Ophthalmology

The large number of long term hydroxychloroquine users in Australia necessitates clear guidelines on hydroxychloroquine retinopathy screening Hydroxychloroquine retinopathy, which causes permanent visual loss, is a well documented adverse effect in long term users of both hydroxychloroquine and chloroquine. However, it can be difficult to detect as visual acuity is often well preserved until the disease is severe.1 Because of this, it was once thought to be a rare adverse effect, with only 0.5–2.0% of long term hydroxychloroquine users estimated to suffer from the condition.2 However, a 2014 epidemiological study of 2361 patients using hydroxychloroquine long term in the United States found that this was a large underestimation.2 The investigators found an overall prevalence of 7.5% in patients who had taken the drug for at least 5 years, but this risk increased with length of use and dosage.2 Owing to its efficacy in treating a variety of inflammatory and dermatological conditions (eg, systemic lupus erythematosus), cost‐effectiveness and relatively good safety profile, hydroxychloroquine is widely used by many Australians long term.3 In 2015, there were about 28 300 individuals (0.12% of all Australians) using the drug daily.4 Given this estimated number of users and the 7.5% prevalence rate,2 there could be more than 2000 potential cases of hydroxychloroquine retinopathy in Australia. However, there is no recommended consensus on screening for this condition in Australia, which may lead to inconsistent screening and missed cases.5 Existing screening guidelines Currently, two main guidelines on hydroxychloroquine retinopathy screening exist and are used by practitioners in Australia: the American Academy of Ophthalmology 2016 guidelines and the United Kingdom Royal College of Ophthalmologists 2020 guidelines.1,6 While both are very similar, small but significant differences exist between them. For example, both guidelines recommend that patients who fall within the high risk category should commence screening earlier than the general population, who are screened starting from 5 years of taking hydroxychloroquine.1,6 However, there is some disagreement on which risk factors warrant classification into the high risk category (Box 1). Recommendations also vary regarding the frequency of screening in high risk patients.1,6 There are also small differences in the investigations recommended by each set of guidelines. For example, the UK guidelines6 recommend fundus autofluorescence as an additional standard screening investigation (Box 2). The need for Australian guidelines There are currently no studies discussing the prevalence of hydroxychloroquine retinopathy in Australia, which makes it difficult to determine whether current screening practices are sufficient. However, the differences in the US and UK guidelines may have practical consequences for the consistency of hydroxychloroquine detection rates in the Australian population.5 As these guidelines were developed in non‐Australian settings, they may also need to be modified to better suit Australia’s unique context. For example, compared with the US and the UK, Australia has a significantly larger proportion of residents identifying as Asian in ancestry. In 2016, about 13% identified as having Asian ancestry,7 compared with 5.9% of Americans who identified as Asian in 2019.8 Due to the more peripheral pattern of damage from hydroxychloroquine sometimes seen in Asian populations, there are recommendations that a wider 24‐2 or 30‐2 visual field test should be performed for such patients, in addition to the recommended 10‐2 visual field test in the US and UK guidelines.9 Another factor to consider is whether Australia’s public health system can support ophthalmology screening at the frequency recommended by the US and UK guidelines. Already, waiting times for non‐urgent appointments for ophthalmologists in the public system can reach years. In South Australia, the median waiting time for an outpatient ophthalmologist appointment ranges from 4.8 to 17.6 months at metropolitan hospitals,10 which makes annual screening impossible for many patients without private care. The costs to the health system also warrant consideration. Under the current Medicare Benefits Schedule, a standard specialist consultation (item 104) and visual field test (item 11224) would cost $131.65, totalling more than $1.5 million to test 50% of the individuals taking hydroxychloroquine annually in the public setting.11 Australia‐specific screening guidelines could better account for these practical considerations, although further studies would be necessary to determine how successfully the system already supports hydroxychloroquine retinopathy screening based on existing guidelines. Conclusion Given its potential to cause permanent vision loss and the number of Australians taking hydroxychloroquine long term, developing Australian screening guidelines for hydroxychloroquine retinopathy would be beneficial in promoting consistent screening practices tailored to the Australian population. Before these can be established, however, more research needs to be conducted on the prevalence and current detection rates of hydroxychloroquine retinopathy in Australia. Box 1 – Risk factors and recommendations in the United States1 and United Kingdom6 hydroxychloroquine retinopathy screening guidelines Risk factor US UK Hydroxychloroquine dose > 5 mg/kg Yes Yes Renal disease Yes Yes Tamoxifen use Yes Yes Pre‐existing retinal and macular conditions Yes No Equivalent chloroquine dose > 2.3 mg/kg No Yes Box 2 – Screening investigations for hydroxychloroquine retinopathy recommended by the United States1 and United Kingdom6 guidelines Investigations US UK Baseline (for patients with no known pathology) Fundus evaluation of the macula Fundus evaluation of the macula Spectral domain optical coherence tomography Screening 10‐2 visual field test Spectral domain optical coherence tomography 10‐2 visual field test Spectral domain optical coherence tomography Fundus autofluorescence

