Impact and Trends in Global Ophthalmology

Eye and adnexa hospitalization in Australia: An ecological study

To investigate the trends of hospital admissions concerning diseases of the eye and adnexa in Australia in the past 2 decades. This is a descriptive ecological study on the population level that examined hospitalization data for the duration between 1998 and 2021 in Australia. Hospitalization data were extracted from the National Hospital Morbidity Database. The chi-squared test was utilized to assess the difference in admission rates between the years 1998 and 2021. Hospital admission rate for diseases of the eye and adnexa increased by 1.20-fold (from 852.32 [95% confidence interval [CI] 848.16-856.47] in 1998 to 1873.72 [95% CI 1868.48-1878.96] in 2021 per 100,000 persons, P < .01). The most common cause of hospitalization for diseases of the eye and adnexa was disorders of the lens (65.7%), followed by disorders of the choroid and retina (15.6%), followed by disorders of the eyelid, lacrimal system, and orbit (7.7%). Hospital admission rate among males increased by 1.25-fold (from 737.67 [95% CI 732.18-743.16] in 1998 to 1657.19 [95% CI 1650.19-1664.20] in 2021 per 100,000 persons). Hospital admission rate among females increased less sharply by 1.03-fold (from 965.37 [95% CI 959.14-971.59] in 1998 to 1964.35 [95% CI 1956.80-1971.90] in 2021 per 100,000 persons). There are clear gender and age roles in the epidemiology of hospital admissions related to eye and adnexa disorders. Lens disorders were the most common cause of hospital admission. The admission rate increase during the past decades could be due to increases in life expectancy, lifestyle changes, and improvements in screening protocols.

Predicting myopic changes in children wearing glasses using the Plusoptix photoscreener

INTRODUCTION

With high increase in myopia prevalence, we aimed to assess whether Plusoptix_A09 can be used in myopic children over spectacles to predict visual acuity (VA) and myopic refraction changes.

METHODS

Myopic children underwent a complete ophthalmological examination. Plusoptix_A09 was performed over spectacles. VA changes, refraction changes and time since previous glasses prescription, were determined. Age, current or past history of amblyopia, presence of strabismus and self-perception of VA changes were registered.

RESULTS

In total, 199 patients were included. Spherical power (SP) and spherical equivalent (SE) measured by Plusoptix_A09 over spectacles predicted both VA changes (p < 0.001) and refraction changes (p < 0.001). Values of SP < - 0.06D or SE < - 0.22D indicated a VA decrease (AUC > 0.9, p < 0.01) for sensitivity and specificity of 85.1%, 82.1% and 82.6%, 83.3%, respectively. Age and ophthalmological comorbidities did not influence Plusoptix_A09 measurements (p > 0.05). Plusoptix_A09 over spectacles was a stronger predictor of VA changes when compared to children's self-perception, either in 4-9-year-old patients (p < 0.001 versus p = 0.628) and in 10-18-year-old children (OR <  = 0.066 versus OR = 0.190). A decrease in SP and SE of - 0.10D in Plusoptix_A09 predicted a myopia progression of - 0.04D and - 0.05D, respectively.

CONCLUSION/RELEVANCE

This study unveiled new features for the Plusoptix, a worldwide available photoscreener used in amblyopia screening. When Plusoptix is performed in children with their glasses on, it can rapidly predict myopia progression. For each decrease of - 0.10D in Plusoptix, a myopia progression of -0.05D is expected. Moreover, Plusoptix is more reliable than children's self-perception of visual acuity changes, making it a useful tool either in primary care or ophthalmology practice.

Applications of deep learning for detecting ophthalmic diseases with ultrawide-field fundus images

AIM

To summarize the application of deep learning in detecting ophthalmic disease with ultrawide-field fundus images and analyze the advantages, limitations, and possible solutions common to all tasks.

