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The broad-based term "Global Ophthalmology" commonly elicits images of resource-limited, field-based settings where vast disparities in vision health exist, but also encompasses disparities that also exist in well-resourced countries. 3 Huang Y, Mustapha J, Harrison-Williams L. Global ophthalmic health initiatives in Ebola and emerging infectious diseases: implications for vision health systems, program implementation and disease surveillance. In this issue of International Ophthalmology Clinics (IOC), experienced clinicians, scientists, ophthalmic public health expertise, and partners from multiple countries involved in global ophthalmic health initiatives have contributed a variety of focused articles related to key issues, challenges, and potential solutions within global ophthalmology. [Extracted from the article]

To assess changes in vision care availability at Federally Qualified Health Centers (FQHCs) between 2017 and 2021 and whether neighborhood-level demographic social risk factors (SRFs) associated with eye care services provided by FQHCs. Secondary data analysis of the Health Resources and Services Administration (HRSA) data and 2017–2021 American Community Survey (ACS). Federally Qualified Health Centers. Patient and neighborhood characteristics for SRFs were summarized. Differences in FQHCs providing and not providing vision care were compared via Wilcoxon-Mann–Whitney tests for continuous measures and chi-square tests for categorical measures. Logistic regression models were used to test the associations between neighborhood measures and FQHCs providing vision care, adjusted for patient characteristics. Odds ratios (ORs) with 95% confidence intervals (CIs) for neighborhood-level predictors of FQHCs providing vision care services. Overall, 28.5% of FQHCs (n = 375/1318) provided vision care in 2017 versus 32% (n = 435/1362) in 2021 with some increases and decreases in both the number of FQHCs and those with and without vision services. Only 2.6% of people who accessed FQHC services received eye care in 2021. Among the 435 FQHCs that provided vision care in 2021, 27.1% (n = 118) had added vision services between 2017 and 2021, 71.5% (n = 311) had been offering vision services since at least 2017, and 1.4% (n = 6) were newly established. FQHCs providing vision care in 2021 were more likely to be in neighborhoods with a higher percentage of Hispanic/Latino individuals (OR, 1.08, 95% CI, 1.02–1.14, P = 0.0094), Medicaid-insured individuals (OR, 1.08, 95% CI, 1.02–1.14, P = 0.0120), and no car households (OR, 1.07, 95% CI, 1.01–1.13, P = 0.0142). However, FQHCs with vision care, compared to FQHCs without vision care, served a lower percentage of Hispanic/Latino individuals (27.2% vs. 33.9%, P = 0.0007), Medicaid-insured patients (42.8% vs. 46.8%, P < 0.0001), and patients living at or below 100% of the federal poverty line (61.3% vs. 66.3%, P < 0.0001). Vision care services are available at a few FQHCs, localized to a few states. Expanding eye care access at FQHCs would meet patients where they seek care to mitigate vision loss to underserved communities. Proprietary or commercial disclosure may be found after the references. [ABSTRACT FROM AUTHOR]

To examine the association between neighborhood-level social vulnerability and adherence to scheduled ophthalmology appointments. In this retrospective cohort study, records of all patients ≥18 years scheduled for an ophthalmology appointment between September 12, 2020, and February 8, 2021, were reviewed. Primary exposure is neighborhood-level Social Vulnerability Index (SVI) based on the patient's residential location. SVI is a rank score of 15 social factors into four themes (socioeconomic status, household composition/disability, minority status/language, and housing type/transportation), ranging from 0 to 1.0, with higher ranks indicating greater social vulnerability. The overall SVI score and each theme were analyzed separately as the primary exposure of interest in multivariable logistic regression models that controlled for age, sex, appointment status (new or established), race, and distance from clinic. The primary outcome, non-adherence, was defined as missing more than 25% of scheduled appointments. Of 8,322 patients (41% non-Hispanic Black, 24% Hispanic, 22% non-Hispanic White) with scheduled appointments, 28% were non-adherent. Non-adherence was associated with greater social vulnerability (adjusted odds ratio [aOR] per 0.01 increase in overall SVI = 2.46 [95% confidence interval, 1.99, 3.06]) and each SVI theme (socioeconomic status: aOR = 2.38 [1.94, 2.91]; household composition/disability: aOR = = 1.51 [1.26, 1.81]; minority status/language: aOR = 2.03 [1.55, 2.68]; housing type/transportation: aOR = 1.41 [1.16, 1.73]). Neighborhood-level social vulnerability is associated with greater risk of non-adherence to scheduled ophthalmology appointments, controlling for individual characteristics. Multi-level intervention strategies that incorporate neighborhood-level vulnerabilities are needed to reduce disparities in access to ophthalmology care. [ABSTRACT FROM AUTHOR]