Marisse T Sonido · Kristopher Rallah-Baker · Monisha Gupta

Rapid advances in AI in ophthalmology are a harbinger of things to come for other fields of medicine The autonomous detection and triage of eye disease, or even accurate estimations of gender, age, and blood pressure from a simple retinal photo, may sound like the realms of science fiction, but advances in artificial intelligence (AI) have already made this a reality.1 Ophthalmology is at the vanguard of the development and clinical application of AI. Advances in the field may provide useful insights into the application of this technology in health care more broadly. Artificial intelligence Once described as the capacity of intelligent machines to imitate human intelligence and behaviour, AI now describes many theories and practices used to achieve computer intelligence (Box 1).2 Machine learning is an application of AI that uses algorithms or statistical models to make decisions or predictions. Complex patterns and relationships are learned from data to generate an outcome.2 Machine learning traditionally relies on the extraction of features from the data by human operators which then serve as input variables to optimise algorithm performance. The performance of these systems is constrained by the features that are recognised as important by humans. In contrast, artificial neural networks are an advanced method of machine learning able to extract features without explicit programming.2 Deep learning is the construction of multiple layers of artificial neural networks which can identify features in data that are not recognisable by humans. Although deep learning systems may be powerful, they lack human‐crafted inputs, meaning that large quantities of data are typically required to train algorithms. Artificial intelligence in ophthalmology As a discipline, ophthalmology is at the forefront of AI system development and translation in clinical practice. Leading uses of the technology include detecting, classifying and triaging a range of diseases, such as diabetic retinopathy, age‐related macular degeneration (AMD), glaucoma, retinopathy of prematurity, and retinal vein occlusion, from clinical images.3 The increasing global burden of eye diseases, coupled with the development of new therapies for previously untreatable conditions, has served as a major driver for AI innovation in ophthalmology. As a case in point, there are presently over 430 million people living with diabetes, most of whom require annual or biennial screening for retinopathy using retinal photography. This vast demand for diabetic eye screening services has stimulated the development of AI algorithms to identify sight‐threatening disease. Several algorithms have achieved performance that meets or exceeds that of human experts.4,5 Accordingly, in 2018, the United States Food and Drug Administration approved an AI system to detect referable diabetic retinopathy from retinal photographs, the first autonomous diagnostic system to be approved in any field of medicine.6 Advances in deep learning have extended to other imaging modalities that are commonly used in ophthalmology. Ocular coherence tomography is an imaging technology that produces highly detailed, depth‐resolved images of the retina. A recent collaboration between researchers and clinicians at Google DeepMind, Moorfields Eye Hospital and University College London culminated in the development of a deep learning system capable of detecting and triaging more than 50 different retinal conditions at levels equivalent to a panel of experienced ophthalmologists.7 AI systems with the capacity to detect a wide range of diseases, such as this, are likely to be most useful in clinical practice. A highly anticipated innovation is the development of AI systems capable of accurate disease prediction. Such tools could assist in managing patient expectations, improve the quality of care and reduce treatment costs.3 In ophthalmology, prediction models have been trained to personalise re‐treatment intervals for patients with neovascular AMD,8 predict progression from early to late AMD,9 estimate the extent of future visual field defects in patients with glaucoma,10 and predict diabetic retinopathy progression.11 Although these models presently achieve only moderate levels of accuracy, their performance has been shown to be superior to humans in several studies.3,8 Future advances in the accuracy of prediction models will likely come from the use of large longitudinal datasets drawing on multiple data sources, together with the development of more advanced AI systems.3 Despite these significant advances, AI systems are not in widespread clinical use and in some cases real‐world performance has been inferior compared with in silico validation.2,3 Training and validation of deep learning algorithms with large, representative data (eg, data from people of different ethnicities) acquired using multiple devices (eg, different retinal camera models) and data collection protocols (eg, retinal photographs acquired with and without pupil dilation) are key to achieving clinical applicability.4,5 This approach was used in the development of deep learning systems for retinal photographic screening for diabetic retinopathy, AMD and glaucoma which are now being used in large