We report two cases of endothelial corneal allograft rejection following immunisation with SARS-CoV-2 messenger RNA (mRNA) vaccine BNT162b2 and describe the implications for management of transplant ...recipients postvaccination for COVID-19.
A 66-year-old woman with Fuchs endothelial corneal dystrophy (FECD) and a unilateral Descemet's membrane endothelial keratoplasty (DMEK) transplant received COVID-19 mRNA vaccine BNT162b2 14 days post-transplant. Seven days later, she presented with symptoms and signs of endothelial graft rejection. An 83-year-old woman with bilateral DMEK transplants for FECD 3 and 6 years earlier developed simultaneous acute endothelial rejection in both eyes, 3 weeks post second dose of COVID-19 mRNA vaccine BNT162b2. Rejection in both cases was treated successfully with topical corticosteroids.
We believe this is the first report of temporal association between corneal transplant rejection following immunisation against COVID-19 and the first report of DMEK rejection following any immunisation. We hypothesise that the allogeneic response may have been initiated by the host antibody response following vaccination. Clinicians and patients should be aware of the potential of corneal graft rejection associated with vaccine administration and may wish to consider vaccination in advance of planned non-urgent keratoplasties. Patients should be counselled on the symptoms and signs that require urgent review to allow early treatment of any confirmed rejection episode.
The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health ...supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a “new normal”, the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions.
Coronavirus disease 19 (COVID-19) has been described to potentially be complicated by ocular involvement. However, scant information is available regarding severe acute respiratory ...syndrome-coronavirus-2 (SARS-CoV-2) and ocular structures tropism. We conducted a systematic review of articles referenced in PubMed, Cochrane Library, Web of Science and Chinese Clinical Trial Register (ChiCTR) from December 20, 2019 to April 6, 2020, providing information on the presence of SARS-CoV-2 in cornea, conjunctiva, lacrimal sac, and tears. We excluded ongoing clinical studies as for unobtainable conclusive results. Of 2422 articles, 11 met the inclusion criteria for analysis and were included in the study. None of the studies were multinational. Among the 11 selected papers there were three original articles, one review, four letters, two editorials, and one correspondence letter. Globally, 252 SARS-CoV-2 infected patients were included in our review. The prevalence of ocular conjunctivitis complicating the course of COVID-19 was demonstrated to be as high as 32% in one study only. Globally, three patients had conjunctivitis with a positive tear-PCR, 8 patients had positive tear-PCR in the absence of conjunctivitis, and 14 had conjunctivitis with negative tear-PCR. The majority of the available data regarding SARS-CoV-2 colonization of ocular and periocular tissues and secretions have to be considered controversial. However, it cannot be excluded that SARS-CoV-2 could both infect the eye and the surrounding structures. SARS-CoV-2 may use ocular structure as an additional transmission route, as demonstrated by the COVID-19 patients' conjunctival secretion and tears positivity to reverse transcriptase-PCR SARS-CoV-2-RNA assay.
To develop and validate a multimodal artificial intelligence algorithm, FusionNet, using the pattern deviation probability plots from visual field (VF) reports and circular peripapillary OCT scans to ...detect glaucomatous optic neuropathy (GON).
Cross-sectional study.
Two thousand four hundred sixty-three pairs of VF and OCT images from 1083 patients.
FusionNet based on bimodal input of VF and OCT paired data was developed to detect GON. Visual field data were collected using the Humphrey Field Analyzer (HFA). OCT images were collected from 3 types of devices (DRI-OCT, Cirrus OCT, and Spectralis). Two thousand four hundred sixty-three pairs of VF and OCT images were divided into 4 datasets: 1567 for training (HFA and DRI-OCT), 441 for primary validation (HFA and DRI-OCT), 255 for the internal test (HFA and Cirrus OCT), and 200 for the external test set (HFA and Spectralis). GON was defined as retinal nerve fiber layer thinning with corresponding VF defects.
Diagnostic performance of FusionNet compared with that of VFNet (with VF data as input) and OCTNet (with OCT data as input).
