Trends in the Prevalence of Common Retinal and Optic Nerve Diseases in China: An Artificial Intelligence Based National Screening.

Purpose: Retinal and optic nerve diseases have become the primary cause of irreversible vision loss and blindness. However, there is still a lack of thorough evaluation regarding their prevalence in China. Methods: This artificial intelligence-based national screening study applied a previously developed deep learning algorithm, named the Retinal Artificial Intelligence Diagnosis System (RAIDS). De-identified personal medical records from January 2019 to December 2021 were extracted from 65 examination centers in 19 provinces of China. Crude prevalence and age-sex-adjusted prevalence were calculated by mapping to the standard population in the seventh national census. Results: In 2021, adjusted referral possible glaucoma (63.29, 95% confidence interval [CI] = 57.12-68.90 cases per 1000), epiretinal macular membrane (21.84, 95% CI = 15.64-29.22), age-related macular degeneration (13.93, 95% CI = 11.09-17.17), and diabetic retinopathy (11.33, 95% CI = 8.89-13.77) ranked the highest among 10 diseases. Female participants had significantly higher adjusted prevalence of pathologic myopia, yet a lower adjusted prevalence of diabetic retinopathy, referral possible glaucoma, and hypertensive retinopathy than male participants. From 2019 to 2021, the adjusted prevalence of retinal vein occlusion (0.99, 95% CI = 0.73-1.26 to 1.88, 95% CI = 1.42-2.44), macular hole (0.59, 95% CI = 0.41-0.82 to 1.12, 95% CI = 0.76-1.51), and hypertensive retinopathy (0.53, 95% CI = 0.40-0.67 to 0.77, 95% CI = 0.60-0.95) significantly increased. The prevalence of diabetic retinopathy in participants under 50 years old significant increased. Conclusions: Retinal and optic nerve diseases are an important public health concern in China. Further well-conceived epidemiological studies are required to validate the observed increased prevalence of diabetic retinopathy, hypertensive retinopathy, retinal vein occlusion, and macular hole nationwide. Translational Relevance: This artificial intelligence system can be a potential tool to monitor the prevalence of major retinal and optic nerve diseases over a wide geographic area.

Vitamin D and myopia: a review.

Myopia is a worldwide public health problem of vision disorder caused by multiple factors, which has posed a huge socioeconomic burden, raising concerns about sight-threatening ocular complications. Vitamin D, as a kind of fat-soluble vitamin, related to time-spent-outdoors, has been considered by extensive studies to have potential relationship with myopia. We reviewed studies published in a decade which estimated the association of blood vitamin D status with myopia and summarized the universality and individuality of all research articles. Several research articles suggested the known environmental risk factors of myopia, including age, gender, ethnicity, education level, parental and school conditions, time-spent-outdoors, and sunlight exposure, and recent epidemiological studies demonstrate that increased vitamin D levels, by virtue of the extended outdoor time, may be an important modifiable factor and a protective effect that delay the progression of myopia in children and adolescents rather than in adults. The genetic studies have been conducted to get access to the evidence of gene polymorphism for explaining the association of serum vitamin D status and myopia, but the precise genetic interpretation of vitamin D and myopia remains unclear so far; on the other hand, the possible mechanisms are various like copolymerization mechanism, calcium homeostasis and imbalance of ciliary muscle function regulation, but nearly all of the investigators are inclined to remain skeptical. This article reviews the age-related epidemiological proofs, existent genetics correlations, possible underlying biological mechanisms and further values for the protective association between vitamin D and myopia, providing the possibility of prevention or postponement for myopia.

Predicting systemic diseases in fundus images: systematic review of setting, reporting, bias, and models' clinical availability in deep learning studies.

