Search

How can empirical investigations conducted on medical and healthcare interactions contribute to the training and education of professionals, trainees, patients and clients? This edited volume offers some answers in the form of a collection of empirical studies by scholars in ethnomethodology and conversation analysis (EMCA). The studies are based on video-recordings of real-life work and training encounters among medical and healthcare professionals and trainees or between professionals and patients. They provide detailed descriptions and discussions of the methods and procedures through which interactants produce actions and interpret those of others. The volume sheds light on medical/healthcare members’ competences as recognizably displayed in situated courses of interaction and the ways in which members’ socialization is achieved in distinct work, teaching, and learning settings. In doing so, the volume provides new insight to a growing research field in which contributing to medical/healthcare work and training practices is something that members of the field under study and its research community approach in collaboration with each other.

This chapter focuses on face-to-face physiotherapy consultations in which a mobile eHealth tool (hereafter “the app”) is introduced to the patient. Based on video-recordings, it examines how physiotherapists and patients accomplish the introduction task. Over the past few decades, the benefits of digital tools in physiotherapy, notably to support patients’ self-management and allow patients’ remote access to physiotherapy, have been stressed and numerous apps have been developed. However, in Switzerland, their implementation in ambulatory practice is slow and the adoption rate remains low overall. Although pressure on physiotherapists to adopt the app is significant, its use in physiotherapy practice is underexamined. We reveal how physiotherapists’ and patients’ organization of the introduction to the app's functions and options for home use involves the operation of patients’ smartphones. The instructional sequences are constantly adapted to the situated contingencies, such as the time constraints inherent to physiotherapy consultations, technological affordances, and patients’ claimed or displayed understanding of the app. Introductions are thereby achieved in a time-efficient way, while expansions on issues that participants consider relevant for the app's use at home remain possible at any time, and participants treat patients’ socialization to eHealth literacy as sufficient for all practical purposes at hand.

BACKGROUND: Myopic macular degeneration (MMD) is a primary cause of blindness and visual impairment in many parts of the world. A review of clinical practice guidelines (CPGs) for intervention selection are required with the increasing demand for MMD management in clinical practice as well as in national health services. Therefore, we aim to systematically review CPGs for MMD and assist the recommendations development of the Package of Eye Care Interventions (PECI) program of the World Health Organization. METHODS: A systematic review of CPGs published on MMD between 2010 and April 2020 was conducted. Guidelines were evaluated using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. Cochrane systematic reviews were also included when the evidence from included CPGs were inadequate or contradict. RESULTS: After applying exclusion criteria and conducting the quality appraisal, two CPGs were finally included. The average of the AGREE II ratings for the identified Guidelines were 56 and 63 respectively (7 for each item). To provide further information on interventions for MMD, one Cochrane review on MMD was additionally identified and included in the study. Intravitreal anti-vascular endothelial growth factor (anti-VEGF) drugs were recommended for patients with myopic choroidal neovascularization (mCNV) as first-line therapy to improve vision and reduce central macular thickness, and ranibizumab showed significant effectiveness compared to photodynamic therapy (PDT). PDT was recommended to be performed in those resistant to the treatment by one CPG but lacked of adequate description and support. Data extracted from the Cochrane systematic reviews indicated that anti-VEGF therapy for mCNV had significant effectiveness in improving visual acuity and reducing CMT compared to PDT with moderate to low certainty of evidence. Ranibizumab and bevacizumab were considered as equally effective with moderate certainty. CONCLUSIONS: The outcomes of this revi

The objective of this paper is to provide an overview of the World Health Organization - International Telecommunication Union MyopiaEd programme - a digital message programme targeting education on myopia and its prevention. The development of the MyopiaEd programme included 4 key steps: (1) Conceptualization and consultation with experts in the field of myopia, mHealth and health behavior change; (2) Creation of SMS message libraries and programme algorithm; (3) Review of the message libraries to ensure relevance to the target audience; and (4) Pre-testing amongst end-user groups to ensure that the design of the programme and the message content were understandable. After reviewing the available evidence and considering input of the experts, the aims, end users and key themes of the programme were finalized. Separate SMS-adapted message libraries were developed, reviewed and pre-tested for four target end-user groups; (1) general population involved in the care of children (2) parents or caregivers of children with myopia; (3) adolescents with myopia; and (4) adults with myopia. The message libraries are part of a comprehensive toolkit, developed through a consultative process with experts in digital health, to support implementation within countries. The development of the MyopiaEd programme aims to provide a basis for Member States and other stakeholders to develop, implement and monitor large-scale mHealth programmes. It is aimed at raising awareness of good eye care behaviors and addressing common reasons for non-compliance to spectacle wear. The next steps will involve adapting and evaluating the MyopiaEd programme in selected settings.