METHODS

We searched three academic databases, including PubMed, Web of Science, and Ovid, with the date of August 2022. We matched and screened according to the target keywords and publication year and retrieved a total of 4358 research papers according to the keywords, of which 23 studies were retrieved on applying deep learning in diagnosing ophthalmic disease with ultrawide-field images.

RESULTS

Deep learning in ultrawide-field images can detect various ophthalmic diseases and achieve great performance, including diabetic retinopathy, glaucoma, age-related macular degeneration, retinal vein occlusions, retinal detachment, and other peripheral retinal diseases. Compared to fundus images, the ultrawide-field fundus scanning laser ophthalmoscopy enables the capture of the ocular fundus up to 200° in a single exposure, which can observe more areas of the retina.

CONCLUSION

The combination of ultrawide-field fundus images and artificial intelligence will achieve great performance in diagnosing multiple ophthalmic diseases in the future.

Tracing the barriers to decarbonising ophthalmology: A review

As climate change demands increasingly urgent mitigation of greenhouse gas emissions, the health sector needs to do its part to decarbonise. Ophthalmologists share concerns about climate change and seek opportunities to reduce their environmental impact. When measuring the footprint of ophthalmology, major contributions are from patient travel to clinics, and from the large amounts of single-use disposable materials that are consumed during surgeries and sterile procedures. Ophthalmic services in India have already demonstrated systems that consume far fewer of these products through efficient throughput of patients and the safe reuse of many items, while maintaining equivalent safety and quality outcomes. Choosing these low-cost low-emission options would seem obvious, but many ophthalmologists experience barriers that prevent them operating as Indian surgeons do. Understanding these barriers to change is a crucial step in the decarbonisation of ophthalmology and the health sector more broadly.

The TeleTriageTeam, Offering Continuity of Personalized Care through Telemedicine: Development and Evaluation

BACKGROUND

If anything, the COVID-19 pandemic learned us how to rethink care delivery. It catalyzed creative solutions to amplify the potential of personnel and facilities. This paper presents and evaluates an acutely introduced triaging solution, that evolved into a tool to tackle the ever-growing waiting lists at an academic ophthalmology department: the TeleTriageTeam. A team of undergraduate optometry students, tutor-optometrists, and ophthalmologists collaborate to maintain continuity of eye care. In this ongoing project, we combine innovative inter-professional task allocation, teaching, and remote care delivery.

OBJECTIVE

This paper describes this novel approach, and reports on its clinical effectiveness, its impact on waiting lists, and discusses its transformation to a sustainable method for delivering remote eye care.

METHODS

Real-world clinical data of all patients assessed by the TeleTriageTeam between April 16, 2020, and December 31, 2021 are covered in this paper. Business data about waiting lists and patient portal access were collected from our hospital's capacity management team and IT department. Interim analyses were performed at different time points during the project and this paper will present a synthesis of these analyses.

RESULTS

A total of 3,658 cases were assessed by the TeleTriageTeam. For approximately half (48%) of the assessed cases, an alternative to a conventional face-to-face consultation was found. The waiting lists that had been built up during the first months of the pandemic diminished and have been stable since the end of 2020, even in periods of imposed lockdown restrictions and reduced capacity. Patient portal access decreased with age and patients who were invited to perform a remote, web-based eye test at home were on average younger than patients who were not invited.

CONCLUSIONS

Our acutely introduced approach to remotely review cases and prioritize urgency has been successful in maintaining continuity of care and education throughout the pandemic and evolved into a telemedicine service that is of great interest for future purposes, especially in the routine follow-up of chronic patients. TeleTriage appears as a potentially preferred practice for other clinics and medical specialties. The paradox is that judicious clinical decision making based on remotely collected data actually is possible, lest we as care-givers are willing to change our routines and cognitions regarding face-to-face care delivery.

CLINICALTRIAL

Design and Evaluating Psychometric Properties of the Eye Care Behaviors Assessment Instrument

Background

Eye health is essential for quality-of-life. The present study aimed to design an eye care behaviors assessment instrument for the student community and evaluate its psychometric properties.