scale screening programs in Singapore and China.4,5 In these programs, AI is used to identify images without evidence of disease, so that human graders can focus their efforts on the images of those with disease, enabling improved efficiency and cost savings.12 Challenges to the clinical adoption of artificial intelligence Several obstacles to the adoption of AI in health care remain. The training of deep learning systems requires access to large amounts of medical data which has significant implications relating to privacy and data protection. In the context of ophthalmology, this is particularly pertinent, as the retinal vasculature may be considered biometric data, making it impossible to completely anonymise retinal photographs.3 Furthermore, characteristics that are not visible to human examiners, such as age and sex, can now be accurately predicted from a single retinal photograph using deep learning.1 Several recent major breaches of data protection laws relating to AI system development have already come to light.13 While individual patient data used to train an algorithm do not remain within the system, incorrect handling and sharing of data may lead to patients withdrawing consent to the use of their data under General Data Protection Regulation laws. It is not certain how data withdrawal requests will be dealt with when an individual’s data have been used in the process of training a deep learning system. Accordingly, developments in AI need to be accompanied by advanced data protection and security measures. Another challenge to the acceptance of deep learning algorithms in medicine is the difficulty in determining the basis for clinical decisions made by these systems, informally described as the “black box” problem. Visualisation tools have been developed to assist clinicians by highlighting the salient image features that contribute to the AI system classification (Box 2).12 This has the potential to create trust in system‐generated decisions, particularly if the features correspond with those used by experienced clinicians for clinical decision making.14 Interpretability is particularly important when considering legal liability in the event of patient harm arising from the use of AI in medicine. In traditional malpractice cases, a physician may be asked to justify the basis for a particular clinical decision and this is then considered in light of conventional medical practice.15 In comparison, challenges in identifying the basis for a given decision made by AI might pose problems for clinicians whose actions were based on that decision. The extent to which the clinician, as opposed to the technology manufacturer, should be held accountable for harm arising from AI use is a subject of intense debate.15 Factors such as the manner in which these AI systems are used and their classification as either products or software are likely to have important bearings on how cases are litigated.15 Further challenges for existing regulatory frameworks come from algorithms that continue to learn and evolve over time.15 Understanding how a given system is trained, its accuracy, and its operational limits is of great importance. Oversampling of a particular population or disease severity during training has the potential to introduce bias.4 Therefore, consideration of performance thresholds will help to inform appropriate use of AI systems. The Australian Government, through the CSIRO and Data61;16 the Australian Council of Learned Academies;17 the Australian Academy of Health and Medical Sciences;18 and specialty groups, such as the Royal Australian and New Zealand College of Radiologists,19 have made significant efforts to develop frameworks and policies for the effective and ethical development of AI. These consultative works have highlighted key priorities, including building a specialist AI workforce, ensuring effective data governance and enabling trust in AI through transparency and appropriate safety standards. Through targeted investment in research and development, Australia is aiming to advance its AI competitiveness. These framework documents provide guidance for developers, clinicians and health care consumers to navigate this rapidly evolving field. Broad dissemination of these documents should form part of a wider public engagement and education campaign to ensure that AI is developed and used in a considered and careful manner in health care. Rapid advances in AI in ophthalmology are a harbinger of things to come for other fields of medicine. While these technologies may eventually lead to more efficient, cost‐effective and safer health care, they are not a panacea in isolation. The successful integration of AI into health systems will need to first consider patient needs, ethical challenges and the performance limits of individual systems. Box 1 – Relationship between artificial intelligence and its subtypes Box 2 – Original retinal photograph of right eye with macular degeneration (A). Heat map of image A showing visualisation of traditional features associated with macular degeneration, such as central scarring (B). Original retinal photograph of left eye with referable diabetic retinopathy (C). Heat map of image C showing visualisation of traditional features, such as micro‐aneurysms and haemorrhages (D)