IMPORTANCE: Despite persistent inequalities in access to eye care services globally, guidance on a set of recommended, evidence-based eye care interventions to support country health care planning has not been available. To overcome this barrier, the World Health Organization (WHO) Package of Eye Care Interventions (PECI) has been developed. OBJECTIVE: To describe the key outcomes of the PECI development. EVIDENCE REVIEW: A standardized stepwise approach that included the following stages: (1) selection of priority eye conditions by an expert panel after reviewing epidemiological evidence and health facility data; (2) identification of interventions and related evidence for the selected eye conditions from a systematic review of clinical practice guidelines (CPGs); stage 2 included a systematic literature search, screening of title and abstracts (excluding articles that were not relevant CPGs), full-text review to assess disclosure of conflicts of interest and affiliations, quality appraisal, and data extraction; (3) expert review of the evidence extracted in stage 2, identification of missed interventions, and agreement on the inclusion of essential interventions suitable for implementation in low- and middle-income resource settings; and (4) peer review. FINDINGS: Fifteen priority eye conditions were chosen. The literature search identified 3601 articles. Of these, 469 passed title and abstract screening, 151 passed full-text screening, 98 passed quality appraisal, and 87 were selected for data extraction. Little evidence (≤1 CPG identified) was available for pterygium, keratoconus, congenital eyelid disorders, vision rehabilitation, myopic macular degeneration, ptosis, entropion, and ectropion. In stage 3, domain-specific expert groups voted to include 135 interventions (57%) of a potential 235 interventions collated from stage 2. After synthesis across all interventions and eye conditions, 64 interventions (13 health promotion and education, 6 screening and prev

BACKGROUND: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from par

Our vision for the food system is to supply all people living in Switzerland with healthy food meeting their demands for nutrients and well-being in a sustainable way. The latter must allow the following generations to produce enough food for them with the same intensity. It is a food system in which producers get recognition for their important work, have a fulfilling job with a good income. Consumers have access to food but also education about nutrition, the way food is produced and processed and best also about how it is handled and experienced in a cultural context. A sustainable and healthy diet is the focus of all policy measures proposed. These changes are part of a policy framework which supports climate friendly production practices, shifts subsidies in the direction of a plant-based diet and allows us to get away from the dependence on highly polluting methods. Its aim is to enable a sustainable food production considering the evident complexity of the issue and the relations and interactions between agriculture, the environment, society and the economy. It is essential that the issues are addressed in all the proposed fields at the same time. If we omit one of these points, or concentrate only on certain, we run the risk that it can negatively compensate all the efforts in the other fields. A sustainable diet consists of a much larger share of plant based products, compared to today’s consumption patterns. Animal products in the diet will be reduced to one third compared to the present situation. Luxury and unhealthy food items like alcohol, sweets, chocolate, cocoa will have a much lower share in our diet and thus reduce fatalities due to illness caused by malnutrition. Switzerland will further use grasslands for animal production. Ruminant production in Switzerland will be regulated by the amount of grassland available and fodder imports or domestic fodder production will be cut to zero. Greenhouses in Switzerland are only heated by waste energy from i

The eye care sector is well positioned to contribute to the advancement of universal health coverage within countries. Given the large unmet need for care associated with cataract and refractive error, coupled with the fact that highly cost-effective interventions exist, we propose that effective cataract surgery coverage (eCSC) and effective refractive error coverage (eREC) serve as ideal indicators to track progress in the uptake and quality of eye care services at the global level, and to monitor progress towards universal health coverage in general. Global targets for 2030 for these two indicators were endorsed by WHO Member States at the 74th World Health Assembly in May, 2021. To develop consensus on the data requirements and methods of calculating eCSC and eREC, WHO convened a series of expert consultations to make recommendations for standardising the definitions and measurement approaches for eCSC and eREC and to identify areas in which future work is required.

Artificial intelligence technology has advanced rapidly in recent years and has the potential to improve healthcare outcomes. However, technology uptake will be largely driven by clinicians, and there is a paucity of data regarding the attitude that clinicians have to this new technology. In June-August 2019 we conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence. There were 632 complete responses (n = 305, 230, and 97, respectively), equating to a response rate of 20.4%, 5.1%, and 13.2% for the above colleges, respectively. The majority (n = 449, 71.0%) believed artificial intelligence would improve their field of medicine, and that medical workforce needs would be impacted by the technology within the next decade (n = 542, 85.8%). Improved disease screening and streamlining of monotonous tasks were identified as key benefits of artificial intelligence. The divestment of healthcare to technology companies and medical liability implications were the greatest concerns. Education was identified as a priority to prepare clinicians for the implementation of artificial intelligence in healthcare. This survey highlights parallels between the perceptions of different clinician groups in Australia and New Zealand about artificial intelligence in medicine. Artificial intelligence was recognized as valuable technology that will have wide-ranging impacts on healthcare.