Methods

The present mixed-method cross-sectional study was conducted in two sections using Creswell and Plano Clark methods for instrument development. The study was conducted in Isfahan, Iran, in 2021. The first section (textual analysis and qualitative research) explained and developed the instrument's fundamental items. This section included in-depth, semistructured interviews with 21 students and eight experts. The second section measured the psychometric properties of the instrument. Twenty students assessed the instrument's qualitative and quantitative face validity in this section. The instrument's content validity ratio (CVR) and content validity index (CVI) were evaluated. In addition, exploratory factor analysis (performed by 251 students) was used to establish construct validity. Internal and test-retest reliability was determined using Cronbach's alpha and intraclass correlation coefficients (ICC), respectively.

Results

During face and content validity assessment, a 37-item questionnaire was finalized. Exploratory factor analysis led to the identification of three factors, including "examinations and glasses-related behaviors," "symptom-related behaviors," and "screen-related behaviors." The three extracted factors accounted for 37.9% of the variance. Cronbach's alpha was equal to 0.874 when evaluating internal consistency, and the ICC value for the total score of the questionnaire was 0.885 (0.810-0.941), indicating excellent test-retest reliability.

Conclusions

These results demonstrate the questionnaire's validity and reliability. This instrument assesses the prevalence of university students' most significant eye health risk behaviors. Consequently, it helps prevent eye problems.

Race and Gender in Ophthalmology: A National Analysis of Medical Students with Intention to Pursue the Field

Purpose  The field of ophthalmology must become more reflective of the increasingly diverse U.S. population. This study characterizes students intending to pursue ophthalmology and practice in an underserved area versus other surgical and nonsurgical fields. Subjects  Deidentified responses from 92,080 U.S. MD students who matriculated in the academic years beginning from 2007 to 2011 were obtained from the Association of American Medical Colleges (AAMC) Graduation Questionnaires. Methods  Study participants were those who fully completed the AAMC Graduation Questionnaire. Chi-squared and multivariate logistical regressions were used for analyses. Results  Ophthalmology intending graduates (OIG; n  = 1,177) compared with other surgical intending graduates ( n  = 7,955) were more likely to be female (adjusted odds ratio [aOR]: 1.46; 95% confidence interval [CI]: 1.28-1.66), Asian (1.71 [1.46-2.01]), and have conducted a research project with a faculty member (1.58 [1.26-1.98]). OIG compared with nonsurgery intending graduates ( n  = 35,865) were more likely to have completed a research project with a faculty member (4.78 [3.86-5.92]), to be Asian (1.4 [1.21-1.62]), and have received scholarships (1.18 [1.04-1.34]). OIG were less likely to be female (0.64 [0.57-0.73]) and Black/African American (0.5 [0.33-0.74]). Among OIG, Black/African American students and multiracial students were more likely than non-Hispanic (NH) White students to report intention to practice in underserved areas (IPUA; 14.29 [1.82-111.88] and 2.5 [1.06-5.92]), respectively. OIG with global health experience were more likely to report IPUA (1.64 [1.2-2.25]). Conclusion  Females and underrepresented in medicine (URM), respectively, were more likely to be nonsurgery intending graduates than OIG, which, if not addressed, may lead to a persistent underrepresentation of these groups in the field. In addition, URM students, including African American students, were more likely to report IPUA, which further emphasizes the importance of more URM students entering the field to address these growing gaps in medical care. Finally, we recommend increased mentorship to help address these disparities.

A Virtual Reading Center Model Using Crowdsourcing to Grade Photographs for Trachoma: Validation Study (Preprint)

BACKGROUND

As trachoma is eliminated, skilled field graders become less adept at correctly identifying active disease (trachomatous inflammation-follicular [TF]). Deciding if trachoma has been eliminated from a district or if treatment strategies need to be continued or reinstated is of critical public health importance. Telemedicine solutions require both connectivity, which can be poor in the resource-limited regions of the world in which trachoma occurs, and accurate grading of the images.