Jane Scheetz · Mingguang He · Peter Wijngaarden

To the Editor: Elasticated straps — also known as “octopus” straps or bungee cords — are used to secure loads of various shapes and sizes. Unexpected release of the potential energy stored in these straps can cause catastrophic injuries. The Royal Victorian Eye and Ear Hospital (RVEEH) is the largest eye hospital in Australia and is well positioned to assess and treat a variety of ocular injuries. We explored trends in presentations to the RVEEH emergency department (ED) for such injuries between 2007 and 2018, using the ED triage database and information relating to total numbers of ocular trauma presentations. This study was approved by the RVEEH Ethics Committee (09/886H). Between 2007 and 2018, there were 169 presentations involving an elasticated strap‐related eye injury (145 male and 24 female; mean age, 43.4 years). While most patients had multiple injuries, the most common primary diagnosis was traumatic hyphaema, followed by corneal abrasion and open globe (full‐thickness wounds) injuries (Box). There were 23 admissions, of which 21 required surgical intervention, with vitrectomy, orbital wound exploration and closure, and lensectomy being the most common procedures. The final visual acuity measurements of the 17 patients who were admitted and able to be followed up were 6/36 or better for nine patients and 6/60 or worse for eight patients. While males presented more frequently than females, the absolute number of yearly presentations by gender was stable. Elasticated strap‐related injuries accounted for 0.23% of the total 72 663 ocular trauma presentations in the period. While it is problematic to compare incidence with previous studies, due to factors such as growth of the RVEEH ED, growth of other hospitals around Melbourne, and population growth, elasticated strap‐related eye injuries remain a significant contributor to presentations at the RVEEH. These straps were a known danger in the early to mid‐1990s1 and they remain dangerous more than 20 years later, causing severe ocular damage and requiring operative intervention in 12.4% of patients. Although the total number of elasticated strap‐related eye presentations does not appear to be dramatically rising, the continued presence of severe eye injuries necessitating admission for surgical intervention is cause for concern. Multiple steps can be taken to address the continued challenge of elasticated strap‐related injuries. Thorough assessment of the patient remains crucial to facilitate prompt treatment of vision‐threatening diagnoses. In addition, preventive measures should be undertaken to lessen the likelihood of visual loss caused by these devices. This includes patient education and encouraging the use of alternative devices that are functionally similar but pose no risks to eyesight, such as non‐elasticated straps that can be gradually tightened, braided metal locking straps, or even self‐contained soft roof rack and strap combinations. Regulators should also consider whether the convenience of elasticated straps justifies the danger they continue to pose to eyesight almost half a century after they were first introduced to Australia and the first eye‐related injury was reported.2 Box – Primary diagnoses of elasticated strap‐related eye injury sequelae table#t1 tbody td:nth-child(n+2) P. Pleft { text-align: center; } Primary diagnosis* Total cases Traumatic hyphaema 63 (3.3%) Corneal abrasion 42 (24.9%) Open globe injury 11 6.5%) Conjunctival/lid/canalicular laceration 7 (4.1%) Commotio retinae 8 (4.7%) Traumatic iritis/mydriasis/uveitis 7 (4.1%) Periorbital haematoma 3 (1.8%) Corneal foreign body 2 (1.2%) Subconjunctival haemorrhage 2 (1.2%) Traumatic glaucoma 2 (1.2%) Conjunctival abrasion 1 (0.6%) Vitreous haemorrhage 1 (0.6%) Posterior vitreous detachment 1 (0.6%) Retinal detachment 1 (0.6%) Lens dislocation 1 (0.6%) Other injury 5 (3.0%) No abnormality detected 7 (4.1%) Patient did not wait to be seen 5 (3.0%) Total 169