OBJECTIVE: To determine the association between cataract surgery and age-related macular degeneration (AMD) in a representative US sample. DESIGN: Population-based, cross-sectional study. SETTING: The US National Health and Nutrition Examination Survey 2005-2008. PARTICIPANTS: A total of 5401 participants aged ≥40 years had information in cataract surgery status and gradable retinal photographs for right eyes. METHODS: Cataract surgery status was obtained from questionnaire. Non-mydriatic fundus photographs were collected and AMD status was assessed. The associations between AMD and cataract surgery were evaluated in right eyes using logistic regression models. RESULTS: Of 338 right eyes with any AMD, 107 right eyes (28.9%) had cataract surgery. After adjusting for multiple variables, there were significant associations between cataract surgery and any AMD (OR 1.36; 95% CI 1.03 to 1.81) or late AMD (OR 2.48; 95% CI 1.01 to 6.09). No significant association was found between cataract surgery and early AMD after adjusting for multiple covariates (OR 1.20; 95% CI 0.91 to 1.59). CONCLUSION: Our results suggest that cataract surgery is associated with the presence of AMD, particularly for late AMD. Longitudinal studies investigating the risk and progression of AMD after cataract surgery are needed in the era of phacoemulsification.

IMPORTANCE: In Australia, nationally representative data of the burden and associations of severe uncorrected refractive error are scarce. BACKGROUND: To report the prevalence and characteristics of severe uncorrected refractive error in Indigenous and non-Indigenous Australians. DESIGN: Population-based cross-sectional study. PARTICIPANTS: A total of 3098 non-Indigenous Australians aged 50 to 98 and 1738 Indigenous Australians aged 40 to 92 living in 30 randomly selected Australian sites were examined. METHODS: Severe uncorrected refractive error was defined as an improvement of ≥2 lines on the logMAR chart in one or both eyes in participants with a presenting visual acuity <6/12. MAIN OUTCOME MEASURE: Severe uncorrected refractive error RESULTS: Prevalence of severe uncorrected refractive error was 11.0% (95% confidence interval 9.3-13.0) in non-Indigenous and 14.5% (12.5-16.7) in Indigenous Australians. Eighty-two percent of non-Indigenous and 77% of Indigenous participants had a spherical equivalent refraction between -2.00D and +2.00D. Indigenous Australians who were older (odds ratio [OR] for 70-79 years vs 40-49 years = 3.59), resided in outer regional areas (OR = 1.78) and did not have an eye examination in the previous 2-years (OR = 1.50) were associated with higher odds of severe uncorrected refractive error. Geographical remoteness (OR = .68 for inner regional), male gender (OR = 1.30), older age (OR for 70-79 years vs 50-59 years = 1.51) and failure to have an eye examination in the previous 2-years (OR = 2.06) were associated with severe uncorrected refractive error among non-Indigenous participants. CONCLUSIONS AND RELEVANCE: Increased public awareness of the importance of regular optometric examinations may be required in groups at high risk of severe uncorrected refractive error.

IMPORTANCE: Projections of Australia's future burden of vision loss will inform eye health service delivery. BACKGROUND: This study aimed to forecast bilateral vision loss in Australia from 2020 to 2050. DESIGN: Population-based survey. PARTICIPANTS: Indigenous and non-indigenous Australians (n = 4253) aged ≥50 years from the National Eye Health Survey (NEHS, 2015-2016). METHODS: Using the age-and-sex-stratified prevalence of vision loss (better eye visual acuity <6/12) from the NEHS, the prevalence of, and number of people aged ≥50 years with, vision loss were forecast to 2050 using Australian census projections. MAIN OUTCOME MEASURE: Prevalence of, and number of Australians with, vision loss from 2020 to 2050. RESULTS: The prevalence of vision loss is predicted to increase from 6.7% to 7.5% by 2050. Owing to population dynamics, the estimated number of Australians ≥50 years old with vision loss will nearly double from 532 386 in 2016 to 1 015 021 in 2050. The greatest increase in vision loss is expected to occur in those aged ≥80 years (2.6-fold, 2016 = 144 240; 2050 = 376 296). The number of people with uncorrected refractive error is projected to increase 1.7-fold, from 331 914 in 2016 to 578 969 in 2050. CONCLUSIONS AND RELEVANCE: Due to population growth and ageing, the future burden of vision loss in Australia is likely to increase, but the magnitude of this change is uncertain due to a lack of available data on some relevant input variables. Nonetheless, efforts are required to ensure early detection and treatment of major eye conditions, particularly treatable conditions such as uncorrected refractive error and cataract.

