Eye Injury Epidemiology in Australia: A 25-Year Systematic Review and Public Health Perspective.

Background: Eye injuries are a significant cause of monocular blindness, contributing to individual morbidity and substantial healthcare costs. Despite this burden, eye injury prevention remains underrepresented in Australian public health initiatives. This systematic review (PROSPERO ID: CRD42024551054) aims to provide the first comprehensive nationwide synthesis of eye injury epidemiology in Australia.

Effectiveness of artificial intelligence-based diabetic retinopathy screening in primary care and endocrinology settings in Australia: a pragmatic trial.

Purpose: To investigate the diagnostic accuracy, feasibility and end-user experiences of an artificial intelligence (AI)-based, automated diabetic retinopathy (DR) screening model in real-world, Australian primary care and endocrinology clinics.

Methods: In a pragmatic trial conducted across five sites including general practice and endocrinology clinics, from August 2021 to June 2023, patients aged ≥50 years, and those aged ≥18 years with diabetes were screened using an AI-integrated, non-mydriatic fundus camera. The AI instantly analysed the retinal images for referable DR.

Using geographic information systems to map eye care service distribution in rural and remote Western Australia.

Background: Many rural residents face barriers to eye care access. Government workforce data show a maldistribution of eye care providers in Western Australia however, no detailed information is available on regional coverage within the state. This study aimed to identify and map all eye care services in rural and remote Western Australia and to calculate the regional workforce rates.

Implementation of A New, Mobile Diabetic Retinopathy Screening Model Incorporating Artificial Intelligence in Remote Western Australia.

Objective: Diabetic retinopathy (DR) screening rates are poor in remote Western Australia where communities rely on outdated primary care-based retinal cameras. Deep learning systems (DLS) may improve access to screening, however, require validation in real-world settings. This study describes and evaluates the implementation of a new, mobile DR screening model that incorporates artificial intelligence (AI) into routine care.

Recommendations for implementing rheumatic heart disease echocardiographic detection in remote Australia: A narrative review and lesson-drawing from diabetic retinopathy screening.

Background And Objectives: Australia has some communities with the highest rates of rheumatic heart disease (RHD) in the world. Echocardiographic detection of RHD through active case finding has been proposed for early detection. Lessons can be learnt from the implementation of a similar program - diabetic retinopathy screening.

Rural Eye Care Access, Workforce Challenges and Opportunities: Perspectives of the Eye Health Workforce in Western Australia.

Objective: Rural residents face numerous barriers to accessing eye care services that contribute to disparities in eye health outcomes. This study aimed to explore the perspectives of the rural workforce on opportunities to improve patient access to eye care services, as well as understand the ways the workforce can be supported.

Setting: Regional, rural and remote Western Australia.

Prevalence of visually significant cataract and cataract surgical coverage in Indigenous and non-Indigenous Australians: a systematic review and meta-analysis.

Aims: Compare the prevalence of age-related cataract and the cataract surgical coverage rate between Indigenous and non-Indigenous Australians and explore differences in these estimates across location and time.

Methods: The Joanna Briggs Institute guidance for systematic reviews of prevalence studies was followed. A systematic search of Medline, Embase, Web of Science and grey literature from database inception to June 2022 was performed.

Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.

Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS), that quantifies the degree of pigmentation from a colour fundus photograph of the eye. RPS was validated using two large epidemiological studies with demographic and genetic data (UK Biobank and EPIC-Norfolk Study) and reproduced in a Tanzanian, an Australian, and a Chinese dataset.

Real-world evaluation of RetCAD deep-learning system for the detection of referable diabetic retinopathy and age-related macular degeneration.

Clinical Relevance: The challenges of establishing retinal screening programs in rural settings may be mitigated by the emergence of deep-learning systems for early disease detection.

Background: Deep-learning systems have demonstrated promising results in retinal disease detection and may be particularly useful in rural settings where accessibility remains a barrier to equitable service provision. This study aims to evaluate the real-world performance of Thirona RetCAD for the detection of referable diabetic retinopathy and age-related macular degeneration in a rural Australian population.