BACKGROUND: Analyzing fundus images with deep learning techniques is promising for screening systematic diseases. However, the quality of the rapidly increasing number of studies was variable and lacked systematic evaluation. OBJECTIVE: To systematically review all the articles that aimed to predict systemic parameters and conditions using fundus image and deep learning, assessing their performance, and providing suggestions that would enable translation into clinical practice. METHODS: Two major electronic databases (MEDLINE and EMBASE) were searched until August 22, 2023, with keywords 'deep learning' and 'fundus'. Studies using deep learning and fundus images to predict systematic parameters were included, and assessed in four aspects: study characteristics, transparent reporting, risk of bias, and clinical availability. Transparent reporting was assessed by the TRIPOD statement, while the risk of bias was assessed by PROBAST. RESULTS: 4969 articles were identified through systematic research. Thirty-one articles were included in the review. A variety of vascular and non-vascular diseases can be predicted by fundus images, including diabetes and related diseases (19%), sex (22%) and age (19%). Most of the studies focused on developed countries. The models' reporting was insufficient in determining sample size and missing data treatment according to the TRIPOD. Full access to datasets and code was also under-reported. 1/31(3.2%) study was classified as having a low risk of bias overall, whereas 30/31(96.8%) were classified as having a high risk of bias according to the PROBAST. 5/31(16.1%) of studies used prospective external validation cohorts. Only two (6.4%) described the study's calibration. The number of publications by year increased significantly from 2018 to 2023. However, only two models (6.5%) were applied to the device, and no model has been applied in clinical. CONCLUSION: Deep learning fundus images have shown great potential in predicting systematic conditions in clinical situations. Further work needs to be done to improve the methodology and clinical application.

Intraocular cetuximab: Safety and effect on axial elongation in young Guinea pigs with lens-induced myopization.

This study aimed to examine the intraocular tolerability of the epidermal growth factor receptor antibody cetuximab, when applied intravitreally, and its effect on axial elongation. Guinea pigs aged 2-3 weeks were subjected to bilateral plano glasses and bilateral lens-induced myopization (LIM) as a single procedure for group I (n = 8) and group II (n = 8), respectively. In the animals of group III (n = 8), group IV (n = 8), and group V (n = 8), the right eyes of the animals, in addition to LIM, received four weekly intravitreal injections of cetuximab (Erbitux®) in doses of 6.25 µg, 12.5 µg, and 25 µg, respectively. As controls, the left eyes, in addition to LIM, received corresponding intraocular injections of phosphate-buffered saline. The animals underwent regular ophthalmoscopic examinations and biometry for axial length measurements. With increasing doses of cetuximab, the inter-eye difference in axial elongation (at study end, left eyes minus right eyes) were significantly the smallest in group I (0.00 ± 0.02 mm) and group II (-0.01 ± 0.02 mm), they were larger in group III (0.04 ± 0.04 mm) and group IV (0.10 ± 0.03 mm), and they were the largest in group V (0.11 ± 0.01 mm). The inter-eye difference in axial elongation enlarged (P < 0.001) with the number of injections applied. Retinal thickness at the posterior pole (right eyes) was significantly thicker in group V than in group II (P < 0.01). The density of apoptotic cells (visualized by TUNEL-staining) did not vary significantly between any of the groups (all P > 0.05). The results suggest that intravitreal injections of cetuximab in young guinea pigs with LIM resulted in a reduction in axial elongation in a dose-dependent and number of treatment-dependent manner. Intraocular toxic effects, such as intraocular inflammation, retinal thinning, or an increased density of apoptotic cells in the retina, were not observed in association with the intravitreally applied cetuximab.

mTORC1 Signaling and Negative Lens-Induced Axial Elongation.