Orthokeratology (Ortho-K) works to reshape cornea and is the only non-surgical way to enable vision without corrective aids. However, its effect is only temporary, and successful stabilization requires ongoing Ortho-K wear to maintain the reshaping effect. Corneal crosslinking (CXL) is a commonly-used technique in clinical practice to stabilize corneal shape in keratoconic eyes. However, whether or not CXL can stabilize corneal shape after Ortho-K in normal cornea has not been reported. Therefore, this proof-of-concept study using 2 rhesus monkeys aimed to determine the efficacy of the combined procedure. One monkey wore Ortho-K bilaterally for 24 hours, and the other from 6 pm to 8 am for 7 days. The left eyes of both monkeys underwent CXL after Ortho-K while the contralateral eye served as control. Results showed a gradual regression of corneal shape in all eyes with or without CXL. However, eyes underwent CXL regressed more slowly than the control eyes. The control eyes and the CXL treatment eye in the 7-day Ortho-K monkey regressed completely at last, while the CXL treatment eye in the 24 h Ortho-K monkey maintained a corneal flattening of -1.48 D 27 days after procedure. These findings suggest CXL can slow the regression of Ortho-K for a short duration, but cannot sustain its effect according to the current protocol.

BACKGROUND: Previous conventional models for the prediction of diabetes could be updated by incorporating the increasing amount of health data available and new risk prediction methodology. OBJECTIVE: We aimed to develop a substantially improved diabetes risk prediction model using sophisticated machine-learning algorithms based on a large retrospective population cohort of over 230,000 people who were enrolled in the study during 2006-2017. METHODS: We collected demographic, medical, behavioral, and incidence data for type 2 diabetes mellitus (T2DM) in over 236,684 diabetes-free participants recruited from the 45 and Up Study. We predicted and compared the risk of diabetes onset in these participants at 3, 5, 7, and 10 years based on three machine-learning approaches and the conventional regression model. RESULTS: Overall, 6.05% (14,313/236,684) of the participants developed T2DM during an average 8.8-year follow-up period. The 10-year diabetes incidence in men was 8.30% (8.08%-8.49%), which was significantly higher (odds ratio 1.37, 95% CI 1.32-1.41) than that in women at 6.20% (6.00%-6.40%). The incidence of T2DM was doubled in individuals with obesity (men: 17.78% [17.05%-18.43%]; women: 14.59% [13.99%-15.17%]) compared with that of nonobese individuals. The gradient boosting machine model showed the best performance among the four models (area under the curve of 79% in 3-year prediction and 75% in 10-year prediction). All machine-learning models predicted BMI as the most significant factor contributing to diabetes onset, which explained 12%-50% of the variance in the prediction of diabetes. The model predicted that if BMI in obese and overweight participants could be hypothetically reduced to a healthy range, the 10-year probability of diabetes onset would be significantly reduced from 8.3% to 2.8% (P<.001). CONCLUSIONS: A one-time self-reported survey can accurately predict the risk of diabetes using a machine-learning approach. Achieving a healthy BMI can sig

Objectives: To investigate mobile health product use in Australia and societal and clinician perceptions towards smartphone based visual acuity (VA) assessment tools. Design: Quantitative analysis of a cross-sectional survey delivered to the general public and thematic analysis of in-depth interviews of eye health clinicians. Setting: Online survey within Australia and face-to-face in-depth interviews of clinicians. Participants: 1016 adults were recruited via Survey Monkey Audience, social media (Facebook and Twitter), Rotary Australia and Lions Clubs Australia. Six clinicians were recruited from private and public settings in Melbourne, Australia. Primary and secondary outcome measures: The study assessed socio-demographic characteristics, history of mobile health product use and perceived advantages and potential drawbacks of smartphone based VA assessment tools. Results: A total of 14.4% of the study population had previously used a mobile-based health product. After adjusting for covariates, younger age (p=0.001), male gender (p=0.01) and higher income (>$45 000) were associated with increased likelihood of having used a mobile health product (p=0.005). Seventy-two per cent of participants would use an automated smartphone based VA assessment tool, provided that the accuracy was on par to that of human assessors. Convenience (37.3%) and cost-savings (15.5%) were ranked as the greatest perceived advantages. While test accuracy (50.6%), a lack of personal contact with healthcare providers (18.3%) and data security (11.9%) were the greatest concerns. Themes to emerge from clinician qualitative data included the potential benefits for identifying refractive error in patients, as well as the ability to self-monitor vision. Concerns were raised over the potential misuse of self-testing vision apps and the inability to detect pathology. Conclusion: Our findings suggest that a substantial proportion of the Australian population do not use mobile health products. Fur