FusionNet achieved an area under the receiver operating characteristic curve (AUC) of 0.950 (0.931-0.968) and outperformed VFNet (AUC, 0.868 95% confidence interval (CI), 0.834-0.902), OCTNet (AUC, 0.809 95% CI, 0.768-0.850), and 2 glaucoma specialists (glaucoma specialist 1: AUC, 0.882 95% CI, 0.847-0.917; glaucoma specialist 2: AUC, 0.883 95% CI, 0.849-0.918) in the primary validation set. In the internal and external test sets, the performances of FusionNet were also superior to VFNet and OCTNet (FusionNet vs VFNet vs OCTNet: internal test set 0.917 vs 0.854 vs 0.811; external test set 0.873 vs 0.772 vs 0.785). No significant difference was found between the 2 glaucoma specialists and FusionNet in the internal and external test sets, except for glaucoma specialist 2 (AUC, 0.858 95% CI, 0.805-0.912) in the internal test set.
FusionNet, developed using paired VF and OCT data, demonstrated superior performance to both VFNet and OCTNet in detecting GON, suggesting that multimodal machine learning models are valuable in detecting GON.
Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains ...unsatisfactory. Our study aimed to train a clinically applicable DLS for fundus diseases using data derived from the real world, and externally test the model using fundus photographs collected prospectively from the settings in which the model would most likely be adopted.
In this national real-world evidence study, we trained a DLS, the Comprehensive AI Retinal Expert (CARE) system, to identify the 14 most common retinal abnormalities using 207 228 colour fundus photographs derived from 16 clinical settings with different disease distributions. CARE was internally validated using 21 867 photographs and externally tested using 18 136 photographs prospectively collected from 35 real-world settings across China where CARE might be adopted, including eight tertiary hospitals, six community hospitals, and 21 physical examination centres. The performance of CARE was further compared with that of 16 ophthalmologists and tested using datasets with non-Chinese ethnicities and previously unused camera types. This study was registered with ClinicalTrials.gov, NCT04213430, and is currently closed.
The area under the receiver operating characteristic curve (AUC) in the internal validation set was 0·955 (SD 0·046). AUC values in the external test set were 0·965 (0·035) in tertiary hospitals, 0·983 (0·031) in community hospitals, and 0·953 (0·042) in physical examination centres. The performance of CARE was similar to that of ophthalmologists. Large variations in sensitivity were observed among the ophthalmologists in different regions and with varying experience. The system retained strong identification performance when tested using the non-Chinese dataset (AUC 0·960, 95% CI 0·957–0·964 in referable diabetic retinopathy).
Our DLS (CARE) showed satisfactory performance for screening multiple retinal abnormalities in real-world settings using prospectively collected fundus photographs, and so could allow the system to be implemented and adopted for clinical care.
This study was funded by the National Key R&D Programme of China, the Science and Technology Planning Projects of Guangdong Province, the National Natural Science Foundation of China, the Natural Science Foundation of Guangdong Province, and the Fundamental Research Funds for the Central Universities.
For the Chinese translation of the abstract see Supplementary Materials section.
Bacterial keratitis is a common corneal infection that is treated with topical antimicrobials. By the time of presentation there may already be severe visual loss from corneal ulceration and opacity, ...which may persist despite treatment. There are significant differences in the associated risk factors and the bacterial isolates between high income and low- or middle-income countries, so that general management guidelines may not be appropriate. Although the diagnosis of bacterial keratitis may seem intuitive there are multiple uncertainties about the criteria that are used, which impacts the interpretation of investigations and recruitment to clinical studies. Importantly, the concept that bacterial keratitis can only be confirmed by culture ignores the approximately 50% of cases clinically consistent with bacterial keratitis in which investigations are negative. The aetiology of these culture-negative cases is unknown. Currently, the estimation of bacterial susceptibility to antimicrobials is based on data from systemic administration and achievable serum or tissue concentrations, rather than relevant corneal concentrations and biological activity in the cornea. The provision to the clinician of minimum inhibitory concentrations of the antimicrobials for the isolated bacteria would be an important step forward. An increase in the prevalence of antimicrobial resistance is a concern, but the effect this has on disease outcomes is yet unclear. Virulence factors are not routinely assessed although they may affect the pathogenicity of bacteria within species and affect outcomes. New technologies have been developed to detect and kill bacteria, and their application to bacterial keratitis is discussed. In this review we present the multiple areas of clinical uncertainty that hamper research and the clinical management of bacterial keratitis, and we address some of the assumptions and dogma that have become established in the literature.
•There is no agreement on the criteria that should define bacterial keratitis.•The role of investigation is unclear, particularly how this affects outcomes.•A diagnostic rule establishes how to interpret isolates whether identified from culture or metagenomics.•New technologies for investigation should enable personalisation of treatment.•Non-antibiotic therapies are being introduced encompassing phage and anti-virulence compounds.
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