Purpose: The mechanism underlying axial elongation during myopia progression remains unknown. Epidermal growth factor receptor (EGFR) signaling is associated with axial elongation. We explored whether mammalian target of rapamycin complex 1 (mTORC1) signaling acts as the downstream pathway of EGFR and participates in negative lens-induced axial elongation (NLIAE). Methods: Three-week-old male pigmented guinea pigs underwent binocular NLIAE. (1) To investigate whether EGFR is the upstream regulator of mTORC1, an EGFR inhibitor (20 µg erlotinib) was intravitreally injected once a week for three weeks. (2) To assess the effect of mTORC1 inhibition on NLIAE, an mTORC1 inhibitor (2 µg, 10 µg, and 20 µg everolimus) was intravitreally injected once a week for three weeks. (3) To explore the long-term effect of mTORC1 overactivation on axial elongation, an mTORC1 agonist (4 µg MHY1485) was intravitreally injected once a week for three months. Biometric measurements included axial length and choroidal thickness were performed. Results: Compared with the guinea pigs without NLIAE, NLIAE was associated with activation of mTORC1 signaling, which was suppressed by intravitreal erlotinib injection. Intravitreally injected everolimus suppressed NLIAE-induced axial elongation, mTORC1 activation, choroidal thinning, and hypoxia-inducible factor-1α expression in the sclera. Immunofluorescence revealed that the retinal pigment epithelium was the primary location of mTORC1 activation during NLIAE. Combining NLIAE and MHY1485 intravitreal injections significantly promoted axial elongation, choroidal thinning, and peripapillary choroidal atrophy. Conclusions: The mTORC1 signaling is associated with increased axial elongation, as in NLIAE, raising the possibility of inhibiting mTORC1 as a novel treatment for slowing myopia progression.

Rapid Detection of SARS-CoV-2 RNA Using Reverse Transcription Recombinase Polymerase Amplification (RT-RPA) with Lateral Flow for N-Protein Gene and Variant-Specific Deletion-Insertion Mutation in S-Protein Gene.

Rapid molecular testing for severe acute respiratory coronavirus 2 (SARS-CoV-2) variants may contribute to the development of public health measures, particularly in resource-limited areas. Reverse transcription recombinase polymerase amplification using a lateral flow assay (RT-RPA-LF) allows rapid RNA detection without thermal cyclers. In this study, we developed two assays to detect SARS-CoV-2 nucleocapsid (N) gene and Omicron BA.1 spike (S) gene-specific deletion-insertion mutations (del211/ins214). Both tests had a detection limit of 10 copies/µL in vitro and the detection time was approximately 35 min from incubation to detection. The sensitivities of SARS-CoV-2 (N) RT-RPA-LF by viral load categories were 100% for clinical samples with high (>9015.7 copies/µL, cycle quantification (Cq): < 25) and moderate (385.5-9015.7 copies/µL, Cq: 25-29.9) viral load, 83.3% for low (16.5-385.5 copies/µL, Cq: 30-34.9), and 14.3% for very low (<16.5 copies/µL, Cq: 35-40). The sensitivities of the Omicron BA.1 (S) RT-RPA-LF were 94.9%, 78%, 23.8%, and 0%, respectively, and the specificity against non-BA.1 SARS-CoV-2-positive samples was 96%. The assays seemed more sensitive than rapid antigen detection in moderate viral load samples. Although implementation in resource-limited settings requires additional improvements, deletion-insertion mutations were successfully detected by the RT-RPA-LF technique.

Automatic retinoblastoma screening and surveillance using deep learning.

