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. The systematic review was registered prospectively on the International Prospective Register of Systematic Reviews (identifier, CRD42022323865). Results were aggregated with outcome subgroup analysis and description in relationship to geographical and temporal trends. Descriptive statistics, including nonparametric correlations, were used to analyze data and trends. RESULTS: Systematic review yielded 4596 publication titles, of which 52 were included in the analysis, with data from 19 countries. Average course length ranged from 12.5 to 208.7 hours, with significant continental disparity among mean course lengths. Africa reported the longest average course length at 103.3 hours, and North America reported the shortest at 36.4 hours. On average, course lengths have been declining over the last 2 decades, from an average overall course length of 92.9 hours in the 2000s to 52.9 hours in the 2020s. Mean student self-evaluation of skills was 51.3%, and mean student self-evaluation of knowledge was 55.4%. Objective mean assessment mark of skills was 57.5% and that of knowledge was 71.7%, compared with an average pass mark of 66.7%. On average, 26.4% of students felt confident in their ophthalmology knowledge and 34.5% felt confident in their skills. DISCUSSION: Most evidence describes declining length of courses devoted to ophthalmology in the last 20 years, significant student dissatisfaction with courses and content, and suboptimal knowledge and confidence. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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. Existing DR prevalence studies comparing Indigenous and non-Indigenous Australians have shown conflicting results. METHODS: This study was conducted following Joanna Briggs Institute guidance on systematic reviews of prevalence studies (PROSPERO ID: CRD42022259048). We performed searches of Medline (Ovid), EMBASE, and Web of Science until October 2021, using a strategy designed by an information specialist. We included studies reporting DR prevalence among diabetic patients in Indigenous and non-Indigenous Australian populations. Two independent reviewers performed quality assessments using a 9-item appraisal tool. Meta-analysis and meta-regression were performed using double arcsine transformation and a random-effects model comparing Indigenous and non-Indigenous subgroups. RESULTS: Fifteen studies with 8219 participants met criteria for inclusion. The Indigenous subgroup scored lower on the appraisal tool than the non-Indigenous subgroup (mean score 50% vs. 72%, P = 0.04). In the unadjusted meta-analysis, DR prevalence in the Indigenous subgroup (30.2%; 95% confidence interval [CI], 24.9-35.7) did not differ significantly (P = 0.17) from the non-Indigenous subgroup (23.7%; 95% CI, 16.8-31.4). After adjusting for age and quality, DR prevalence was higher in the Indigenous subgroup (P < 0.01), with prevalence ratio point estimates ranging from 1.72 to 2.58, depending on the meta-regression model. For the secondary outcomes, prevalence estimates were higher in the Indigenous subgroup for diabetic macular edema (DME) (8.7% vs. 2.7%, P = 0.02) and vision-threatening DR (VTDR) (8.6% vs. 3.0%, P = 0.03) but not for proliferative DR (2.5% vs. 0.8%, P = 0.07). CONCLUSIONS: Indigenous studies scored lower for methodological quality, raising the possibility that systematic differences in research practices may be leading to underestimation of disease burden. After adjusting for age and quality, we found a higher DR prevalence in the Indigenous subgroup. This contrasts with a previous review that reported the opposite finding of lower DR prevalence using unadjusted pooled estimates. Future epidemiological work exploring DR burden in Indigenous communities should aim to address methodological weaknesses identified by this review.

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. Group-based DR trajectory modelling was performed. Logistic regression determined independent associates of incident moderate NPDR or worse and trajectory group membership. RESULTS: Of 1521 participants (mean age 65.6 years, 52.1% males, median diabetes duration 9.0 years; 98% of all FDS2 participants with Type 2 diabetes) with gradable baseline photographs, 563 (37.0%) had DR. During a median 6.1 years of follow-up, 23 (3.2%) without baseline DR developed at least moderate NPDR (crude incidence 6.1/1000 person-years) with HbA1c the sole independent predictor (odds ratio [95% CI]: 1.62 [1.30-2.02] per 1% [11 mmol/mol] increase). Trajectory analysis showed two distinct groups, those with baseline/persistent DR (20%) and those remaining DR free (80%). Longer diabetes duration, insulin use, higher mean HbA1c , higher mean systolic blood pressure and higher mean urinary albumin: creatinine ratio all increased the odds (p ≤ 0.014) of being in the persistent DR trajectory group. CONCLUSIONS: The low incidence of at least moderate NPDR reflects the trajectory analysis. The currently recommended biennial retinal screening frequency for individuals without DR could potentially be extended.

