Updated Efficacy and Safety of Lorlatinib in a Phase 2 Study in Chinese Patients With Previously Treated Advanced ALK-Positive Non-small Cell Lung Cancer.

OBJECTIVES: Lorlatinib, a brain-penetrant, third-generation anaplastic lymphoma kinase (ALK) inhibitor, demonstrated robust overall and intracranial antitumor activity in patients with advanced ALK-positive non-small cell lung cancer (NSCLC) previously treated with an ALK inhibitor in a global phase 1/2 study (NCT01970865) and a multicenter phase 2 study conducted in China (NCT03909971). We report updated 3-year follow-up data from the phase 2 study. MATERIALS AND METHODS: Chinese patients with locally advanced or metastatic ALK-positive NSCLC that progressed after crizotinib as the only prior ALK inhibitor (cohort 1) or after 1 non-crizotinib ALK inhibitor (cohort 2), were enrolled in the study. All patients received lorlatinib 100 mg once daily. RESULTS: At data cutoff, of 109 enrolled patients, the median duration of follow-up for progression-free survival (PFS) was 35.8 months in cohort 1 (n = 67) and 33.1 months in cohort 2 (n = 42). Median PFS (95% CI) per independent central review was 26.3 months (16.6-35.9) and 5.6 months (2.9-12.4), respectively. The median duration of follow-up for overall survival (OS) was 36.4 months and 37.5 months, respectively. Median OS (95% CI) was not reached (NR; NR-NR) and 21.9 months (11.9-NR), respectively. Median intracranial time to progression (95% CI) was NR (NR-NR) and NR (9.7 months-NR), respectively. No new safety signals emerged with long-term treatment. CONCLUSION: The long-term data confirm robust overall and intracranial clinical activity of lorlatinib, with no new safety signals emerging. These results support using lorlatinib in Chinese patients with previously treated ALK-positive NSCLC with or without brain metastases. CLINICALTRIALS: gov NCT03909971.

Deep learning system for screening AIDS-related cytomegalovirus retinitis with ultra-wide-field fundus images.

Background: Ophthalmological screening for cytomegalovirus retinitis (CMVR) for HIV/AIDS patients is important to prevent lifelong blindness. Previous studies have shown good properties of automated CMVR screening using digital fundus images. However, the application of a deep learning (DL) system to CMVR with ultra-wide-field (UWF) fundus images has not been studied, and the feasibility and efficiency of this method are uncertain. Methods: In this study, we developed, internally validated, externally validated, and prospectively validated a DL system to detect AIDS-related from UWF fundus images from different clinical datasets. We independently used the InceptionResnetV2 network to develop and internally validate a DL system for identifying active CMVR, inactive CMVR, and non-CMVR in 6960 UWF fundus images from 862 AIDS patients and validated the system in a prospective and an external validation data set using the area under the curve (AUC), accuracy, sensitivity, and specificity. A heat map identified the most important area (lesions) used by the DL system for differentiating CMVR. Results: The DL system showed AUCs of 0.945 (95 % confidence interval [CI]: 0.929, 0.962), 0.964 (95 % CI: 0.870, 0.999) and 0.968 (95 % CI: 0.860, 1.000) for detecting active CMVR from non-CMVR and 0.923 (95 % CI: 0.908, 0.938), 0.902 (0.857, 0.948) and 0.884 (0.851, 0.917) for detecting active CMVR from non-CMVR in the internal cross-validation, external validation, and prospective validation, respectively. Deep learning performed promisingly in screening CMVR. It also showed the ability to differentiate active CMVR from non-CMVR and inactive CMVR as well as to identify active CMVR and inactive CMVR from non-CMVR (all AUCs in the three independent data sets >0.900). The heat maps successfully highlighted lesion locations. Conclusions: Our UWF fundus image-based DL system showed reliable performance for screening AIDS-related CMVR showing its potential for screening CMVR in HIV/AIDS patients, especially in the absence of ophthalmic resources.

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.

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 schwannoma: case series of 28 patients and literature review.

