Background Deep learning offers considerable promise for medical diagnostics. We aimed to evaluate the diagnostic accuracy of deep learning algorithms versus health-care professionals in classifying diseases using medical imaging.Methods In this systematic review and meta-analysis, we searched Ovid-MEDLINE, Embase, Science Citation Index, and Conference Proceedings Citation Index for studies published from Jan 1, 2012, to June 6, 2019. Studies comparing the diagnostic performance of deep learning models and health-care professionals based on medical imaging, for any disease, were included. We excluded studies that used medical waveform data graphics material or investigated the accuracy of image segmentation rather than disease classification. We extracted binary diagnostic accuracy data and constructed contingency tables to derive the outcomes of interest: sensitivity and specificity. Studies undertaking an out-of-sample external validation were included in a meta-analysis, using a unified hierarchical model. This study is registered with PROSPERO, CRD42018091176.Findings Our search identified 31 587 studies, of which 82 (describing 147 patient cohorts) were included. 69 studies provided enough data to construct contingency tables, enabling calculation of test accuracy, with sensitivity ranging from 9•7% to 100•0% (mean 79•1%, SD 0•2) and specificity ranging from 38•9% to 100•0% (mean 88•3%, SD 0•1). An out-of-sample external validation was done in 25 studies, of which 14 made the comparison between deep learning models and health-care professionals in the same sample. Comparison of the performance between health-care professionals in these 14 studies, when restricting the analysis to the contingency table for each study reporting the highest accuracy, found a pooled sensitivity of 87•0% (95% CI 83•0-90•2) for deep learning models and 86•4% (79•9-91•0) for health-care professionals, and a pooled specificity of 92•5% (95% CI 85•1-96•4) for deep learning models and 90•5% (80•6-95•7) for health-care professionals.Interpretation Our review found the diagnostic performance of deep learning models to be equivalent to that of health-care professionals. However, a major finding of the review is that few studies presented externally validated results or compared the performance of deep learning models and health-care professionals using the same sample. Additionally, poor reporting is prevalent in deep learning studies, which limits reliable interpretation of the reported diagnostic accuracy. New reporting standards that address specific challenges of deep learning could improve future studies, enabling greater confidence in the results of future evaluations of this promising technology.

Background/aimsTo measure health-related quality of life (HRQOL) in patients with uveitis using time trade-off (TTO) and standard gamble (SG) methods of direct utility analysis.MethodsConsecutive patients attending a tertiary referral uveitis clinic were administered standardised, interview-delivered TTO and SG questionnaires and completed the European Quality of Life Five Dimensions Five Level (EQ5D-5L) questionnaire. Clinical data recorded included best-corrected visual acuity, uveitis anatomical and clinical classifications, duration since diagnosis, disease activity, current medication and any ocular or systemic comorbidities.ResultsTwo hundred patients with uveitis (124 female, 76 male, median age 54 years) were included. Overall mean TTO utility was 0.831 (95% CI 0.802 to 0.860); mean SG utility was 0.868 (95% CI 0.840 to 0.896) and mean EQ5D-5L utility was 0.742 (95% CI 0.702 to 0.782). There was a negative correlation between visual acuity and mean HRQOL (6/12 or better: TTO 0.86, SG 0.893; 6/15–6/60: TTO 0.662, SG 0.742; worse than 6/60: TTO 0.608, SG 0.712). Poor vision in the better- seeing eye (p=0.004), bilateral disease (p=0.047) and concurrent glaucomatous optic neuropathy (p=0.005) were predictors of poor TTO HRQOL. No correlation was found between HRQOL and duration of diagnosis, a flare of uveitis or being on systemic therapy. Patients with uveitis with poor vision have a TTO value worse than patients with end-stage renal failure on haemodialysis or those with AIDS.ConclusionLoss of vision resulting from uveitis is associated with reduced HRQOL. The TTO and SG utility values appear directly dependent on the degree of vision loss and not on the duration of disease or systemic medications.

Mucous Membrane Pemphigoid is an orphan multi-system autoimmune scarring disease involving mucosal sites, including the ocular surface (OcMMP) and gut. Loss of tolerance to epithelial basement membrane proteins and generation of autoreactive T cell and/or autoantibodies are central to the disease process. The gut microbiome plays a critical role in the development of the immune system. Alteration in the gut microbiome (gut dysbiosis) affects the generation of autoreactive T cells and B cell autoantibody repertoire in several autoimmune conditions. This study examines the relationship between gut microbiome diversity and ocular inflammation in patients with OcMMP by comparing OcMMP gut microbiome profiles with healthy controls. DNA was extracted from faecal samples (49 OcMMP patients, 40 healthy controls), amplified for the V4 region of the 16S rRNA gene and sequenced using Illumina Miseq platform. Sequencing reads were processed using the bioinformatics pipeline available in the mothur v.1.44.1 software. After adjusting for participant factors in the multivariable model (age, gender, BMI, diet, proton pump inhibitor use), OcMMP cohort was found to be associated with lower number of operational taxonomic units (OTUs) and Shannon Diversity Index when compared to healthy controls. Within the OcMMP cohort, the number of OTUs were found to be significantly correlated with both the bulbar conjunctival inflammation score (p=0.03) and the current use of systemic immunotherapy (p=0.02). The linear discriminant analysis effect size scores indicated that Streptococcus and Lachnoclostridium were enriched in OcMMP patients whilst Oxalobacter, Clostridia uncultured genus-level group (UCG) 014, Christensenellaceae R-7 group and butyrate-producing bacteria such as Ruminococcus, Lachnospiraceae, Coprococcus, Roseburia, Oscillospiraceae UCG 003, 005, NK4A214 group were enriched in healthy controls (Log10 LDA score < 2, FDR-adjusted p <0.05). In conclusion, OcMMP patients have gut dysbiosis correlating with bulbar conjunctival inflammation and the use of systemic immunotherapies. This provides a framework for future longitudinal deep phenotyping studies on the role of the gut microbiome in the pathogenesis of OcMMP.

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Background: Plasma fibroblast skin tightening treatment is a relatively novel and growing minimally invasive aesthetic skin procedure. The treatment claims to rejuvenate skin by improving facial lines, wrinkles and skin pigmentation associated with photo-ageing. The skin is often anaesthetised prior to the procedure with topical creams such as EMLA (Eutectic mixture of local anaesthetics). We present the first case of bilateral chemical eye injury following plasma fibroblast skin tightening treatment secondary to EMLA cream. EMLA cream was inadvertently administered to both eyes in preparation for the treatment. Case presentation: A patient was referred from the emergency department to a tertiary ophthalmology centre with bilateral exquisite eye pain, inability to open the eyes, photosensitivity and reduced vision. She underwent cosmetic plasma fibroblast skin tightening treatment at her local salon four hours earlier. She was found to have bilateral alkali chemical eye injuries with significant diffuse corneal epithelial loss. The injury was thought to be caused by inadvertent ocular exposure to EMLA cream, which was used in preparation for the plasma fibroblast skin tightening treatment. She was treated with topical antibiotics and achieved satisfactory recovery. Conclusion: This case report highlights a possible complication following plasma fibroblast skin tightening treatment. We lay emphasis on the importance identifying chemical injury and recommend that medication attention should be sought if there is any concern.