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. The prevalence of any DR and moderate non-proliferative DR (NPDR), and the incidence of new or worsening DR were ascertained using baseline and 4-year follow-up data. RESULTS: Compared with Anglo-Celts, the Aboriginal participants had a higher prevalence of any DR (33.0% vs 52.1%) and moderate NPDR or worse (5.1% vs 24.4%), and new or worsening DR during follow up (6.7% vs 23.5%). The unadjusted odds ratios (95% confidence interval) of any DR and moderate NPDR at baseline were 2.21 (1.43, 3.39) and 5.98 (3.40, 10.50), respectively, and of new or worsening DR 4.32 (1.33, 13.98). In adjusted models, Aboriginal ethnicity was only associated with the prevalence of moderate NPDR or worse (5.58 (2.44, 12.76)). CONCLUSIONS: Aboriginal participants had a higher prevalence of DR and new or worsening DR, reflecting conventional risk factors including suboptimal glycaemic control. Their significantly higher odds of moderate NPDR or worse in adjusted models suggest ethnic-specific determinants of DR severity. These findings highlight the need for equitable, culturally appropriate diabetes/ophthalmic care.

Retinopathy predicts stroke but not myocardial infarction in type 2 diabetes: the Fremantle Diabetes Study Phase II.

BACKGROUND: Microangiopathy in type 2 diabetes (T2D) is associated with cardiovascular disease (CVD), but most relevant studies were performed > 10 years ago. CVD risk factor management has since improved. The aim of this study was to determine whether diabetic retinopathy (DR) and its severity increases stroke and myocardial infarction (MI) risk in a contemporary cohort. METHODS: Fremantle Diabetes Study Phase II participants with T2D had DR graded from fundus photography at baseline between 2008 and 2011. Subsequent hospitalizations and mortality for MI or stroke were ascertained through validated data linkage to end-2016. Cox regression modelling identified predictors of first stroke and MI including DR presence and severity. RESULTS: The 1521 participants with T2D and known DR status (mean age 65.6 years, 52.1% males, median diabetes duration 9.0 years) were followed for a mean of 6.6 years. After excluding those with prior MI/stroke, there were 126 incident MIs among 1393 eligible participants and 53 incident strokes in 1473 eligible participants, respectively. Moderate non-proliferative DR (NPDR) or worse was significantly and independently associated with an increased risk of incident stroke (adjusted hazard ratio 2.55 (95% CI 1.19, 5.47), p = 0.016). Retinopathy presence and severity increased the risk of incident MI in unadjusted models (p ≤ 0.001), but these associations were no longer statistically significant after adjusting for other risk factors. CONCLUSIONS: Moderate NPDR or worse was associated with an increased risk of first stroke in Australians with T2D. Intensified CVD risk factor management should be considered for patients with at least moderate NPDR.

Evaluating the impact of optical coherence tomography in diabetic retinopathy screening for an Aboriginal population.

IMPORTANCE: Optical coherence tomography is used routinely in management of diabetic eye disease but has not been evaluated in Australian outreach settings for screening programmes. BACKGROUND: The study aims to evaluate the use of optical coherence tomography combined with a fundus camera compared with a fundus camera only in a telehealth diabetic retinopathy screening programme for Aboriginal Australians. DESIGN: Retrospective comparative study was used. PARTICIPANTS: The study included patients with diabetes at two Aboriginal Health Services. METHODS: An intervention group was studied in 2015 using a Topcon 3D optical coherence tomography-1 Maestro combined with optical coherence tomography/fundus camera. A control group was studied in 2014 using a DRS non-mydriatic fundus camera. Fundus photographs were emailed to trained retinal graders for review. Optical coherence tomography scans were graded by ophthalmologists via remote TeamViewer access. MAIN OUTCOME MEASURE: Referral rates to an eye health professional and the rate of inadequate photographs. RESULTS: Two hundred and twenty-two patients were included, with 80 in the control group and 142 in the intervention group. There was a significantly higher rate of inadequate fundus photographs in the intervention group (31.0% vs. 13.8%). Although there was a higher rate of referral to an eye health professional in the intervention group (39.6% vs. 30.0%), this was not significant. Diabetic retinopathy and maculopathy was evident in 32.3% and 12.0% of adequate fundus photographs, respectively. Diabetic macular oedema was present in 3.6% of optical coherence tomography scans. CONCLUSIONS AND RELEVANCE: The combined optical coherence tomography fundus camera provided no advantage for diabetic retinopathy screening compared with fundus photography in an Australian programme. The rate of referral to an eye health professional was not reduced with a higher rate of inadequate fundus photographs.