PURPOSE: Intraocular schwannoma is a rare tumour, which is often misdiagnosed. We presented the demographics and clinical characteristics of patients with intraocular schwannoma. METHODS: Retrospective case series were collected between May 2005 and July 2021 in Beijing Tongren Hospital. RESULTS: A total of 28 patients were diagnosed with intraocular schwannoma on histopathological examination of surgical specimen. The median age was 39 years (range: 12-64). Fourteen patients were female and 14 were male. Among the all subjects, 21/28 patients (75.0%) presented as visual loss, and 3/28 patients (10.7%) had visual field loss. Intraocular schwannoma presented as nonpigmented mass in the ciliary body in 12/28 cases (42.9%), in the choroid in 9/28 cases (32.1%), and in ciliochoroid in 7/28 cases (25.0%). Intraocular schwannoma was often clinically misdiagnosed as uveal melanoma, which occurred in 16/28 patients (57.1%). Tumour excision with pars plana vitrectomy was performed for all included patients. Endoresection with lens removal was performed for tumours in the choroid, while transscleral resection was performed for tumours located in ciliary body or ciliochoroid. Increased light transmission was detected in 12/28 cases (42.9%). In the consecutive follow-up (median: 73 months, range: 7-193 months), no cases of recurrence or metastatic disease were detected. CONCLUSIONS: Intraocular schwannoma is a rare benign tumour. It usually presents as nonpigmented mass, which can easily be misdiagnosed as nonpigmented uveal melanoma.

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.

Gender differences in the burden of multiple sclerosis in China from 1990 to 2019 and its 25-year projection: An analysis of the Global Burden of Diseases Study.

Background and Aims: Multiple sclerosis (MS) is a crippling, chronic, gender-related disease that causes burdens to individuals and society. China has a considerable and increasing population of MS. We aim to analyze the gender disparities in the burden of MS in China and predict the trends. Methods: The study was conducted based on the Global Burden of Disease Study 2019. Data on incidence, prevalence, deaths, and disability-adjusted life years (DALYs) of MS in China from 1990 to 2019 was descriptively analyzed by year, gender, and age group. The Nordpred package in R (version 4.2.2) was used for age-period-cohort analysis to predict the all-ages numbers and age-standardized rates of incidence, prevalence, deaths, and DALYs in China from 2020 to 2044. Results: The number of prevalent cases of MS in 2019 reached 18,143.56 (95% uncertainty intervals [UI]: 13,997.71-22,658.60) in males and 24,427.11 (95% UI: 18,906.02-30,530.21) in females in China. The peak age of prevalence was shifted from 40-44 years in 1990 to 45-49 years in 2019 in females but remained unchanged in males. In contrast to the increased age-standardized prevalence rate, the age-standardized death rate (ASDR) and age-standardized DALYs rate showed downward trends, which were more significant in females. Different from the global, Chinese males showed lower prevalence but higher deaths and DALYs than females for age-standardized rates and numbers. In the next 25 years, the patient population will remain large and peak around 44,599.78 in 2025-2029. The ASDR, age-standardized DALYs rate, and DALYs number were expected to decrease. The improvements in deaths and DALYs will be more significant in females. Conclusion: Males with MS had a lower prevalence but higher deaths and DALYs than females in China. The ASDR and age-standardized DALYs rate have reduced over the past 30 years and were expected to continue decreasing, especially in females. The burden of MS will remain notable in the next 25 years.

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.

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.

Association between vitamin D and myopia in adolescents and young adults: Evidence of national cross-sectional study.

PURPOSE: Studies have indicated that the observed association between vitamin D and myopia was confounded by time spent outdoors. This study aimed to elucidate this association using a national cross-sectional dataset. METHODS: Participants with 12 to 25 years who participated in non-cycloplegic vision exam from National Health and Nutrition Examination Survey (NHANES) 2001 to 2008 were included in the present study. Myopia was defined as spherical equivalent of any eyes ≤ -0.5 diopters (D). RESULTS: 7,657 participants were included. The weighted proportion of emmetropes, mild myopia, moderate myopia, and high myopia were 45.5%, 39.1%, 11.6%, and 3.8%, respectively. After adjusting for age, gender, ethnicity, TV/computer usage, and stratified by education attainment, every 10 nmol/L increment of serum 25(OH)D concentration was associated with a reduced risk of myopia (odds ratio [OR] = 0.96, 95% confidence interval [95%CI] 0.93-0.99 for any myopia; OR = 0.96, 95%CI 0.93-1.00 for mild myopia; OR = 0.99, 95%CI 0.97-1.01 for moderate myopia; OR = 0.89, 95%CI 0.84-0.95 for high myopia). Serum 25(OH)D level was closely correlated with time spent outdoors. After categorizing time spent outdoors into quarters (low, low-medium, medium-high, and high), every 1 quarter increment of time spent outdoors was associated with 2.49 nmol/L higher serum 25(OH)D concentration. After adjusting for time spent outdoors, serum 25(OH)D level did not show significant association with myopia (OR = 1.01, 95%CI 0.94-1.06 for 10 nmol/L increment). CONCLUSIONS: The association between high serum vitamin D and reduced risk of myopia is confounded by longer time spent outdoors. Evidence from the present study does not support that there is a direct association between serum vitamin D level with myopia.

Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.

PURPOSE: Artificial intelligence (AI) can detect diabetic macular edema (DME) from optical coherence tomography (OCT) images. We aimed to evaluate the performance of deep learning neural networks in DME detection. METHODS: Embase, Pubmed, the Cochrane Library, and IEEE Xplore were searched up to August 14, 2021. We included studies using deep learning algorithms to detect DME from OCT images. Two reviewers extracted the data independently, and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was applied to assess the risk of bias. The study is reported according to Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA). RESULTS: Ninteen studies involving 41005 subjects were included. The pooled sensitivity and specificity were 96.0% (95% confidence interval (CI): 93.9% to 97.3%) and 99.3% (95% CI: 98.2% to 99.7%), respectively. Subgroup analyses found that data set selection, sample size of training set and the choice of OCT devices contributed to the heterogeneity (all P < 0.05). While there was no association between the diagnostic accuracy and transfer learning adoption or image management (all P > 0.05). CONCLUSIONS: Deep learning methods, particularly the convolutional neural networks (CNNs) could effectively detect clinically significant DME, which can provide referral suggestions to the patients.

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.

Visual impairment and major eye diseases in stroke: a national cross-sectional study.

OBJECTIVES: Major ocular diseases share common risk factors and pathogeneses with stroke. This study aimed to evaluate the relation between stroke and ocular diseases including visual impairment (VI). METHODS: The cross-sectional study investigated the prevalence and associations of VI and major eye diseases with stroke among 4570 participants in the 2005-2008 National Health and Nutrition Examination Survey (NHANES). The association of VI and major ocular diseases with stroke were estimated using univariate and multivariate logistic regression crude models and models adjusted for demographics and clinical factors. We also conducted stratified analyses by diabetes and hypertension status. RESULTS: VI was associated with stroke, and the odds ratios (ORs) for mild and moderate and severe visual impairment (MSVI) were 6.79 (95% confidence interval (CI): 2.44-18.88) and 9.46 (95% CI: 2.19-40.94) after adjusting for age and gender (all P < 0.05). Ocular disease was associated with stroke with OR reaching 5.54 (95% CI: 1.83-16.74), and the OR was 9.61 (95% CI: 3.05-30.23) for stroke patients suffering DR after adjusting for age and gender (all P < 0.05). After multivariable adjustment, the associations were limited to mild VI (OR = 10.00, 95% CI: 3.16-30.58), MSVI (OR = 8.57, 95% CI: 1.58-43.36), and any ocular disease (OR = 5.18, 95% CI: 1.46-18.42) (all P < 0.05). Significant associations between stroke and any ocular disease and DR were observed among diabetic participants, and significant relation between stroke and MSVI was found among hypertension patients. CONCLUSIONS: The sample of the US population demonstrates significant associations between VI and major ocular disease with stroke.

Screening for novel risk factors related to high myopia using machine learning.

BACKGROUND: High myopia-related complications have become a major cause of irreversible vision loss. Evaluating the association between potential factors and high myopia can provide insights into pathophysiologic mechanisms and further intervention targets for myopia progression. METHOD: Participants aged 12-25 years from National Health and Nutrition Examination Survey 2001-2006 were selected for the analysis. Myopia was defined as spherical equivalent (sum of spherical error and half of the cylindrical error) of any eyes ≤-0.5 diopters. High myopia was defined as the spherical equivalent of any eye ≤ - 5.00 diopters. Essential variables were selected by Random Forest algorithm and verified by multivariable logistic regression. RESULTS: A total of 7,033 participants and 74 potential factors, including demographic (4 factors), physical examination (6 factors), nutritional and serological (45 factors), immunological (9 variables), and past medical history factors (10 factors), were included into the analysis. Random Forest algorithm found that several anthropometric, nutritional, and serological factors were associated with high myopia. Combined with multivariable logistic regression, high levels of serum vitamin A was significantly associated with an increased prevalence of high myopia (adjusted odd ratio = 1.46 for 1 µmol/L increment, 95% confidence interval [CI] 1.01-2.10). Furthermore, we found that neither C-reactive protein nor asthma increased the risk and severity of myopia. CONCLUSION: High levels of serum vitamin A was seemingly associated with an increased prevalence of high myopia. This borderline significant association should be interpreted with caution because the potential increased type I error after the multiple testing. It still needs further investigation regarding the mechanism underlying this association. Neither C-reactive protein nor asthma increased the risk and severity of myopia.