PURPOSE: To describe the development and validation of a smartphone-based visual acuity (VA) test called Vision at home (V@home). METHODS: Three study populations (elderly Chinese, adolescent Chinese, and Australian groups) underwent distance and near VA testing using standard Early Treatment Diabetic Retinopathy Study (ETDRS) charts and the V@home device; all VA tests used tumbling E optotypes. VA tests were repeated with one eye, selected randomly. Distance VA was measured monocularly at 2 m, and near VA was measured binocularly at 40 cm. Participants also completed a questionnaire about their satisfaction with the device. V@home VA (logMAR) was compared to VA for ETDRS charts at distance and near and test-retest reliability. RESULTS: The mean difference between V@home and ETDRS distance VA across all groups ranged from -0.010 to -0.100 logMAR. Tolerant weighted kappa (TWK) agreement ranged from substantial (0.742) in the Australian group to almost perfect (0.950) in the adolescent Chinese group. There was high agreement of V@home with near ETDRS VA across all groups, with a mean difference of -0.092 to -0.042 logMAR and a TWK of 0.736 to 0.837. Test-retest reliability was also high (difference: -0.018 to 0.026) for both distance and near VA tests (95% limits of agreement: -0.289 to 0.258 for distance and -0.235 to 0.199 for near). The majority of participants were satisfied with V@home. CONCLUSIONS: V@home could accurately and reliably measure both distance and near VA and is well accepted by participants. TRANSLATIONAL RELEVANCE: The V@home system could potentially serve as a useful tool to improve eye care accessibility, especially in underdeveloped areas with limited eye care personnel and resources.

Background: Identifying leading determinants for disease-free status may provide evidence for action priorities, which is imperative for public health with an expanding aged population worldwide. This study aimed to identify leading determinants, especially modifiable factors for disease-free status using machine learning methods. Methods: We included 52,036 participants aged 45-64 years from the 45 and Up Study who were free of 13 predefined chronic conditions at baseline (2006-2009). Disease-free status was defined as participants aging from 45-64 years at baseline to 55-75 years at the end of the follow-up (December 31, 2016) without developing any of the 13 chronic conditions. We used machine learning methods to evaluate the importance of 40 potential predictors and analyzed the association between the number of leading modifiable healthy factors and disease-free status. Results: Disease-free status was found in about half of both men and women during a mean 9-year follow-up. The five most common leading predictors were body mass index (6.4-9.5% of total variance), self-rated health (5.2-8.2%), self-rated quality of life (4.1-6.8%), red meat intake (4.5-6.5%), and chicken intake (4.5-5.9%) in both genders. Modifiable behavioral factors including body mass index, diets, smoking, alcohol consumption, and physical activity, contributed to 37.2-40.3% of total variance. Participants having six or more modifiable health factors were 1.63-8.76 times more likely to remain disease-free status and had 0.60-2.49 more disease-free years (out of 9-year follow-up) than those having two or fewer. Non-behavioral factors including low levels of education and income and high relative socioeconomic disadvantage, were leading risk factors for disease-free status. Conclusions: Body mass index, diets, smoking, alcohol consumption, and physical activity are key factors for disease-free status promotion. Individuals with low socioeconomic status are more in need of care.

IMPORTANCE: Data on the incidence of presenting vision impairment (PVI) and spectacle coverage rate (SCR) in urban China is limited. BACKGROUND: To estimate the 6-year incidence and risk factors for PVI and the SCR in urban Southern China. DESIGN: Population-based cohort study. PARTICIPANTS: A total of 1817 participants aged ≥35 years were identified from Guangzhou in 2008 at baseline and 1427 attended follow-up examination in 2014. METHODS: Presenting visual acuity (PVA) was measured using the ETDRS chart with habitual spectacles. Participants with PVA ≤20/40 underwent subjective refraction at the follow-up visit. Incidence of PVI was calculated using the WHO and US criteria, respectively. The met-need SCR was defined as the percentage of participants with PVA <20/40 that had been improved to ≥20/40 after correction. MAIN OUTCOME MEASURES: Incidence of PVI and SCR. RESULTS: Incidence of PVI was 8.3% (95%CI, 6.9-9.8) and 12.2% (95%CI, 10.5-14.0) based on the WHO and US definition, respectively. Older age, female, lower education level, more myopic spherical equivalent and worse PVA at baseline were significantly related to a higher PVI incidence based on the WHO criteria, with similar associations identified using the US criteria except for gender. The overall met-need SCR was 42.5%, and was lower among the elderly, more hyperopic participants or participants with lower education level. CONCLUSIONS AND RELEVANCE: The incidence of PVI is high in urban Southern China and spectacle wearing is available in less than half of those in need. This highlights the needs to promote spectacle coverage even in the urban population.