Real-time teleophthalmology in rural Western Australia.

OBJECTIVE: This study aims to assess the current utilisation of a real-time teleophthalmology service for rural Western Australia (WA). DESIGN: Service evaluation by prospective audit. SETTING: Includes general practices, optometrists, hospitals in rural WA and the Lions Eye Institute in Perth. PARTICIPANTS: Eighty-five patients from rural WA participating. INTERVENTIONS: Video consultation (VC) with a general ophthalmologist. MAIN OUTCOME MEASURES: Number of referring practitioners and their locations, software and imaging equipment used as well as the presentation, working diagnosis and follow-up plan for each consultation. RESULTS: Eighty-five participants took part in a total of 100 VCs in the 5-month data collection period. There were 49 men (58%); age range 7-92 years; 31 identified as Indigenous Australian (37%). Participants were referred by optometrists (59%), hospital district medical officers (23%) and GPs (18%). Karratha (41%), Albany (20%) and Broome (14%) were the main VC locations. There were 31 different eye conditions managed; red eye, acute vision loss, known glaucoma and abnormal retinal photographs were the main presentations. Skype was the commonly used software (71%). Images were provided in 63% of all VCs. The main equipment used included digital retinal cameras (56%), smartphones (25%) and digital slit lamps (13%). An outpatient appointment with the ophthalmologist was recommended following 35 VCs. CONCLUSIONS: Optometrists used this service most frequently, despite a lack of financial incentive. Digital retinal cameras and smartphones were the most commonly used imaging modalities. Overall, real-time teleophthalmology was used in the management of a broad range of eye conditions and was a useful supplement to outreach ophthalmology services.

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. The validation set consisted of 1682 consecutive, single-field, macula-centred retinal photographs from 864 patients with diabetes (mean age 54.9 years, 52.4% women) at an Indigenous primary care service in Perth, Australia. Three-person adjudication by a panel of specialists served as the reference standard. RESULTS: For mtmDR detection, sensitivity of the DLS was superior to the retina specialist (98.0% (95% CI, 96.5 to 99.4) vs 87.1% (95% CI, 83.6 to 90.6), McNemar's test p<0.001) with a small reduction in specificity (95.1% (95% CI, 93.6 to 96.4) vs 97.0% (95% CI, 95.9 to 98.0), p=0.006). For vtDR, the DLS's sensitivity was again superior to the human grader (96.2% (95% CI, 93.4 to 98.6) vs 84.4% (95% CI, 79.7 to 89.2), p<0.001) with a slight drop in specificity (95.8% (95% CI, 94.6 to 96.9) vs 97.8% (95% CI, 96.9 to 98.6), p=0.002). For all-cause referable DR, there was a substantial increase in sensitivity (93.7% (95% CI, 91.8 to 95.5) vs 74.4% (95% CI, 71.1 to 77.5), p<0.001) and a smaller reduction in specificity (91.7% (95% CI, 90.0 to 93.3) vs 96.3% (95% CI, 95.2 to 97.4), p<0.001). CONCLUSION: The DLS showed improved sensitivity and similar specificity compared with a retina specialist for DR detection. This demonstrates its potential to support DR screening among Indigenous Australians, an underserved population with a high burden of diabetic eye disease.

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. METHODS: Colour fundus images from participants with known diabetic retinopathy or age-related macular degeneration were randomly selected from ophthalmology clinics in four rural Australian centres. Grading was confirmed retrospectively by two retinal specialists. RetCAD produced a quantitative measure (0-100) for DR and AMD severity. The area under the ROC curve (AUC) was calculated. Sensitivity, specificity, and positive and negative predictive values were calculated at a pre-defined cut-point of ≥50. RESULTS: A total of 150 images from 82 participants were included. The mean age (SD) was 64.0 (12.8) years. Seventy-nine (52.7%) eyes had evidence of referable DR, while 54 (36.0%) had evidence of referable AMD. The AUC for referable DR detection was 0.971 (95% CI 0.950-0.936) with a sensitivity of 86.1% (76.8%-92.0%) and a specificity of 91.6% (82.8%-96.1%) at the pre-defined cut-point. Using the Youden Index method, the optimal cut-point was 41.2 (sensitivity 93.7%, specificity 90.1%). The AUC for the detection of referable AMD was 0.880 (0.824-0.936). At the pre-defined cut-point sensitivity was 88.9% (77.8%-94.8%) and specificity was 66.7% (56.8%-75.3%). The optimal cut-point was 52.6 (sensitivity 87.0%, specificity 75.0%). CONCLUSION: RetCAD is comparable with but does not outperform equivalent deep-learning systems for retinal disease detection. RetCAD may be suitable as an automated screening tool in a rural Australian setting.