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).

Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases.

Importance: The lack of experienced ophthalmologists limits the early diagnosis of retinal diseases. Artificial intelligence can be an efficient real-time way for screening retinal diseases. Objective: To develop and prospectively validate a deep learning (DL) algorithm that, based on ocular fundus images, recognizes numerous retinal diseases simultaneously in clinical practice. Design, Setting, and Participants: This multicenter, diagnostic study at 65 public medical screening centers and hospitals in 19 Chinese provinces included individuals attending annual routine medical examinations and participants of population-based and community-based studies. Exposures: Based on 120 002 ocular fundus photographs, the Retinal Artificial Intelligence Diagnosis System (RAIDS) was developed to identify 10 retinal diseases. RAIDS was validated in a prospective collected data set, and the performance between RAIDS and ophthalmologists was compared in the data sets of the population-based Beijing Eye Study and the community-based Kailuan Eye Study. Main Outcomes and Measures: The performance of each classifier included sensitivity, specificity, accuracy, F1 score, and Cohen κ score. Results: In the prospective validation data set of 208 758 images collected from 110 784 individuals (median [range] age, 42 [8-87] years; 115 443 [55.3%] female), RAIDS achieved a sensitivity of 89.8% (95% CI, 89.5%-90.1%) to detect any of 10 retinal diseases. RAIDS differentiated 10 retinal diseases with accuracies ranging from 95.3% to 99.9%, without marked differences between medical screening centers and geographical regions in China. Compared with retinal specialists, RAIDS achieved a higher sensitivity for detection of any retinal abnormality (RAIDS, 91.7% [95% CI, 90.6%-92.8%]; certified ophthalmologists, 83.7% [95% CI, 82.1%-85.1%]; junior retinal specialists, 86.4% [95% CI, 84.9%-87.7%]; and senior retinal specialists, 88.5% [95% CI, 87.1%-89.8%]). RAIDS reached a superior or similar diagnostic sensitivity compared with senior retinal specialists in the detection of 7 of 10 retinal diseases (ie, referral diabetic retinopathy, referral possible glaucoma, macular hole, epiretinal macular membrane, hypertensive retinopathy, myelinated fibers, and retinitis pigmentosa). It achieved a performance comparable with the performance by certified ophthalmologists in 2 diseases (ie, age-related macular degeneration and retinal vein occlusion). Compared with ophthalmologists, RAIDS needed 96% to 97% less time for the image assessment. Conclusions and Relevance: In this diagnostic study, the DL system was associated with accurately distinguishing 10 retinal diseases in real time. This technology may help overcome the lack of experienced ophthalmologists in underdeveloped areas.

Circulating MicroRNAs as Quantitative Biomarkers for Diagnosis and Prognosis of Uveal Melanoma.

For uveal melanoma (UM) patients, it is significant to establish diagnosis and prognosis evaluation systems through imaging techniques. However, imaging examinations are short of quantitative biomarkers and it is difficult to finish early diagnosis of UM. In order to discover new molecular biomarkers for the diagnosis and prognostic evaluation of UM, six circulating miRNAs (mir-132-3p, mir-21-5p, mir-34a-5p, mir-126-3p, mir-199a-3p, mir-214-3p) were chosen as candidates for independent validation. Validation of these miRNAs was performed in a cohort of 20 patients, including 10 spindle-shaped melanoma and 10 epithelioid cell melanoma, and 10 healthy donors. Then 5 patients with metastatic UM were included to validate the performance of miRNAs in advanced UM. Serum levels of miRNAs were determined using quantitative real-time PCR. We confirmed significantly higher levels of three miRNAs in serum of UM patients in comparison to healthy controls, and miR-199a-3p had the best performance (p < 0.0001; AUC = 0.985). MiR-214-3p and miR-21-5p were significantly upregulated in serum of epithelioid cell melanoma patients compared to spindle-shaped melanoma patients and miR-132-3p and, conversely, were significantly downregulated in serum of epithelioid cell melanoma patients. MiR-21-5p shows their best performance (p < 0.0001; AUC = 0.980). Both miR-199a-3p and miR-21-5p showed great performance in advanced UM. Significantly higher levels of miR-21-5p (p < 0.001) were found in serum of metastatic UM patients compared to patients with localized spindle-shaped melanoma, and significantly higher levels of miR-199a-3p (p < 0.001) were detected in serum of metastatic UM patients compared to healthy controls. Our preliminary data indicate promising diagnostic utility of circulating miR-199a-3p and promising prognostic utility of circulating miR-21-5p in both early and advanced UM patients.