OBJECTIVE

Our purpose was to develop and validate a cloud-based "virtual reading center" (VRC) model using crowdsourcing for image interpretation.

METHODS

The Amazon Mechanical Turk (AMT) platform was used to recruit lay graders to interpret 2299 gradable images from a prior field trial of a smartphone-based camera system. Each image received 7 grades for US $0.05 per grade in this VRC. The resultant data set was divided into training and test sets to internally validate the VRC. In the training set, crowdsourcing scores were summed, and the optimal raw score cutoff was chosen to optimize kappa agreement and the resulting prevalence of TF. The best method was then applied to the test set, and the sensitivity, specificity, kappa, and TF prevalence were calculated.

RESULTS

In this trial, over 16,000 grades were rendered in just over 60 minutes for US $1098 including AMT fees. After choosing an AMT raw score cut point to optimize kappa near the World Health Organization (WHO)-endorsed level of 0.7 (with a simulated 40% prevalence TF), crowdsourcing was 95% sensitive and 87% specific for TF in the training set with a kappa of 0.797. All 196 crowdsourced-positive images received a skilled overread to mimic a tiered reading center and specificity improved to 99%, while sensitivity remained above 78%. Kappa for the entire sample improved from 0.162 to 0.685 with overreads, and the skilled grader burden was reduced by over 80%. This tiered VRC model was then applied to the test set and produced a sensitivity of 99% and a specificity of 76% with a kappa of 0.775 in the entire set. The prevalence estimated by the VRC was 2.70% (95% CI 1.84%-3.80%) compared to the ground truth prevalence of 2.87% (95% CI 1.98%-4.01%).

CONCLUSIONS

A VRC model using crowdsourcing as a first pass with skilled grading of positive images was able to identify TF rapidly and accurately in a low prevalence setting. The findings from this study support further validation of a VRC and crowdsourcing for image grading and estimation of trachoma prevalence from field-acquired images, although further prospective field testing is required to determine if diagnostic characteristics are acceptable in real-world surveys with a low prevalence of the disease.

Current Status of Mesenchymal Stem/Stromal Cells for Treatment of Neurological Diseases

Neurological disorders include a wide spectrum of clinical conditions affecting the central and peripheral nervous systems. For these conditions, which affect hundreds of millions of people worldwide, generally limited or no treatments are available, and cell-based therapies have been intensively investigated in preclinical and clinical studies. Among the available cell types, mesenchymal stem/stromal cells (MSCs) have been widely studied but as yet no cell-based treatment exists for neurological disease. We review current knowledge of the therapeutic potential of MSC-based therapies for neurological diseases, as well as possible mechanisms of action that may be explored to hasten the development of new and effective treatments. We also discuss the challenges for culture conditions, quality control, and the development of potency tests, aiming to generate more efficient cell therapy products for neurological disorders.

[Use of artificial intelligence in screening for diabetic retinopathy at a tertiary diabetes center]

BACKGROUND

In 2018, IDx-DR was approved as a method to determine the degree of diabetic retinopathy (DR) using artificial intelligence (AI) by the FDA.

METHODS

We integrated IDx-DR into the consultation at a diabetology focus clinic and report the agreement between IDx-DR and fundoscopy as well as IDx-DR and ophthalmological image assessment and the influence of different camera systems.