Purpose To evaluate a tele-education system developed to improve diagnostic competency in retinopathy of prematurity (ROP) by ophthalmologists-in-training in Mexico. Design Prospective, randomized cohort study. Participants Fifty-eight ophthalmology residents and fellows from a training program in Mexico consented to participate. Twenty-nine of 58 trainees (50%) were randomized to the educational intervention (pretest, ROP tutorial, ROP educational chapters, and posttest), and 29 of 58 trainees (50%) were randomized to a control group (pretest and posttest only). Methods A secure web-based educational system was created using clinical cases (20 pretest, 20 posttest, and 25 training chapter–based) developed from a repository of over 2500 unique image sets of ROP. For each image set used, a reference standard ROP diagnosis was established by combining the clinical diagnosis by indirect ophthalmoscope examination and image-based diagnosis by multiple experts. Trainees were presented with image-based clinical cases of ROP during a pretest, posttest, and training chapters. Main Outcome Measures The accuracy of ROP diagnosis (e.g., plus disease, zone, stage, category) was determined using sensitivity and specificity calculations from the pretest and posttest results of the educational intervention group versus control group. The unweighted kappa statistic was used to analyze the intragrader agreement for ROP diagnosis by the ophthalmologists-in-training during the pretest and posttest for both groups. Results Trainees completing the tele-education system had statistically significant improvements ( P < 0.01) in the accuracy of ROP diagnosis for plus disease, zone, stage, category, and aggressive posterior ROP (AP-ROP). Compared with the control group, trainees who completed the ROP tele-education system performed better on the posttest for accurately diagnosing plus disease (67% vs. 48%; P = 0.04) and the presence of ROP (96% vs. 91%; P < 0.01). The specificity for diagnosing AP-ROP (94% vs. 78%; P < 0.01), type 2 ROP or worse (92% vs. 84%; P = 0.04), and ROP requiring treatment (89% vs. 79%; P < 0.01) was better for the trainees completing the tele-education system compared with the control group. Intragrader agreement improved for identification of plus disease, zone, stage, and category of ROP after completion of the educational intervention. Conclusions A tele-education system for ROP education was effective in improving the diagnostic accuracy of ROP by ophthalmologists-in-training in Mexico. This system has the potential to increase competency in ROP diagnosis and management for ophthalmologists-in-training from middle-income nations. [ABSTRACT FROM AUTHOR]

Though screening programs may be limited, maintaining ongoing dialogue and relationships with partners in ROP screening will help ensure that as soon as resources are available, ROP screening and treatment programs can resume. In a recent study, most parents reported being educated about ROP at time of discharge through verbal explanation by providers or written materials, while less than 15% reported learning about ROP from online resources or videos.[35] This method of education requires providers to be educated and frequently updated about ROP--a well described area of improvement for ROP screening in many countries. In a population of parents of ROP patients in Massachusetts and South Carolina, limited understanding of ROP, feeling overwhelmed, and lack of resources to address social stressors significantly limited parents' ability to manage their child's healthcare.[56] Suggestions to increase parent adherence with screening and follow-up include thorough ROP parent education, optimizing insurance coverage, reducing transportation costs, and absences from work excused with appropriate documentation. The 10 Essential Public Health Services Model Challenges to Retinopathy of Prematurity (ROP) Screening and the Need for a Model to Evaluate... ROP is one the leading causes of preventable childhood blindness in the world.[1] In 2010, an estimate of 184,700 preterm infants worldwide developed some degree of ROP, and of these, 53,800 developed visually impairing severe disease (Blencowe et al 2010). [Extracted from the article]

