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.

Lens-induced myopization and body weight in young guinea pigs.

BACKGROUND: To investigate the relationship between body weight and Axial length in guinea pigs. METHODS: Forty pigmented guinea pigs were randomly divided into two groups, namely control group and negative lens-induced myopization (LIM) group. After measuring the baseline axial length and body weight (BW), guinea pigs of LIM group received bilateral negative lens-induced myopization using - 10.0 diopters lenses. One week later, the lenses were removed and biometric and ophthalmoscopic examinations were repeated. RESULTS: Two groups of guinea pigs showed no statistical difference in initial body weight and eye axis length. Compared to the control group, the lens-induced group had a lower weight (P = 0.02) and a longer axial length (P < 0.01) at the end of study Neither at baseline nor at week 1 did AL correlate with BW in both groups (Control Baseline: r = 0.306, P = 0.19; Control Week1: r = 0.333, P = 0.15; LIM Baseline: r=-0.142, P = 0.55; LIM Week 1: r = 0.189, P = 0.42). Lens-induction had a significant effect on axial elongation (P < 0.01) while body weight had no impact on such aspect (P > 0.05). CONCLUSION: In guinea pigs of the same age, axial length was not correlated with body weight. Also, baseline body weight had no impact on natural axial length growth or lens-induced myopia. Lens-induction caused a significant reduction in body weight gain.

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).

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.

Retrospective analysis of secondary enucleation for uveal melanoma after plaque radiotherapy.

BACKGROUND: Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Plaque brachytherapy (PRT) is widely accepted as an effective globe-conserving treatment modality for UM. However, local treatment failure and complications lead to the enucleation of irradiated eyes. We conducted this study to explore the causes and long-term prognosis for UM patients who accepted secondary enucleation after plaque radiotherapy. METHODS: This was a retrospective cohort study. Data of patients who underwent secondary enucleation for UM after plaque radiotherapy, from July 2007 to July 2019, at Beijing Tongren Hospital were analyzed. Kaplan-Meier analysis was performed to assess the probability of indications, metastasis, and metastasis-related death. Cox regression analysis was used to analyze associations of the prognostic factors. RESULTS: Eight hundred and eighty patients were clinically diagnosed with uveal melanoma and initially treated by iodine-125 plaque radiotherapy, 132 of whom underwent secondary enucleation and pathological examination in the same hospital. Fifty-two (39.4%) eyes were enucleated simply because of uncontrollable neovascular glaucoma (NVG). Forty-four (33.3%) patients suffered from tumor recurrence. Tumor non-response occurred in 18 (13.6%) cases. Ten (7.6%) eyes received enucleation entirely due to other types of glaucoma. Failure to preserve the eyes for other reasons occurred in eight (6.1%) patients. At a median follow-up of 58.1 [IQR: 40.9-90.5] months, the systemic spread was detected in 45 (34.1%) patients, and 38 of them died. On multivariate analysis, tumor largest basal diameter (HR 1.15 [95% CI: 1.01, 1.31]), tumor non-response (HR 7.22 [95% CI: 2.63, 19.82]), and recurrence (HR 3.29 [95% CI: 1.54, 7.07]) were risk factors for metastasis. Increased age (HR 1.54 [95% CI: 1.07, 2.23]), tumor non-response (HR 7.91 [95% CI: 2.79, 22.48]), and recurrence (HR 3.08 [95% CI: 1.13, 7.23]) were risk factors for metastasis-related death. CONCLUSIONS: NVG was the major reason for secondary enucleation for Chinese UM patients after PRT. Tumor non-response and recurrence were associated with a significantly higher risk of long-term metastasis and metastasis-related death.

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.

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.

Global, regional, and national prevalence, disability adjusted life years, and time trends for refraction disorders, 1990-2019: findings from the global burden of disease study 2019.