Endophthalmitis following intravitreal injections administered by junior medical officers in rural Western Australia.

Background: Patients in rural Australia have limited access to intravitreal treatments due to a maldistribution of the ophthalmology workforce. To improve access, a novel outreach service model was implemented whereby junior medical staff administered intravitreal injections under a supervising ophthalmology consultant. This model involves outreach visits in hospitals, mobile clinics and a remote hub with intravitreal injections administered by junior doctors overseen by an ophthalmologist.

Foundation models in ophthalmology.

Foundation models represent a paradigm shift in artificial intelligence (AI), evolving from narrow models designed for specific tasks to versatile, generalisable models adaptable to a myriad of diverse applications. Ophthalmology as a specialty has the potential to act as an exemplar for other medical specialties, offering a blueprint for integrating foundation models broadly into clinical practice. This review hopes to serve as a roadmap for eyecare professionals seeking to better understand foundation models, while equipping readers with the tools to explore the use of foundation models in their own research and practice.

Ocular biomarkers: useful incidental findings by deep learning algorithms in fundus photographs.

Background/objectives: Artificial intelligence can assist with ocular image analysis for screening and diagnosis, but it is not yet capable of autonomous full-spectrum screening. Hypothetically, false-positive results may have unrealized screening potential arising from signals persisting despite training and/or ambiguous signals such as from biomarker overlap or high comorbidity. The study aimed to explore the potential to detect clinically useful incidental ocular biomarkers by screening fundus photographs of hypertensive adults using diabetic deep learning algorithms.

A Systematic Review of Ophthalmology Education in Medical Schools: The Global Decline.

Topic: This systematic review examined geographical and temporal trends in medical school ophthalmology education in relationship to course and student outcomes.

Clinical Relevance: Evidence suggesting a decline in ophthalmology teaching in medical schools is increasing, raising concern for the adequacy of eye knowledge across the rest of the medical profession.

Methods: Systematic review of Embase and SCOPUS, with inclusion of studies containing data on medical school ophthalmic course length; 1 or more outcome measures on student ophthalmology knowledge, skills, self-evaluation of knowledge or skills, or student course appraisal; or both.

Comparison of three modalities of teleophthalmology delivery in regional Western Australia during the COVID-19 lock-down.

Clinical Relevance: In conjunction with local optometry services, telehealth may be used in to provide specialist care for patients living in rural areas underserved by ophthalmology.

Background: To combat travel restrictions for specialist outreach to regional areas during the 2020 COVID-19 lockdown, Lions Outback Vision introduced three different modalities of teleophthalmology consultations; home-based telephone, hospital-based video, and optometry-based video. This study evaluated the utility of these in providing specialist care to rural patients during the pandemic.

A systematic review of diabetic retinopathy screening intervals.

The current evidence on whether annual diabetic retinopathy (DR) screening intervals can be extended was reviewed. A systematic review protocol was followed (PROSPERO ID: CRD42022359590). Original longitudinal articles that specifically assessed DR screening intervals were in English and collected data after 2000 were included.

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.

Background/aims: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic minority groups, therefore external validation within these populations is critical for health equity. This study evaluates the performance of a DLS for DR detection among Indigenous Australians, an understudied ethnic group who suffer disproportionately from DR-related blindness.

Methods: We performed a retrospective external validation study comparing the performance of a DLS against a retinal specialist for the detection of more-than-mild DR (mtmDR), vision-threatening DR (vtDR) and all-cause referable DR.

Retinopathy prevalence, incidence and trajectories in type 2 diabetes: The Fremantle diabetes study phase II.

Aims: To determine diabetic retinopathy (DR) prevalence, incidence, and whether distinct trajectories are associated with DR-complicating Type 2 diabetes.