IMPORTANCE: Detection of early onset neovascular age-related macular degeneration (AMD) is critical to protecting vision. BACKGROUND: To describe the development and validation of a deep-learning algorithm (DLA) for the detection of neovascular age-related macular degeneration. DESIGN: Development and validation of a DLA using retrospective datasets. PARTICIPANTS: We developed and trained the DLA using 56 113 retinal images and an additional 86 162 images from an independent dataset to externally validate the DLA. All images were non-stereoscopic and retrospectively collected. METHODS: The internal validation dataset was derived from real-world clinical settings in China. Gold standard grading was assigned when consensus was reached by three individual ophthalmologists. The DLA classified 31 247 images as gradable and 24 866 as ungradable (poor quality or poor field definition). These ungradable images were used to create a classification model for image quality. Efficiency and diagnostic accuracy were tested using 86 162 images derived from the Melbourne Collaborative Cohort Study. Neovascular AMD and/or ungradable outcome in one or both eyes was considered referable. MAIN OUTCOME MEASURES: Area under the receiver operating characteristic curve (AUC), sensitivity and specificity. RESULTS: In the internal validation dataset, the AUC, sensitivity and specificity of the DLA for neovascular AMD was 0.995, 96.7%, 96.4%, respectively. Testing against the independent external dataset achieved an AUC, sensitivity and specificity of 0.967, 100% and 93.4%, respectively. More than 60% of false positive cases displayed other macular pathologies. Amongst the false negative cases (internal validation dataset only), over half (57.2%) proved to be undetected detachment of the neurosensory retina or RPE layer. CONCLUSIONS AND RELEVANCE: This DLA shows robust performance for the detection of neovascular AMD amongst retinal images from a multi-ethnic sample and under different imagin

The purpose of this study is to evaluate the feasibility and patient acceptability of a novel artificial intelligence (AI)-based diabetic retinopathy (DR) screening model within endocrinology outpatient settings. Adults with diabetes were recruited from two urban endocrinology outpatient clinics and single-field, non-mydriatic fundus photographs were taken and graded for referable DR ( ≥ pre-proliferative DR). Each participant underwent; (1) automated screening model; where a deep learning algorithm (DLA) provided real-time reporting of results; and (2) manual model where retinal images were transferred to a retinal grading centre and manual grading outcomes were distributed to the patient within 2 weeks of assessment. Participants completed a questionnaire on the day of examination and 1-month following assessment to determine overall satisfaction and the preferred model of care. In total, 96 participants were screened for DR and the mean assessment time for automated screening was 6.9 minutes. Ninety-six percent of participants reported that they were either satisfied or very satisfied with the automated screening model and 78% reported that they preferred the automated model over manual. The sensitivity and specificity of the DLA for correct referral was 92.3% and 93.7%, respectively. AI-based DR screening in endocrinology outpatient settings appears to be feasible and well accepted by patients.

IMPORTANCE: National data on eye health-care service utilization will inform Australia's eye health policy. BACKGROUND: To investigate the utilization of eye health-care services by Australians. DESIGN: Cross-sectional survey. PARTICIPANTS: Indigenous Australians aged 40 years and older and non-Indigenous Australians aged 50 years and older. METHODS: One thousand seven hundred thirty-eight Indigenous Australians and 3098 non-Indigenous Australians were recruited from 30 randomly selected sites, stratified by remoteness. Sociodemographic, ocular history and eye health-care service utilization data were collected, and an eye examination was conducted. MAIN OUTCOME MEASURES: Recentness of eye examinations, types of providers used and associated risk factors. RESULTS: Approximately 67.0% of Indigenous Australians and 82.5% of non-Indigenous Australians underwent an eye examination within the previous 2 years. Indigenous status (P < 0.001), male gender (P < 0.001), Outer Regional (P < 0.001) and Very Remote (P < 0.001) residence were associated with less recent examinations. Participants with >self-reported eye disease or diabetes were most likely to have been examined within the past year (P < 0.001). For Indigenous Australians, older age was associated with recent eye testing (P = 0.001). Those with retinal disease and cataract were more likely to see an ophthalmologist (P < 0.001), and those with refractive error were more likely to see an optometrist (P < 0.001). In Regional Australia, non-Indigenouspeople were more likely to see optometrists (P < 0.001), and Indigenous Australians were more likely to utilize other, non-specialistservices (P < 0.001). CONCLUSIONS AND RELEVANCE: Eye examination frequency has improved in Indigenous and non-Indigenous Australians compared with previous population-based research. Further improvements are required in risk groups including Indigenous Australians and those living in Regional and Remote areas.