BACKGROUND: To evaluate global burden of refraction disorders by year, age, region, gender, socioeconomic status and other national characteristics in terms of disability adjusted life years (DALYs) and prevalence from Global Burden of Disease (GBD) study 2019 and World Bank Open Data 2019. METHODS: Global, regional, and national DALY numbers, crude DALY rates, age-standardized DALY and prevalence rates of refraction disorders were acquired from the GBD study 2019. Mobile cellular subscriptions, urban population, GDP per capita, access to electricity and total fertility rate were obtained from the World Bank to explore the factors that influenced the health burden of refraction disorders. Kruskal-Wallis test, linear regression and multiple linear regression were performed to evaluate the associations between the health burden with socioeconomic levels and other national characteristics. Wilcoxon Signed-Rank Test was used to investigate the gender disparity. RESULTS: Globally, age-standardized DALY rates of refraction disorders decreased from 88.9 (95% UI: 60.5-120.3) in 1990 to 81.5 (95% UI: 55.0-114.8) in 2019, and might fall to 73.16 (95% UI: 67.81-78.51) by 2050. Age-standardized prevalence rates would also reduce to 1830 (95% UI: 1700-1960) by 2050, from 2080 (95% UI: 1870-2310) in 1990 to 1960 (95% UI: 1750-2180) in 2019. In low SDI region, age-standardized DALY rates (equation: Y = 114.05*X + 27.88) and prevalence rates (equation: Y = 3171.1*X + 403.2) were positively correlated with SDI in linear regression respectively. East Asia had the highest blindness rate caused by refraction disorders in terms of age-standardized DALY rates (11.20, 95% UI: 7.38-16.36). Gender inequality was found among different age groups and SDI regions. CONCLUSION: Health burden of refraction disorders decreased in recent years, and may continue to alleviate in the next three decades. Older ages, females and lower socioeconomic status were associated with higher refraction disorders health burden.

Non-linear association between diabetes mellitus and pulmonary function: a population-based study.

BACKGROUND: There is increasing evidence that the lung is a target organ of diabetes. This study aimed to examine in detail the association between diabetes mellitus and pulmonary function using a national cohort. We also aimed to explore the non-linear association between pulmonary function and blood glucose, insulin resistance, and C-reactive protein (CRP). METHODS: A total of 30,442 participants from the National Health and Nutrition Examination Survey from the period between 2007 and 2012 were included. The cross-sectional association between diabetes mellitus and pulmonary function was assessed using multiple linear regression. Where there was evidence of non-linearity, we applied a restricted cubic spline with three knots to explore the non-linear association. Partial mediation analysis was performed to evaluate the underlying mechanism. All analyses were weighted to represent the US population and to account for the intricate survey design. RESULTS: A total of 8584 people were included in the final study population. We found that diabetes was significantly associated with reduced forced expiratory volume in one second (FEV1) and forced vital capacity. We further found L-shaped associations between hemoglobin A1c (HbA1c) and pulmonary function. There was a negative association between HbA1c and FEV1 in diabetes participants with good glucose control (HbA1c < 7.0%), but not in patients with poor glucose control. A non-linear association was also found with fasting plasma glucose, 2 h-plasma glucose after oral glucose tolerance test, insulin resistance, and CRP. Finally, we found that diabetes duration did not affect pulmonary function, and the deleterious effect of diabetes on pulmonary function was mediated by hyperglycemia, insulin resistance, low-grade chronic inflammation (CRP), and obesity. CONCLUSIONS: Diabetes mellitus is non-linearly associated with pulmonary function. Our finding of a negative association between HbA1c and FEV1 in diabetes patients with good glucose control but not in patients with poor glucose control indicates that a stricter glycemic target should be applied to diabetic patients to improve pulmonary function. Given, the cross-sectional nature of this research, a longitudinal study is still needed to validate our findings.

Obstructive sleep apnea is associated with coronary microvascular dysfunction: A systematic review from a clinical perspective.

There is now increasing evidence demonstrating that obstructive sleep apnea (OSA) contributes to microvascular disorder. However, whether OSA is associated with impaired coronary flow reserve is still unclear. Therefore, we conducted this systematic review and meta-analysis to summarize current evidence. In a systematic review, PubMed, Embase, the Cochrane Library and Web of Science were searched; five observational studies fulfilled the selection criteria and were included in this study. Data were extracted from selected studies and meta-analysis was performed using random-effects modelling. In all, 829 OSA patients and 507 non-OSA subjects were included and assessed for coronary flow reserve (CFR), the clinical indicator of coronary microvascular dysfunction (CMD). For all studies, OSA was significantly associated with reduced CFR. The pooled weighted mean difference (WMD) of CFR was -0.78 (95% confidence interval [CI] -1.25 to -0.32, p ï¼œ 0.001, I2  = 84.4%). The difference in the apnea-hypopnea index (AHI) between studies can explain 89% of heterogeneity (coef = -0.05, 95% CI -0.12 to 0.02, p = .078) in a meta-regression, indicating the CFR tended to negatively correlate with severity of OSA. The Egger regression test did not show statistical significance (p = .49). In conclusion, there are plausible biological mechanisms linking OSA and CMD, and the preponderance of evidence from this systematic review suggests that OSA, especially severe OSA, is associated with reduced CFR. Future studies are warranted to further delineate the exact role of OSA in CMD occurrence and development in a prospective setting.