Methods: Retinal photographs from Fremantle Diabetes Study Phase II (FDS2) participants with Type 2 diabetes recruited in 2008-2011 and who attended biennial assessments for up to 6 years were graded as no DR, mild non-proliferative DR (NPDR), moderate NPDR or severe NPDR/proliferative DR. Baseline DR prevalence, and the cumulative incidence of moderate NPDR or worse in those without DR at baseline, were calculated.

Prevalence of Diabetic Retinopathy in Indigenous and Non-Indigenous Australians: A Systematic Review and Meta-analysis.

Topic: This systematic review and meta-analysis summarizes evidence relating to the prevalence of diabetic retinopathy (DR) among Indigenous and non-Indigenous Australians.

Clinical Relevance: Indigenous Australians suffer disproportionately from diabetes-related complications. Exploring ethnic variation in disease is important for equitable distribution of resources and may lead to identification of ethnic-specific modifiable risk factors.

Benefits of Integrating Telemedicine and Artificial Intelligence Into Outreach Eye Care: Stepwise Approach and Future Directions.

Telemedicine has traditionally been applied within remote settings to overcome geographical barriers to healthcare access, providing an alternate means of connecting patients to specialist services. The coronavirus 2019 pandemic has rapidly expanded the use of telemedicine into metropolitan areas and enhanced global telemedicine capabilities. Through our experience of delivering real-time telemedicine over the past decade within a large outreach eye service, we have identified key themes for successful implementation which may be relevant to services facing common challenges.

Screening for Glaucomatous Visual Field Defects in Rural Australia with an iPad.

Aim And Objective: Developing improved methods for early detection of visual field defects is pivotal to reducing glaucoma-related vision loss. The Melbourne Rapid Fields screening module (MRF-S) is an iPad-based test, which allows suprathreshold screening with zone-based analysis to rapidly assess the risk of manifest glaucoma. The versatility of MRF-S has potential utility in rural areas and during infectious pandemics.

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.

Assessment of biomarkers associated with rapid renal decline in the detection of retinopathy and its progression in type 2 diabetes: The Fremantle Diabetes Study Phase II.

Aims: To determine whether biomarkers for diabetic kidney disease (DKD) can be used to determine the prevalence, progression and/or incidence of diabetic retinopathy (DR) complicating type 2 diabetes.

Methods: Proteomic biomarkers were measured in baseline fasting plasma from 958 Fremantle Diabetes Study Phase II participants whose baseline and, in those returning for follow-up (n = 764), Year 4 fundus photographs were graded for DR presence/severity. The performance of PromarkerD (three biomarkers and readily available clinical variables which identify prevalent DKD and predict incident DKD and estimated glomerular filtration rate decline ≥30% over four years) for detecting DR prevalence, progression and incidence was assessed using the area under the receiver operating curve (AUC).

Carotid Disease and Retinal Optical Coherence Tomography Angiography Parameters in Type 2 Diabetes: The Fremantle Diabetes Study Phase II.

Objective: To use optical coherence tomography angiography (OCTA) to determine whether retinal microvascular parameters are associated with carotid arterial disease in people with type 2 diabetes.

Research Design And Methods: Participants (community-based) underwent detailed assessments including carotid ultrasonography and OCTA. Ultrasound images were assessed for mean intima-media thickness (IMT) and the presence of stenosis.

Differences in retinopathy prevalence and progression between Anglo-Celt and Aboriginal Australians: the Fremantle Diabetes Study Phase II.

Background: Indigenous populations have higher rates of diabetes and diabetic complications, yet there is a paucity of contemporary data on diabetic retinopathy (DR) prevalence and incidence in urban dwelling Aboriginal Australians.

Aims: The aim of the study was to compare the prevalence of DR and incidence of new or worsening DR between Aboriginal Australians and Anglo-Celts with Type 2 diabetes.

Methods: Participants from the community-based Fremantle Diabetes Study Phase II (817 Anglo-Celts, 94 Aboriginal people) recruited between 2008 and 2011 underwent fundus photography at baseline and biennial reviews.