Global Ophthalmology: A US-Based Academic Fellowship Subsequently, Dr Tabin returned to the United States and took a position as the Cornea Fellowship Director at the University of Utah Moran Eye Center. These are some common questions that arise in deciding to pursue a subspecialty career in Global Ophthalmology (GO) and specifically a GO Fellowship. Unique to GO fellowship training is an introductory fellowship retreat to introduce the core concepts of the shared GO curriculum and public health foundations of global ophthalmology. [Extracted from the article]

Prior seminal studies in ophthalmology have highlighted the impact of vision science research in LMICs on both vision and systemic health, particularly where leading discoveries have directly led to actions. The American Academy of Ophthalmology (AAO) Task Force on Academic Global Ophthalmology was convened to catalyze development of AAO guidance and perspectives related to clinical service, education, and research initiatives within the field of I Global Ophthalmology i . The Lancet Global Health Commission on Global Eye Health: vision beyond 2020. The I Lancet Global Health i Commission on Global Eye Health defined eye health as "maximized vision, ocular health and functional ability, thereby contributing to overall health and wellbeing, social inclusion, and quality of life."[7] The contribution of vision health to individual well-being includes improved educational outcomes, work productivity, and reduced disparities. [Extracted from the article]

The purpose of a curriculum in global ophthalmology (GO) for trainees is difficult to define, given that there may be different motivations depending on the practitioners' perspective. Principles of GO Education A successful GO practitioner is not only highly clinically and surgically competent, but may have a background in systems-based care, program evaluation, public health, global health financing, ethics, research methods, and harm reduction.[[3]] The ideal GO curriculum is challenging to define, as we will explore, due to the heterogeneity in needs to be met. Creating the Curriculum For the capacity building curriculum, we propose a core curriculum with standardized learning objectives that are universally applicable to trainees. The Practitioner's Guide to Global Health: an interactive, online, open-access curriculum preparing medical learners for global health experiences. [Extracted from the article]

To explore individual and community factors associated with adherence to physician recommended urgent eye visits via a tele-triage system during the COVID-19 pandemic. We retrospectively reviewed acute visit requests and medical exam data between April 6, 2020 and June 6, 2020. Patient demographics and adherence to visit were examined. Census tract level community characteristics from the U.S. Census Bureau and zip code level COVID-19 related death data from the Cook County Medical Examiner's Office were appended to each geocoded patient address. Descriptive statistics, t-tests, and logistic regression analyses were performed to explore the effects of individual and community variables on adherence to visit. Of 229 patients recommended an urgent visit, 216 had matching criteria on chart review, and 192 (88.9%) adhered to their visit. No difference in adherence was found based on individual characteristics including: age (p =.24), gender (p =.94), race (p =.56), insurance (p =.28), nor new versus established patient status (p =.20). However, individuals who did not adhere were more likely to reside in neighborhoods with a greater proportion of Blacks (59.4% vs. 33.4%; p =.03), greater unemployment rates (17.5% vs. 10.7%; p <.01), and greater cumulative deaths from COVID-19 (56 vs. 31; p =.01). Unemployment rate continued to be statistically significant after controlling for race and cumulative deaths from COVID-19 (p =.04). We found that as community unemployment rate increases, adherence to urgent eye visits decreases, after controlling for relevant neighborhood characteristics. Unemployment rates were highest in predominantly Black neighborhoods early in the pandemic, which may have contributed to existing racial disparities in eye care. [ABSTRACT FROM AUTHOR]

