Analysis of OCT did not provide a clear diagnostic distinction between both entities. We suggest a diagnostic overlay with the degree of pRNFL and mGCL atrophy of prognostic relevance for poor visual acuity independent of the semantics of terminology.

Deep Learning to Detect OCT-derived Diabetic Macular Edema from Color Retinal Photographs: A Multicenter Validation Study.

PURPOSE: To validate the generalizability of a deep learning system (DLS) that detects diabetic macular edema (DME) from 2-dimensional color fundus photographs (CFP), for which the reference standard for retinal thickness and fluid presence is derived from 3-dimensional OCT. DESIGN: Retrospective validation of a DLS across international datasets. PARTICIPANTS: Paired CFP and OCT of patients from diabetic retinopathy (DR) screening programs or retina clinics. The DLS was developed using data sets from Thailand, the United Kingdom, and the United States and validated using 3060 unique eyes from 1582 patients across screening populations in Australia, India, and Thailand. The DLS was separately validated in 698 eyes from 537 screened patients in the United Kingdom with mild DR and suspicion of DME based on CFP. METHODS: The DLS was trained using DME labels from OCT. The presence of DME was based on retinal thickening or intraretinal fluid. The DLS's performance was compared with expert grades of maculopathy and to a previous proof-of-concept version of the DLS. We further simulated the integration of the current DLS into an algorithm trained to detect DR from CFP. MAIN OUTCOME MEASURES: The superiority of specificity and noninferiority of sensitivity of the DLS for the detection of center-involving DME, using device-specific thresholds, compared with experts. RESULTS: The primary analysis in a combined data set spanning Australia, India, and Thailand showed the DLS had 80% specificity and 81% sensitivity, compared with expert graders, who had 59% specificity and 70% sensitivity. Relative to human experts, the DLS had significantly higher specificity (P = 0.008) and noninferior sensitivity (P < 0.001). In the data set from the United Kingdom, the DLS had a specificity of 80% (P < 0.001 for specificity of >50%) and a sensitivity of 100% (P = 0.02 for sensitivity of > 90%). CONCLUSIONS: The DLS can generalize to multiple international populations with an accuracy exceeding that of experts. The clinical value of this DLS to reduce false-positive referrals, thus decreasing the burden on specialist eye care, warrants a prospective evaluation.

Henle Fibre Layer Haemorrhage after a Valsalva Manoeuvre.

A male patient, 59 years of age, presented with sudden deterioration of visual acuity (VA) caused by a Henle fibre layer haemorrhage (HFLH) in our outpatient department. He reported being under treatment with acetylsalicylic acid and experienced a Valsalva manoeuvre before he observed reduced vision. Due to the impairment caused by the haemorrhage, disturbing the patient's daily activities, intravitreal injection of recombinant tissue plasminogen activator combined with SF6 and bevacizumab was offered. After this procedure, the HFLH disappeared, VA improved from 20/40 to 20/20 (Snellen) 3 months after treatment and a typical hyperreflective vertical line was seen in optical coherence tomography.

Acute Macular Neuroretinopathy following Coronavirus Disease 2019 Vaccination.

Purpose: To report acute macular neuroretinopathy (AMN) in two young women two days after receiving Vaxzevria Coronavirus disease (COVID-19) vaccination.Methods: Observational case reports.Observation: The first patient was an Italian 22-year-old female with acute onset of paracentral scotoma two days post vaccination. The second patient was an Austrian 28-year-old female who presented with sudden onset paracentral scotoma two days after vaccination. Multimodal retinal imaging was consistent with AMN in both cases. Both patients were on long-term oral contraceptives, had no history of COVID-19 and experienced one-day duration fever the day after the vaccination.Conclusions: Vaccination may represent a possible risk factor for AMN onset in women on oral contraceptives. We encourage ophthalmologists to investigate recent vaccination status when dealing with new onset AMN. Further studies are needed to assess the link between vaccinations and AMN.

Predicting sex from retinal fundus photographs using automated deep learning.

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. Herein we present the development of a deep learning model by clinicians without coding, which predicts reported sex from retinal fundus photographs. A model was trained on 84,743 retinal fundus photos from the UK Biobank dataset. External validation was performed on 252 fundus photos from a tertiary ophthalmic referral center. For internal validation, the area under the receiver operating characteristic curve (AUROC) of the code free deep learning (CFDL) model was 0.93. Sensitivity, specificity, positive predictive value (PPV) and accuracy (ACC) were 88.8%, 83.6%, 87.3% and 86.5%, and for external validation were 83.9%, 72.2%, 78.2% and 78.6% respectively. Clinicians are currently unaware of distinct retinal feature variations between males and females, highlighting the importance of model explainability for this task. The model performed significantly worse when foveal pathology was present in the external validation dataset, ACC: 69.4%, compared to 85.4% in healthy eyes, suggesting the fovea is a salient region for model performance OR (95% CI): 0.36 (0.19, 0.70) p = 0.0022. Automated machine learning (AutoML) may enable clinician-driven automated discovery of novel insights and disease biomarkers.

Widefield optical coherence tomography angiography for early detection and objective evaluation of proliferative diabetic retinopathy.

PURPOSE: To evaluate the utility of widefield optical coherence tomography angiography (WF-OCTA) compared with clinical examination in grading diabetic retinopathy in patients diagnosed clinically with proliferative diabetic retinopathy (PDR) or severe non-proliferative diabetic retinopathy (NPDR). DESIGN: This retrospective observational case series included patients diagnosed clinically with PDR or severe NPDR. Patients underwent standard clinical examination and WF-OCTA imaging (PLEX Elite 9000, Carl Zeiss Meditec AG) using 12×12 montage scans between August 2018 and January 2019. Two trained graders identified neovascularisation at the disc (NVD) and neovascularisation elsewhere (NVE) on WF-OCTA which were compared with the clinical examination, and to ultra-widefield fluorescein angiography (UWFA) when available. RESULTS: Seventy-nine eyes of 46 patients were evaluated. Of those, 57 eyes were diagnosed clinically with PDR, and 22 with severe NPDR. NVD was detected on OCTA-B scan as preretinal hyperreflective material (PRHM) in 39 eyes (100%) with evident flow signals in 79.5% compared with 51.3% detected clinically. We further classified NVD on OCTA into four subtypes and found that subtypes 1 and 2 could not be seen on clinical examination alone. WF-OCTA detected NVE in 81% of the cases compared with 55.7% detected clinically. Using WF-OCTA resulted in a higher percentage of PDR grading (88.6%) than on clinical examination (72.2%). When available, UWFA confirmed the WF-OCTA diagnosis in the majority of cases. CONCLUSION: This study demonstrates that WF-OCTA has a higher detection rate of PDR than clinical examination. This suggests that this modality could be used non-invasively for the purpose of early detection and characterisation of neovascularisation.