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. We begin by outlining the key concepts and technological advances which have enabled the development of these models, providing an overview of novel training approaches and modern AI architectures. Next, we summarise existing literature on the topic of foundation models in ophthalmology, encompassing progress in vision foundation models, large language models and large multimodal models. Finally, we outline major challenges relating to privacy, bias and clinical validation, and propose key steps forward to maximise the benefit of this powerful technology.

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. SUBJECTS/METHODS: Patients referred for treatment-resistant hypertension were imaged at a hospital unit in Perth, Australia, between 2016 and 2022. The same 45° colour fundus photograph selected for each of the 433 participants imaged was processed by three deep learning algorithms. Two expert retinal specialists graded all false-positive results for diabetic retinopathy in non-diabetic participants. RESULTS: Of the 29 non-diabetic participants misclassified as positive for diabetic retinopathy, 28 (97%) had clinically useful retinal biomarkers. The models designed to screen for fewer diseases captured more incidental disease. All three algorithms showed a positive correlation between severity of hypertensive retinopathy and misclassified diabetic retinopathy. CONCLUSIONS: The results suggest that diabetic deep learning models may be responsive to hypertensive and other clinically useful retinal biomarkers within an at-risk, hypertensive cohort. Observing that models trained for fewer diseases captured more incidental pathology increases confidence in signalling hypotheses aligned with using self-supervised learning to develop autonomous comprehensive screening. Meanwhile, non-referable and false-positive outputs of other deep learning screening models could be explored for immediate clinical use in other populations.

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. Two reviewers independently conducted the search and reviewed the articles for quality and relevant information. The heterogeneity of the data meant that a meta-analysis was not appropriate. Twelve publications were included. Studies were of good quality and many used data from DR screening programs. Studies fit into three categories; those that assessed specific DR screening intervals, those that determined optimal DR screening intervals and those that developed/assessed DR screening risk equations. For those with type 2 diabetes, extending screening intervals to 3- to 4-yearly in those with no baseline DR appeared safe. DR risk equations considered clinical factors and allocated those at lower risk of DR progression screening intervals of up to five years. Those with baseline DR or type 1 diabetes appeared to have a higher risk of progression to STDR and needed more frequent screening. DR screening intervals can be extended to 3-5 yearly in certain circumstances. These include patients with type 2 diabetes and no current DR, and those who have optimal management of other risk factors such as glucose and blood pressure.

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. METHODS: Data from patients referred during the COVID-19 lock-down period (23 March 2020 to 5 June 2020) were analysed. If sufficient clinical information and imaging were available then ophthalmologists conducted home-based telephone consultations. If further ocular imaging or examination was required, then optometry-based video or hospital-based video were used. Data were analysed using ANOVA and two-sided t tests for continuous data and Chi Square statistics for categorical data (p < 0.05). RESULTS: Majority of the 431 consultations were conducted via home telephone (38%) or optometry-based video (37%). Indigenous patients (p = 0.014) and patients in very remote communities (p < 0.01) were more likely to receive a home-based telephone consultation. Because sufficient clinical information had already been obtained for home-based consultations, these patients were more likely to be booked for surgery than optometry (p < 0.01).Cataracts were the predominant diagnosis in optometry consults compared to hospital (p < 0.01). CONCLUSION: Primary optometry and home telephone represent a new modality for providing specialist care for patients living in very remote regions and for Indigenous patients. When appropriate clinical testing has been completed, telephone-based ophthalmology may continue to be useful for certain conditions such as waitlisting patients for cataract surgery and should continue to be funded beyond the duration of the pandemic for rural patients.

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. We present our journey toward establishing a comprehensive teleophthalmology model built on the principles of collaborative care, with a focus on delivering practical lessons for service design. Artificial intelligence is an emerging technology that has shown potential to further address resource limitations. We explore the applications of artificial intelligence and the need for targeted research within underserved settings in order to meet growing healthcare demands. Based on our rural telemedicine experience, we make the case that similar models may be adapted to urban settings with the aim of reducing surgical waitlists and improving efficiency.