RESULTS

Adequate image quality in miosis was achieved more frequently with the Topcon camera (n = 456; NW400, Topcon Medical Systems, Oakland, NJ, USA) compared with the Zeiss camera (n = 47; Zeiss VISUCAM 500, Carl Zeiss Meditec AG, Jena, Germany). Overall, IDx-DR analysis in miosis was possible in approximately 60% of the patients. All patients in whom IDx-DR analysis in miosis was not possible could be assessed by fundoscopy with dilated pupils. Within the group of images that could be evaluated, there was agreement between IDx-DR and ophthalmic fundoscopy in approximately 55%, overestimation of severity by IDx-DR in approximately 40% and underestimation in approximately 4%. The sensitivity (specificity) for detecting severe retinopathy requiring treatment was 95.7% (89.1%) for cases with fundus images that could be evaluated and 65.2% (66.7%) when all cases were considered (including those without images in miosis which could be evaluated). The kappa coefficient of 0.334 (p < 0.001) shows sufficient agreement between IDx-DR and physician's image analysis based on the fundus photograph, considering all patients with IDx-DR analysis that could be evaluated. The comparison between IDx-DR and the physician's funduscopy under the same conditions shows a low agreement with a kappa value of 0.168 (p < 0.001).

CONCLUSION

The present study shows the possibilities and limitations of AI-assisted DR screening. A major limitation is that sufficient images cannot be obtained in miosis in approximately 40% of patients. When sufficient images were available the IDx-DR and ophthalmological diagnosis matched in more than 50% of cases. Underestimation of severity by IDx-DR occurred only rarely. For integration into an ophthalmologist's practice, this system seems suitable. Without access to an ophthalmologist the high rate of insufficient images in miosis represents an important limitation.

Considerations for Artificial Intelligence Real-World Implementation in Ophthalmology: Providers' and Patients' Perspectives

ABSTRACT

Artificial Intelligence (AI), in particular deep learning, has made waves in the health care industry, with several prominent examples shown in ophthalmology. Despite the burgeoning reports on the development of new AI algorithms for detection and management of various eye diseases, few have reached the stage of regulatory approval for real-world implementation. To better enable real-world translation of AI systems, it is important to understand the demands, needs, and concerns of both health care professionals and patients, as providers and recipients of clinical care are impacted by these solutions. This review outlines the advantages and concerns of incorporating AI in ophthalmology care delivery, from both the providers' and patients' perspectives, and the key enablers for seamless transition to real-world implementation.

Characterising transnational ophthalmic surgical partnerships by engagement and training

BACKGROUND

Transnational ophthalmic partnerships exist between high-income countries (HICs) and low- and middle-income countries (LMICs) in varying capacities. We analyzed partnership stakeholders to better understand and address disparities in ophthalmic surgical care.

METHODS

An international Web search was conducted to identify surgeons, foundations or organisations participating in ophthalmic delivery and/or capacity building from 2010 to 2019. Partnerships were defined through clinical activities, education and training and/or research support. Descriptive data on current ophthalmic partnerships were collected from published reports, literature reviews and information on stakeholder webpages. Partnerships were classified by the extent of engagement and training: grade I 'engagement' represented documented partnerships of at least 1 year and grade I 'training' limited or poorly defined skills transfer programmes, while grade III 'engagement' represented partnerships with well-documented fiscal investment and/or research productivity and grade III 'training' established training programmes. Data were analysed using descriptive statistics and geospatially depicted on Tableau (Mountain View, CA) and ArcMap software (Redlands, CA).

RESULTS

In total, 209 unique HIC-LMIC partnerships encompassing 92 unique countries were described. The most common HIC partners were from North America (123; 59%), followed by Europe (75; 36%). The most common LMIC partners were from Africa (102; 49%), followed by Asia-Pacific (54; 26%) and Latin America (44; 21%). Additionally, partnerships most frequently provided services in cataract (48%), glaucoma (25%) and diabetic retinopathy (25%). The most common 'engagement' classifications were grade I (36%) or II (40%); the most common 'training' classifications were grade I (61%) or II (23%).

CONCLUSION

Transnational ophthalmic partnerships exist with varying degrees of both engagement and training. Partnerships are stronger in research collaboration and direct services, and weaker in LMIC-directed training programmes.