Philip Rothschild · Peter Meagher · Thomas G Campbell

A 75-year-old man was referred to our centre with a history of sudden onset painless loss of vision in the right eye, on a background of recent jaw claudication and weight loss

Khizar Rana · Carmen Oakley · David M Ross · Sumu Simon

A 23-year-old woman was referred to the ophthalmology clinic with sudden onset unilateral paracentral scotomas

Sarah Chan

Herpes zoster ophthalmicus (HZO), a condition that affects the ophthalmic division of the trigeminal nerve, is caused by reactivation of latent varicella zoster virus;1,2 about 10% of people with varicella zoster infections experience HZO.1 Over the past decade, the number of emergency department presentations by people with herpes zoster in Australia has increased by 2–6% per year, and the number of people with herpes zoster managed in general practice has almost doubled.3 The purpose of our study was to develop a contemporary perspective of the clinical presentation, incidence of complications, and treatment practice for patients with HZO referred to an Australian tertiary eye hospital. We performed a retrospective audit of digital health records of the first 100 consecutive patients who presented to the Royal Victorian Eye and Ear Hospital (RVEEH) emergency department with HZO during July 2017 – July 2018. The investigation was approved by the Human Research Ethics Committee of the Hospital as a quality control project (reference, 18/1416HL). The clinical features at the time of presentation of the 100 patients are summarised in the Box. Sixty‐five patients initially presented to their general practitioner, 20 to a hospital emergency department, and 15 directly to the RVEEH. The mean time between rash onset and presentation to a GP or emergency department was 3.3 days (range, 0–14 days). For 51 patients, treatment commenced before presentation to the RVEEH (famciclovir, 27; valaciclovir, 16; acyclovir, 6; two patients had received no topical treatment); treatment had commenced within 72 hours of the rash developing for 36 of these patients (71%). The recommended dose and frequency were prescribed for 16 of the 51 patients: famciclovir (500 mg three times a day), two patients; valaciclovir (1 g three times a day), 12 patients; acyclovir (800 mg five times a day), two patients. For 29 patients, antiviral therapy was prescribed at lower than the recommended dose (famciclovir, 21 patients; valaciclovir, two patients; acyclovir, two patients) or prescribed as a topical treatment (acyclovir, two patients); the prescribing information was not documented for five patients. Nineteen of the 68 patients who attended follow‐up 7–14 days after their initial presentation to the RVEEH presented with ocular symptoms regarded as late complications, including four with more than one complication. Eight of 29 patients (29%) who had not commenced systemic antiviral therapy within 72 hours of rash onset developed late complications, as did 13 of 71 patients (18%) who were treated within 72 hours (Fisher exact test: P = 0.78). We found concerning variations in timing and practice of treating HZO, despite recognised clinical guidelines.4,5 This may be partly explained by diagnostic uncertainty caused by the variability of clinical signs during the early stages of HZO,6 and by an earlier discrepancy between the famciclovir dosing recommended by therapeutic guidelines (250 mg three times a day) and recommendations based upon the results of a clinical trial4 (500 mg three times a day). This discrepancy has since been resolved in the therapeutic guidelines.4 Our findings suggest that education of all health care professionals involved in the care of patients with HZO needs to be improved. Clinical practice guidelines must provide clear and consistent information about managing HZO. Box – Demographic characteristics and clinical features of 100 consecutive people presenting with herpes zoster ophthalmicus to the Royal Victorian Eye and Ear Hospital, July 2017 – July 2018 Characteristic Sex (men) 52 Age at presentation (years), median (IQR) 59 (39–76) Age at presentation (years), range 16–93 Clinical features at presentation Best‐corrected visual acuity ≥ 6/12 62 Intra‐ocular pressure (mmHg), mean (SD) 15.4 (5.9) Rash 92 Pain 63 Conjunctivitis 62 Lid swelling 53 Skin erythema 41 Anterior uveitis 26 Keratitis 20 Other* 6 Late complications 19 Uveitis 11 Keratitis 5 Other† 3 IQR = interquartile range; SD = standard deviation. * Raised intra‐ocular pressure, retinitis/choroiditis, optic neuritis, cranial nerve palsy. † Neuralgia, elevated intra‐ocular pressure.