IMPORTANCE: In Australia, knowledge of the epidemiology of retinal vein occlusion remains scarce because of a paucity of recent population-based data. The National Eye Health Survey (2015-2016) provides an up-to-date estimate of the prevalence of retinal vein occlusion in non-Indigenous and Indigenous Australian adults. BACKGROUND: To determine the prevalence and associations of retinal vein occlusion in a national sample of Indigenous and non-Indigenous Australian adults. DESIGN: Population-based cross-sectional study. PARTICIPANTS: A total of 3098 non-Indigenous Australians (aged 50-98 years) and 1738 Indigenous Australians (aged 40-92 years) living in 30 randomly selected sites, stratified by remoteness. METHODS: Retinal vein occlusions were graded from retinal photographs using standardized protocols and recorded as central retinal vein occlusion or branch retinal vein occlusion. MAIN OUTCOME MEASURE: Prevalence of retinal vein occlusion. RESULTS: In the non-Indigenous population, the sampling weight adjusted prevalence of any retinal vein occlusion was 0.96% (95% confidence interval: 0.59, 1.6), with branch retinal vein occlusion observed in 0.72% (95% confidence interval: 0.41, 1.2) and central retinal vein occlusion in 0.24% (95% confidence interval: 0.13, 0.47). Any retinal vein occlusion was found in 0.91% (95% confidence interval: 0.47, 1.7) of Indigenous Australians aged 40 years and over, with branch retinal vein occlusion observed in 0.83% (95% confidence interval: 0.40, 1.7) and central retinal vein occlusion in 0.07% (95% confidence interval: 0.02, 0.32). Older age (odds ratio = 1.64 per 10 years, P = 0.006) and the presence of self-reported diabetes (odds ratio = 3.24, P = 0.006) were associated with any retinal vein occlusion after multivariable adjustments. Retinal vein occlusion was attributed as the cause of monocular vision loss (<6/12) in seven (0.25%) non-Indigenous and six (0.36%) Indigenous participants. CONCLUSIONS AND RELEVANCE: These data

IMPORTANCE: Australia is the only developed country to still have pockets of endemic trachoma. The research provides up-to-date, population-based prevalence data of later complications of trachoma amongst a national sample of Indigenous adults. BACKGROUND: To report the prevalence of trachomatous trichiasis (TT) in Indigenous Australians aged 40 years and older. DESIGN: Population-based cross-sectional study. PARTICIPANTS: A total of 1738 (41% male) Indigenous Australians aged 40 years or older, living amongst 30 randomly selected Australian sites, stratified by remoteness. METHODS: Anterior segment examination was performed and trachoma grading for the presence of TT and corneal opacification (CO) was conducted using the WHO (WHO) simplified grading system. MAIN OUTCOME MEASURES: Prevalence of TT. RESULTS: A total of three (0.17%) participants had TT, and there were no confirmed cases of trachomatous CO in the NEHS. All three participants with TT were female and aged 40 years or older. Although they had likely spent their childhoods in more remote areas, two of the three confirmed cases resided in an urban and outer regional area at the time of their examinations. CONCLUSIONS AND RELEVANCE: Our data are in line with ongoing national trachoma surveillance reports that suggest the prevalence of late sequences of trachoma appear to be decreasing in Australia.

Purpose: to describe the methodology and present the retinal grading findings of an older sample of australians with well-defined indices of neurocognitive function in the Personality and total Health (PatH) through life project. Design: a cross-sectional study. Methods: three hundred twenty-six individuals from the PatH through life project were invited to participate. Participants completed a general questionnaire and 2-field, 45-degree nonmydriatic color digital retinal photography. Photographs were graded for retinal pathology according to established protocols. Results: two hundred fifty-four (77.9%) subjects, aged 72 to 78 years, agreed to participate in the eye substudy. gradable images of at least 1 eye were acquired in 211 of 254 subjects (83.1%). retinal photographic screening identified 1 or more signs of pathology in 130 of the 174 subjects (74.7%) with gradable images of both eyes. a total of 45 participants (17.7%) had self-reported diabetes and diabetic retinopathy was observed in 22 (48.9%) of these participants. Conclusions: this well-defined sample of older australians provides a unique opportunity to interrogate associations between retinal findings, including retinal vascular geometric parameters, and indices of neurocognitive function.