BACKGROUND: Retinoblastoma is the most common intraocular malignancy in childhood. With the advanced management strategy, the globe salvage and overall survival have significantly improved, which proposes subsequent challenges regarding long-term surveillance and offspring screening. This study aimed to apply a deep learning algorithm to reduce the burden of follow-up and offspring screening. METHODS: This cohort study includes retinoblastoma patients who visited Beijing Tongren Hospital from March 2018 to January 2022 for deep learning algorism development. Clinical-suspected and treated retinoblastoma patients from February 2022 to June 2022 were prospectively collected for prospective validation. Images from the posterior pole and peripheral retina were collected, and reference standards were made according to the consensus of the multidisciplinary management team. A deep learning algorithm was trained to identify "normal fundus", "stable retinoblastoma" in which specific treatment is not required, and "active retinoblastoma" in which specific treatment is required. The performance of each classifier included sensitivity, specificity, accuracy, and cost-utility. RESULTS: A total of 36,623 images were included for developing the Deep Learning Assistant for Retinoblastoma Monitoring (DLA-RB) algorithm. In internal fivefold cross-validation, DLA-RB achieved an area under curve (AUC) of 0.998 (95% confidence interval [CI] 0.986-1.000) in distinguishing normal fundus and active retinoblastoma, and 0.940 (95% CI 0.851-0.996) in distinguishing stable and active retinoblastoma. From February 2022 to June 2022, 139 eyes of 103 patients were prospectively collected. In identifying active retinoblastoma tumours from all clinical-suspected patients and active retinoblastoma from all treated retinoblastoma patients, the AUC of DLA-RB reached 0.991 (95% CI 0.970-1.000), and 0.962 (95% CI 0.915-1.000), respectively. The combination between ophthalmologists and DLA-RB significantly improved the accuracy of competent ophthalmologists and residents regarding both binary tasks. Cost-utility analysis revealed DLA-RB-based diagnosis mode is cost-effective in both retinoblastoma diagnosis and active retinoblastoma identification. CONCLUSIONS: DLA-RB achieved high accuracy and sensitivity in identifying active retinoblastoma from the normal and stable retinoblastoma fundus. It can be used to surveil the activity of retinoblastoma during follow-up and screen high-risk offspring. Compared with referral procedures to ophthalmologic centres, DLA-RB-based screening and surveillance is cost-effective and can be incorporated within telemedicine programs. CLINICAL TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov (NCT05308043).

Intravitreal Short-Hairpin RNA Attenuated Adeno-Associated Virus-Induced Knockdown of Amphiregulin and Axial Elongation in Experimental Myopia.

Background: Epidermal growth factor (EGF) and its family members have been reported to be involved in myopic axial elongation. We examined whether short hairpin RNA attenuated adeno-associated virus (shRNA-AAV)-induced knockdown of amphiregulin, an EGF family member, has an influence on axial elongation. Methods: Three-week-old pigmented guinea pigs underwent lens-induced myopization (LIM) without additional intervention (LIM group; n = 10 animals) or additionally received into their right eyes at baseline an intravitreal injection of scramble shRNA-AAV (5 × 1010 vector genome [vg]) (LIM + Scr-shRNA group; n = 10) or of amphiregulin (AR)-shRNA-AAV (5 × 1010 vg/5 µL) (LIM + AR-shRNA-AAV group; n = 10), or they received an injection of AR-shRNA-AAV at baseline and three weekly amphiregulin injections (20 ng/5 µL) (LIM + AR-shRNA-AAV + AR group; n = 10). The left eyes received equivalent intravitreal injections of phosphate-buffered saline. Four weeks after baseline, the animals were sacrificed. Results: At study end, interocular axial length difference was higher (P < 0.001), choroid and retina were thicker (P < 0.05), and relative expression of amphiregulin and p-PI3K, p-p70S6K, and p-ERK1/2 was lower (P < 0.05) in the LIM + AR-shRNA-AAV group than in any other group. The other groups did not differ significantly when compared with each other. In the LIM + AR-shRNA-AAV group, the interocular axial length difference increased with longer study duration. TUNEL assay did not reveal significant differences among all groups in retinal apoptotic cell density. In vitro retinal pigment epithelium cell proliferation and migration were the lowest (P < 0.05) in the LIM + AR-shRNA-AAV group, followed by the LIM + AR-shRNA-AAV + AR group. Conclusions: shRNA-AAV-induced knockdown of amphiregulin expression, in association with suppression of epidermal growth factor receptor signaling, attenuated axial elongation in guinea pigs with LIM. The finding supports the notion of EGF playing a role in axial elongation.

Development and validation of medical record-based logistic regression and machine learning models to diagnose diabetic retinopathy.