To validate a vascular severity score as an appropriate output for artificial intelligence (AI) Software as a Medical Device (SaMD) for retinopathy of prematurity (ROP) through comparison with ordinal disease severity labels for stage and plus disease assigned by the International Classification of Retinopathy of Prematurity, Third Edition (ICROP3), committee. Validation study of an AI-based ROP vascular severity score. A total of 34 ROP experts from the ICROP3 committee. Two separate datasets of 30 fundus photographs each for stage (0–5) and plus disease (plus, preplus, neither) were labeled by members of the ICROP3 committee using an open-source platform. Averaging these results produced a continuous label for plus (1–9) and stage (1–3) for each image. Experts were also asked to compare each image to each other in terms of relative severity for plus disease. Each image was also labeled with a vascular severity score from the Imaging and Informatics in ROP deep learning system, which was compared with each grader's diagnostic labels for correlation, as well as the ophthalmoscopic diagnosis of stage. Weighted kappa and Pearson correlation coefficients (CCs) were calculated between each pair of grader classification labels for stage and plus disease. The Elo algorithm was also used to convert pairwise comparisons for each expert into an ordered set of images from least to most severe. The mean weighted kappa and CC for all interobserver pairs for plus disease image comparison were 0.67 and 0.88, respectively. The vascular severity score was found to be highly correlated with both the average plus disease classification (CC = 0.90, P < 0.001) and the ophthalmoscopic diagnosis of stage (P < 0.001 by analysis of variance) among all experts. The ROP vascular severity score correlates well with the International Classification of Retinopathy of Prematurity committee member's labels for plus disease and stage, which had significant intergrader variability. Generation of a consensus for a validated scoring system for ROP SaMD can facilitate global innovation and regulatory authorization of these technologies. [ABSTRACT FROM AUTHOR]

Retinopathy of prematurity (ROP) is a retinal vasoproliferative disease that affects premature infants. Despite improvements in neonatal care and management guidelines, ROP remains a leading cause of childhood blindness worldwide. Current screening guidelines are primarily based on two risk factors: birth weight and gestational age; however, many investigators have suggested other risk factors, including maternal factors, prenatal and perinatal factors, demographics, medical interventions, comorbidities of prematurity, nutrition, and genetic factors. We review the existing literature addressing various possible ROP risk factors. Although there have been contradictory reports, and the risk may vary between different populations, understanding ROP risk factors is essential to develop predictive models, to gain insights into pathophysiology of retinal vascular diseases and diseases of prematurity, and to determine future directions in management of and research in ROP. [ABSTRACT FROM AUTHOR]

Purpose To identify patterns of interexpert discrepancy in plus disease diagnosis in retinopathy of prematurity (ROP). Design We developed 2 datasets of clinical images as part of the Imaging and Informatics in ROP study and determined a consensus reference standard diagnosis (RSD) for each image based on 3 independent image graders and the clinical examination results. We recruited 8 expert ROP clinicians to classify these images and compared the distribution of classifications between experts and the RSD. Participants Eight participating experts with more than 10 years of clinical ROP experience and more than 5 peer-reviewed ROP publications who analyzed images obtained during routine ROP screening in neonatal intensive care units. Methods Expert classification of images of plus disease in ROP. Main Outcome Measures Interexpert agreement (weighted κ statistic) and agreement and bias on ordinal classification between experts (analysis of variance [ANOVA]) and the RSD (percent agreement). Results There was variable interexpert agreement on diagnostic classifications between the 8 experts and the RSD (weighted κ, 0–0.75; mean, 0.30). The RSD agreement ranged from 80% to 94% for the dataset of 100 images and from 29% to 79% for the dataset of 34 images. However, when images were ranked in order of disease severity (by average expert classification), the pattern of expert classification revealed a consistent systematic bias for each expert consistent with unique cut points for the diagnosis of plus disease and preplus disease. The 2-way ANOVA model suggested a highly significant effect of both image and user on the average score (dataset A: P < 0.05 and adjusted R 2 = 0.82; and dataset B: P < 0.05 and adjusted R 2 = 0.6615). Conclusions There is wide variability in the classification of plus disease by ROP experts, which occurs because experts have different cut points for the amounts of vascular abnormality required for presence of plus and preplus disease. This has important implications for research, teaching, and patient care for ROP and suggests that a continuous ROP plus disease severity score may reflect more accurately the behavior of expert ROP clinicians and may better standardize classification in the future. [ABSTRACT FROM AUTHOR]