Rahul Chakrabarti · Grace George · Kristen Wells · Carmel Crock

Greater investment is needed to support eye health coordinators, community-based liaison officers, and family members and carers

Aryati Yashadhana · Ling Lee · Jessica Massie · Anthea Burnett

To the Editor: We thoroughly enjoyed the insightful review on erectile dysfunction by McMahon.1 We offer some observations, as most of the abnormalities described in erectile dysfunction are also associated with obstructive sleep apnoea (OSA). Fortunately, OSA can be reliably diagnosed in 80% of cases by bilateral, simultaneous, lateral, passive, anterosuperior, paramarginal distraction of a patient's upper eyelids.2 Finding lax (floppy) lids clearly has a positive association with OSA. Clinical examination of patients with lax eyelids — and in their extreme manifestation, floppy eyelid syndrome — can elucidate a patient's preferred sleeping laterality. Moreover, the presence of OSA can be imputed if the lid laxity is moderate to severe.2 We were concerned that there was no mention of the pathogenetic association of OSA with erectile dysfunction; it may be prudent to exclude OSA in patients diagnosed with erectile dysfunction. As management of floppy eyelid syndrome includes weight loss, it was gratifying to see McMahon emphasising lifestyle modification to reduce the impact of vascular risk factors. Similarly, upper eyelid laxity can also be improved with weight loss.3 This also benefits the OSA‐related complications of hypertension, diabetes, myocardial infarction, stroke and depression, and the ophthalmological complications of floppy eyelid syndrome. It was pleasing to note that McMahon referred to non‐arteritic ischaemic optic neuropathy. However, this condition occurs not only in the context of utilisation of phosphodiesterase type 5 inhibitors but also as a consequence of OSA.4 We suggest that clinicians carry out lid distraction to screen for OSA and assist in the diagnosis and management of erectile dysfunction.

Kriti Agnihotri · Eugene Ting · Ian C Francis

A 19th century explorer and a 20th century surveyor each suffered blinding ophthalmia during their outback travels and took the most unusual step of naming outback places after their afflictions

D Ashley R Watson

A previously well 6-year-old girl presented to her doctor with a mildly injected right eye and upper eyelid swelling

Jiyeon Kim · Jonathan G Ussher

A 77-year-old woman with a background of hypertension, diet-controlled type 2 diabetes and bilateral cataract surgery was referred by her GP to the emergency department

Stuart Campbell · Emma Hack · Babu Philip

A 30-year-old woman was admitted for pancreatitis

Anthony Yao · Bob Wang

New technologies and collaborative care are improving the quality of life of patients with glaucoma

Yu Xiang George Kong · Annie Gibbins · Anne Brooks

A 64-year-old woman was referred to the glaucoma clinic at a tertiary eye hospital with elevated intraocular pressures

Helen HL Chan · John F Salmon

A 12-year-old boy was at a family gathering when he threw a deodorant can on a barbecue with exposed flames

Varun Chandra · Lei Liu · Jonathan B Ruddle

Glaucoma management varies depending on the underlying causative mechanism, with options trending towards earlier surgical intervention for both open‐angle and angle closure glaucoma. While the increased acceptance of SLT and the introduction of MIGS devices have started to change the face of glaucoma management, IOP‐lowering eye drops remain the foundation of treatment. Adherence is an ongoing treatment limitation and future therapies are being designed to diminish this.

Jed Lusthaus · Ivan Goldberg

A 42-year-old man presented to our emergency department with sudden bilateral visual loss

Tanya Kowalski · Jitin Verma · Shaun L Greene · Jeremy Curtin

A previously healthy 12-year-old girl presented to a rural hospital with 10 days of intermittent fevers

Fumitaka Nonaka · Susan M Carden · Coen Butters · Christine Chen

A fit, active 80-year-old man presented to the emergency department with double vision

Sarah L Stevens · Daniel Schweitzer

A 62-year-old man with a history of bee allergy presented with severe eye pain one day after being stung in the eye by a bee

Andrew Olivo Payne · Elaine Chong

Numbers of violence-related orbital fractures and fractures requiring surgery are lower, saving an estimated $464 000

Ryan F Holmes · Thomas Lung · Gordian WO Fulde · Clare L Fraser