Epiregulin, epigen and betacellulin antibodies and axial elongation in young guinea pigs with lens-induced myopization.

BACKGROUND: To examine an effect of intravitreally applied antibodies against epidermal growth factor family members, namely epiregulin, epigen and betacellulin, on ocular axial elongation. METHODS: The experimental study included 30 guinea pigs (age:3-4 weeks) which underwent bilateral lens-induced myopization and received three intraocular injections of 20 µg of epiregulin antibody, epigen antibody and betacellulin antibody in weekly intervals into their right eyes, and of phosphate-buffered saline into their left eyes. Seven days after the last injection, the animals were sacrificed. Axial length was measured by sonographic biometry. RESULTS: At baseline, right eyes and left eyes did not differ (all P > 0.10) in axial length in neither group, nor did the interocular difference in axial length vary between the groups (P = 0.19). During the study period, right and left eyes elongated (P < 0.001) from 8.08 ± 0.07 mm to 8.59 ± 0.06 mm and from 8.08 ± 0.07 mm to 8.66 ± 0.07 mm, respectively. The interocular difference (left eye minus right eye) in axial elongation increased significantly in all three groups (epiregulin-antibody:from 0.03 ± 0.06 mm at one week after baseline to 0.16 ± 0.08 mm at three weeks after baseline;P = 0.001); epigen-antibody group:from -0.01 ± 0.06 mm to 0.06 ± 0.08 mm;P = 0.02; betacellulin antibody group:from -0.05 ± 0.05 mm to 0.02 ± 0.04 mm;P = 0.004). Correspondingly, interocular difference in axial length increased from -0.02 ± 0.04 mm to 0.13 ± 0.06 mm in the epiregulin-antibody group (P < 0.001), and from 0.01 ± 0.05 mm to 0.07 ± 0.05 mm in the epigen-antibody group (P = 0.045). In the betacellulin-antibody group the increase (0.01 ± 0.04 mm to 0.03 ± 0.03 mm) was not significant (P = 0.24). CONCLUSIONS: The EGF family members epiregulin, epigen and betacellulin may be associated with axial elongation in young guinea pigs, with the effect decreasing from epiregulin to epigen and to betacellulin.

Prevalence, Years Lived With Disability, and Time Trends for 16 Causes of Blindness and Vision Impairment: Findings Highlight Retinopathy of Prematurity.

Background: Cause-specific prevalence data of vision loss and blindness is fundamental for making public health policies and is essential for prioritizing scientific advances and industry research. Methods: Cause-specific vision loss data from the Global Health Data Exchange was used. The burden of vision loss was measured by prevalence and years lived with disability (YLDs). Findings: In 2019, uncorrected refractory error and cataract were the most common causes for vision loss and blindness globally. Women have higher rates of cataract, age-related macular degeneration (AMD), and diabetic retinopathy (DR) than men. In the past 30 years, the prevalence of moderate/severe vision loss and blindness due to neonatal disorders has increased by 13.73 and 33.53%, respectively. Retinopathy of prematurity (ROP) is the major cause of neonatal disorders related vision loss. In 2019, ROP caused 101.6 thousand [95% uncertainty intervals (UI) 77.5-128.2] cases of vision impairment, including 49.1 thousand (95% UI 28.1-75.1) moderate vision loss, 27.5 thousand (95% UI 19.3-36.60) severe vision loss and, 25.0 thousand (95% UI 14.6-35.8) blindness. The prevalence of new-onset ROP in Africa and East Asia was significantly higher than other regions. Variation of preterm birth prevalence can explain 49.8% geometry variation of ROP-related vision loss burden among 204 countries and territories. After adjusting for preterm prevalence, government health spending per total health spending (%), rather than total health spending per person, was associated with a reduced burden of ROP-related vision loss in 2019 (-0.19 YLDs for 10% increment). By 2050, prevalence of moderate, severe vision loss and blindness due to ROP is expected to reach 43.6 (95% UI 35.1-52.0), 23.2 (95% UI 19.4-27.1), 31.9 (95% UI 29.7-34.1) per 100,000 population. Conclusion: The global burden of vision loss and blindness highlights the prevalent of ROP, a major and avoidable cause for childhood vision loss. Advanced screening techniques and treatments have shown to be effective in preventing ROP-related vision loss and are urgently needed in regions with high ROP-related blindness rates, including Africa and East Asia.