Purpose To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. Design We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Participants Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Methods Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Main Outcome Measures Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. Results There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06–0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74–0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95–0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Conclusions Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future. [ABSTRACT FROM AUTHOR]

Purpose To identify the most common areas for discrepancy in retinopathy of prematurity (ROP) classification between experts. Design Prospective cohort study. Participants A total of 281 infants were identified as part of a multicenter, prospective, ROP cohort study from 7 participating centers. Each site had participating ophthalmologists who provided the clinical classification after routine examination using binocular indirect ophthalmoscopy (BIO) and obtained wide-angle retinal images, which were independently classified by 2 study experts. Methods Wide-angle retinal images (RetCam; Clarity Medical Systems, Pleasanton, CA) were obtained from study subjects, and 2 experts evaluated each image using a secure web-based module. Image-based classifications for zone, stage, plus disease, and overall disease category (no ROP, mild ROP, type II or pre-plus, and type I) were compared between the 2 experts and with the clinical classification obtained by BIO. Main Outcome Measures Inter-expert image-based agreement and image-based versus ophthalmoscopic diagnostic agreement using absolute agreement and weighted kappa statistic. Results A total of 1553 study eye examinations from 281 infants were included in the study. Experts disagreed on the stage classification in 620 of 1553 comparisons (40%), plus disease classification (including pre-plus) in 287 of 1553 comparisons (18%), zone in 117 of 1553 comparisons (8%), and overall ROP category in 618 of 1553 comparisons (40%). However, agreement for presence versus absence of type 1 disease was >95%. There were no differences between image-based and clinical classification except for zone III disease. Conclusions The most common area of discrepancy in ROP classification is stage, although inter-expert agreement for clinically significant disease, such as presence versus absence of type 1 and type 2 disease, is high. There were no differences between image-based grading and clinical examination in the ability to detect clinically significant disease. This study provides additional evidence that image-based classification of ROP reliably detects clinically significant levels of ROP with high accuracy compared with the clinical examination. [ABSTRACT FROM AUTHOR]

Purpose To examine the influence of fluorescein angiography (FA) on the diagnosis and management of retinopathy of prematurity (ROP). Design Prospective cohort study. Participants Nine recognized ROP experts (3 pediatric ophthalmologists and 6 retina specialists) interpreted 32 sets (16 color fundus photographs and 16 color fundus photographs paired with the corresponding FA images) of wide-angle retinal images from infants with ROP. Methods All experts independently reviewed the 32 image sets on a secure website and provided a diagnosis and management plan for the case presented, first based on color fundus photographs alone, and then based on color fundus photographs and corresponding FA images. Main Outcome Measures Sensitivity and specificity of the ROP diagnosis (zone, stage, plus disease, and category, i.e., no ROP, mild ROP, type 2 ROP, and ROP requiring treatment) were calculated using a consensus reference standard diagnosis, determined from the diagnosis of the color fundus photographs by 3 experienced readers in combination with the clinical diagnosis based on ophthalmoscopic examination. The κ statistic was used to analyze the average intergrader agreement among experts for the diagnosis of zone, stage, plus disease, and category. Results Addition of FA to color fundus photography resulted in a significant improvement in sensitivity for diagnosis of stage 3 or worse disease (39.8% vs. 74.1%; P = 0.008), type 2 or worse ROP (69.4% vs. 86.8%; P = 0.013), and pre-plus or worse disease (50.5 vs. 62.6%; P = 0.031). There was a nonsignificant trend toward improved sensitivity for diagnosis of ROP requiring treatment (22.2% vs. 40.3%; P = 0.063). Using the κ statistic, addition of FA to color fundus photography significantly improved intergrader agreement for diagnosis of ROP requiring treatment. Addition of FA to color fundus photography did not affect intergrader agreement significantly for the diagnosis of stage, zone, or plus disease. Conclusions Compared with color fundus photography alone, FA may improve the sensitivity of diagnosis of ROP by experts, particularly for stage 3 disease. In addition, intergrader agreement for diagnosis of ROP requiring treatment may improve with FA interpretation. [ABSTRACT FROM AUTHOR]