Interest in reliable biomarkers of Alzheimer disease, the leading cause of dementia, has been fuelled by challenges in diagnosing the disease and monitoring disease progression as well as the response to therapy. A range of ocular manifestations of Alzheimer disease, including retinal and lens amyloid-beta accumulation, retinal nerve fiber layer loss, and retinal vascular changes, have been proposed as potential biomarkers of the disease. Herein, we examine the evidence regarding the potential value of these ocular biomarkers of Alzheimer disease.

OBJECTIVE: To present the prevalence of self-reported diabetes in Indigenous and non-Indigenous participants in the National Eye Health Survey. RESEARCH DESIGN AND METHODS: 3098 non-Indigenous Australians aged 50-98 years and 1738 Indigenous Australians aged 40-92 years were examined in 30 randomly selected sites, stratified by remoteness. A history of diabetes was obtained using an interviewer-administered questionnaire. RESULTS: 13.91% (431/3098) of non-Indigenous Australians and 37.11% (645/1738) of Indigenous Australians had self-reported diabetes. The age-adjusted prevalence of self-reported diabetes for non-Indigenous and Indigenous Australians was 11.49% and 43.77%, respectively (p <0.001). The prevalence of self-reported diabetes increased markedly with age (OR = 1.04 per year, p = 0.017). Indigenous Australians living in very remote areas were more likely to have self-reported diabetes than those in major city areas (OR = 1.61, p = 0.038). CONCLUSIONS: The prevalence of self-reported diabetes in Australia was high, with the prevalence being almost 4 times higher in Indigenous Australians compared with non-Indigenous Australians. With the prevalence of diabetes likely to increase, the results of this national survey may inform future policy, planning and funding allocation to assist in controlling the diabetes epidemic.

We assessed the validity and reliability of self-report of eye disease in participants with unilateral vision loss (presenting visual acuity worse than 6/12 in the worse eye and equal to or better than 6/12 in the better eye) or bilateral vision loss (presenting visual acuity worse than 6/12 in the better eye) in Australia's National Eye Health Survey. In total, 1738 Indigenous Australians and 3098 non-Indigenous Australians were sampled from 30 sites. Participants underwent a questionnaire and self-reported their eye disease histories. A clinical examination identified whether participants had cataract, age-related macular degeneration, diabetic retinopathy and glaucoma. For those identified as having unilateral or bilateral vision loss (438 Indigenous Australians and 709 non-Indigenous Australians), self-reports were compared with examination results using validity and reliability measures. Reliability was poor for all four diseases (Kappa 0.06 to 0.37). Measures of validity of self-report were variable, with generally high specificities (93.7% to 99.2%) in all diseases except for cataract (63.9 to 73.1%) and low sensitivities for all diseases (7.6% in Indigenous Australians with diabetic retinopathy to 44.1% of non-Indigenous Australians with cataract). This study suggests that self-report is an unreliable population-based research tool for identifying eye disease in those with vision loss.

PURPOSE: To present the rates of referral of participants in the National Eye Health Survey (NEHS) for further eye care. MATERIALS & METHODS: A national sample of 3098 non-Indigenous Australians aged 50-98 and 1738 Indigenous Australians aged 40-92 years living in 30 randomly selected sites was recruited using a door-to-door approach. Participants completed a general questionnaire and a series of eye tests, including vision and anterior segment assessment, intra-ocular pressure measurement, visual field testing and fundus photography. A predefined protocol was used to guide the referral of participants for follow up eye care. An ophthalmologist was on-call to assist with the triaging of participants. RESULTS: Of the total sample, 32.1% (994/3098) of non-Indigenous participants and 43.6% (757/1738) of Indigenous participants were referred for further eye care (p<0.001). A significant difference in referral rates for Indigenous Australians was observed between regions of differing geographic remoteness [range = 32.2% (Inner Regional)-60.4% (Very Remote), p <0.001]. After adjusting for covariates, males (OR = 1.24, 95% CI: 1.06-1.46), older age (OR = 1.02 per year, 95% CI: 1.01, 1.02) and longer time since previous eye examination (OR = 1.15 per year, 95% CI: 1.12, 1.19) were associated with higher rates of eye care referral in the non-Indigenous population. In the Indigenous population, older age (OR = 1.02 per year, 95% CI: 1.01-1.03), self-reported diabetes (OR = 1.70, 95% CI: 1.37-2.12), greater geographical remoteness (OR = 1.19, 95% CI: 1.09-1.29) and longer time since previous eye examination (OR = 1.10 per year, 95% CI: 1.07, 1.13) were associated with a higher rate of referral after multivariate adjustments. A total of 25 participants (1.4%) were referred for urgent follow-up of potentially sight threatening conditions. CONCLUSIONS: Our data has identified several high risk groups that required ophthalmic referral including older Australians, non-Indigenous me