PURPOSES: Many factors were reported to be associated with diabetic retinopathy (DR); however, their contributions remained unclear. We aimed to evaluate the prognostic and diagnostic accuracy of logistic regression and three machine learning models based on various medical records. METHODS: This was a cross-sectional study. We investigated the prevalence and associations of DR among 757 participants aged 40 years or older in the 2005-2006 National Health and Nutrition Examination Survey (NHANES). We trained the models to predict if the participants had DR with 15 predictor variables. Area under the receiver operating characteristic (AUROC) and mean squared error (MSE) of each algorithm were compared in the external validation dataset using a replicate cohort from NHANES 2007-2008. RESULTS: Among the 757 participants, 53 (7.00%) subjects had DR, the mean (standard deviation, SD) age was 57.7 (13.04), and 78.0% were male (n = 42). Logistic regression revealed that female gender (OR = 4.130, 95% CI: 1.820-9.380; P < 0.05), HbA1c (OR = 1.665, 95% CI: 1.197-2.317; P < 0.05), serum creatine level (OR = 2.952, 95% CI: 1.274-6.851; P < 0.05), and eGFR level (OR = 1.009, 95% CI: 1.000-1.014, P < 0.05) increased the risk of DR. The average performance obtained from internal validation was similar in all models (AUROC ≥ 0.945), and k-nearest neighbors (KNN) had the highest value with an AUROC of 0.984. In external validation, they remained robust or with modest reductions in discrimination with AUROC still ≥ 0.902, and KNN also performed the best with an AUROC of 0.982. Both logistic regression and machine learning models had good performance in the clinical diagnosis of DR. CONCLUSIONS: This study highlights the utility of comparing traditional logistic regression to machine learning models. We found that logistic regression performed as well as optimized machine learning methods when classifying DR patients.

Prophylactic interventions for preventing macular edema after cataract surgery in patients with diabetes: A Bayesian network meta-analysis of randomized controlled trials.

Background: Diabetes significantly increases the risk of postoperative macular edema (PME) after cataract surgery, leading to potential worst post-operative outcomes. This study aims to compare the effect of different prophylactic interventions in improving postoperative anatomic and visual acuity outcomes of diabetes patients who underwent cataract surgery. Methods: We searched MEDLINE, Embase, Web of Science databases from inception until February 2nd, 2022, for studies including studies reporting PME events and/or best-corrected visual acuity (BCVA) outcomes. Random-effects Bayesian network meta-analysis was performed to compare the efficiency of intravitreal anti-vascular endothelial growth factor injections (anti-VEGF), nonsteroidal anti-inflammatory drugs (NSAIDs) and topical steroids eye drop at 1 week, 1 month, 3 months, 6 months after cataract surgery. Findings: The total of 2566 participants from 17 randomized controlled trials were included in the network meta-analysis, with moderate risk of bias and no evidence of publication of bias. Compared to placebo/steroid eye drop alone, patients received additional topical NSAIDs or intravitreal anti-VEGF injections had lower risk of PME at 1 month (NSAIDs: OR=0·221, 95% Confidence interval [CI], 0·044-0·755, I2 =0·0%, 5 studies; anti-VEGF: OR=0·151, 95%CI, 0·037-0·413, I2 =0·0%, 5 studies) and 3 month (NSAIDs: OR=0·370, 95%CI, 0·140-0·875, I2 =0·0%, 8 studies; anti-VEGF: OR=0·203, 95%CI, 0·101-0·353, I2 =0·0%, 4 studies) after cataract surgery. Further, additional anti-VEGF exhibited better BCVA outcome at 1 month (mean difference of LogMAR: -0·083, 95%CI, -0·17 to -0·014, I2 =62·0%, 5 studies), and 3 months (mean difference of LogMAR: -0·061, 95%CI, -0·11 to -0·011, I2 =0·0%, 5 studies) after cataract surgery. Such additional benefits did not reach statistic significant at 6 months after surgery. Interpretation: Our data suggests that compared to placebo/steroid eye drop alone, additional prophylactic anti-VEGF intervention could be considered for preventing the occurrence of PME after cataract surgery in patients with diabetes. Funding: Research and Development of Special (2020-1-2052); Science & Technology Project of Beijing Municipal Science & Technology Commission (Z201100005520045, Z181100001818003).