The incidence of retinopathy of prematurity (ROP) continues to rise due to the improved survival of very low birth weight infants in developed countries. This epidemic is also fueled by increased survival of preterm babies with variable use of oxygen and a lack of ROP awareness and screening services in resource-limited regions. Improvements in technology and a basic understanding of the disease pathophysiology have changed the way we screen and manage ROP, educate providers and patients, and improve ROP awareness. Advancements in imaging techniques, expansion of telemedicine services, and the potential for artificial intelligence-assisted ROP screening programs have created opportunities to improve ROP care in areas with a shortage of ophthalmologists trained in ROP. To address the gap in provider knowledge regarding ROP, the Global Education Network for Retinopathy of Prematurity (GEN-ROP) created a web-based tele-education training module that can be used to educate all providers involved in ROP, including non-physician ROP screeners. Over the past 50 years, the treatment of severe ROP has evolved from limited treatment modalities to cryotherapy and laser photocoagulation. More recently, there has been growing evidence to support the use of anti-vascular endothelial growth factor (VEGF) agents for the treatment of severe ROP. However, VEGF is known to be important in organogenesis and microvascular maintenance, and given that intravitreal anti-VEGF treatment can result in systemic VEGF suppression over a period of at least 1-12 weeks, there are concerns regarding adverse effects and long-term ocular and systemic developmental consequences of anti-VEGF therapy. Future research in ophthalmology to address the growing burden of ROP should focus on cost-effective fundus imaging devices, implementation of artificial intelligence platforms, updated treatment algorithms with optimal use of anti-VEGF and careful investigation of its long-term effects, and surgical options in advanced ROP. Addressing these unmet needs will aid the global effort against the ROP epidemic and optimize our understanding and treatment of this blinding disease. [ABSTRACT FROM AUTHOR]

The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a "new normal", the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions. [ABSTRACT FROM AUTHOR]

Purpose: To measure accuracy and speed for detection of vascular progression in retinopathy of prematurity (ROP) from serial images. Two strategies are compared: static side-by-side presentation and dynamic flickering of superimposed image pairs. Design: Prospective comparative study. Methods: Fifteen de-identified, wide-angle retinal image pairs were taken from infants who eventually developed plus disease. Image pairs representing vascular disease progression were taken ≥1 week apart, and control images without progression were taken on the same day. Dynamic flickering pairs were created by digital image registration. Ten experts independently reviewed each image pair on a secure website using both strategies, and were asked to identify progression or state that images were identical. Accuracy and speed were measured, using examination date and ophthalmoscopic findings as a reference standard. Results: Using static images, experts were accurate in a mean (%) ± standard deviation (SD) of 11.4 of 15 (76%) ± 1.7 image pairs. Using dynamic flickering images, experts were accurate in a mean (%) ± SD of 11.3 of 15 (75%) ± 1.7 image pairs. There was no significant difference in accuracy between these strategies (P = .420). Diagnostic speed was faster using dynamic flickering (24.7 ± 8.3 seconds) vs static side-by-side images (40.3 ± 18.3 seconds) (P = .002). Experts reported higher confidence when interpreting dynamic flickering images (P = .001). Conclusions: Retinal imaging provides objective documentation of vascular appearance, with potentially improved ability to recognize ROP progression compared to standard ophthalmoscopy. Speed of identifying vascular progression was faster by review of dynamic flickering image pairs than by static side-by-side images, although there was no difference in accuracy. [Copyright &y& Elsevier]

Purpose: To examine the relationship between rate of vascular change and plus disease diagnosis. Design: Retrospective observational case-control study. Methods: Wide-angle images were taken bilaterally from 37 infants at 31 to 33 weeks and 35 to 37 weeks postmenstrual age (PMA). The semi-automated Retinal Image multiScale Analysis system was used to measure parameters for all arteries and veins: integrated curvature, diameter, and tortuosity index. A reference standard diagnosis (plus vs not plus) was defined for each eye by consensus of 5 experts at 35 to 37 weeks PMA. Weekly rate of change in parameters was compared in eyes with plus vs not plus disease. Receiver operating characteristic area under the curve (AUC) was calculated for plus disease detection based on 1) weekly rates of parameter change between 31 to 33 weeks and 35 to 37 weeks PMA and 2) parameter values at 35 to 37 weeks only. Results: Weekly rates of change in all venous parameters were significantly different in eyes with plus vs not plus disease, particularly for tortuosity index (P < .0004) and diameter (P = .018). Using weekly rate of change, AUC for plus disease detection was highest for venous tortuosity index (0.819) and venous diameter (0.712). Using the 35 to 37-week PMA image only, AUC was highest for venous integrated curvature (0.952) and diameter (0.789). Conclusion: Rate of change in venous, but not arterial, parameters is correlated with plus disease development in this data set. This did not appear to contribute information beyond analysis of an image at 35 to 37 weeks PMA only. [ABSTRACT FROM AUTHOR]

Purpose: To compare the speed of retinopathy of prematurity (ROP) diagnosis using standard indirect ophthalmoscopy with that of telemedicine. Design: Prospective, comparative study. Methods: Three study examiners (2 pediatric retinal specialists [R.V.P.C., T.C.L.] and 1 pediatric ophthalmologist [M.F.C.]) conducted ROP diagnosis via standard indirect ophthalmoscopy and telemedicine. Each examiner performed: 1) standard ophthalmoscopy on 72 to 150 consecutive infants at his respective institution and 2) telemedical diagnosis on 125 consecutive deidentified retinal image sets from infants from an at-risk population. Time for ophthalmoscopic diagnosis was measured in 2 ways: 1) time spent by the examiner at the infant''s bedside and 2) mean total time commitment per infant. Time for telemedicine diagnosis was recorded by computer time stamps in the web-based system. For each examiner, nonparametric statistical analysis (Mann–Whitney U test) was used to compare the distribution of times for examination by ophthalmoscopy vs telemedicine. Results: Mean (± standard deviation [SD]) times for ophthalmoscopic diagnosis ranged from 4.17 (± 1.34) minutes to 6.63 (± 2.28) minutes per infant. Mean (± SD) times for telemedicine diagnosis ranged from 1.02 (± 0.27) minutes to 1.75 (± 0.80) minutes per infant. Telemedicine was significantly faster than ophthalmoscopy (P < .0001). The total time commitment by ophthalmologists performing bedside ophthalmoscopy for ROP diagnosis, including travel and communication with families and hospital staff, was 10.08 (± 2.53) minutes to 14.42 (± 2.64) minutes per infant. Conclusions: The ophthalmologist time requirement for telemedical ROP diagnosis is significantly less than that for ophthalmoscopic diagnosis. Additional time requirements associated with bedside ROP diagnosis increased this disparity. Telemedicine has potential to alleviate the time commitment for ophthalmologists who manage ROP. [Copyright &y& Elsevier]