Could Vitamin D be Associated with Proliferative Diabetic Retinopathy? Evidence from Pooling Studies.

Contrasting data about the association between proliferative diabetic retinopathy (PDR) and vitamin D status remain unknown. First, a hospital-based cross-sectional study consisting of 889 diabetic retinopathy (DR) and non-DR (NDR) patients was admitted. Further the accumulated evidence was performed to explore the association and dose-response relationship. Our study indicated that the odd ratio for PDR in vitamin D deficiency (VDD) individuals was significantly increased (1.60, 95% CI 1.06-2.42), compared with NDR in vitamin D sufficiency individuals, adjusted by age, sex, diabetic duration, and HbA1c. Four studies plus our study with data on vitamin D levels in 4970 patients with PDR and NDR subjects are compared. Association between vitamin D deficiency and risk of PDR exists (OR=1.69, 95% CI 1.40-2.05; I2=0%, p=0.61). Association between a nonlinear trend for vitamin D decrease with risk of DR was significant (chi2=16.53, p=0.0003). No significant heterogeneity in identified studies was found (goodness of fit chi2=2.98, p=0.225). It is concluded that vitamin D deficiency is significantly associated with risk of proliferative diabetic retinopathy.

Cognition-Driven Structural Prior for Instance-Dependent Label Transition Matrix Estimation.

The label transition matrix has emerged as a widely accepted method for mitigating label noise in machine learning. In recent years, numerous studies have centered on leveraging deep neural networks to estimate the label transition matrix for individual instances within the context of instance-dependent noise. However, these methods suffer from low search efficiency due to the large space of feasible solutions. Behind this drawback, we have explored that the real murderer lies in the invalid class transitions, that is, the actual transition probability between certain classes is zero but is estimated to have a certain value. To mask the invalid class transitions, we introduced a human-cognition-assisted method with structural information from human cognition. Specifically, we introduce a structured transition matrix network (STMN) designed with an adversarial learning process to balance instance features and prior information from human cognition. The proposed method offers two advantages: 1) better estimation effectiveness is obtained by sparing the transition matrix and 2) better estimation accuracy is obtained with the assistance of human cognition. By exploiting these two advantages, our method parametrically estimates a sparse label transition matrix, effectively converting noisy labels into true labels. The efficiency and superiority of our proposed method are substantiated through comprehensive comparisons with state-of-the-art methods on three synthetic datasets and a real-world dataset. Our code will be available at https://github.com/WheatCao/STMN-Pytorch.

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.

Meta-regression of idiopathic full-thickness macular holes diameter and anatomical closure rate: Implications to intraoperative technique.

Purpose: Primary surgery failure of macular holes causes poor visual acuity outcomes. Several studies indicate that small-medium idiopathic full-thickness macular holes (iFTMH) have consistent and high anatomical closure rates after vitrectomy and internal limiting membrane (ILM) peeling, regardless of iFTMH diameters. However, there is no systematic analysis examining the relationship between iFTMH diameters and anatomical closure rates. Methods: In this systematic review and meta-regression, we searched PubMed, Embase, and Web of Science databases on October 24th, 2022. We included studies regarding iFTMH, with ILM peeling/inverted flap technique, long-lasting gas tamponade, and face-down position after surgery. Univariable meta-regression with a restricted cubic spline model and component-plus-residual plot after covariables adjustment were used to explore non-linear association. Results: A total of 7257 participants from 19 randomized controlled trials and 49 observational studies were included in this meta-analysis. In ILM peeling group, every 100-µm increment in diameter was associated with a 3.8 % (95 % confidence interval [CI], 1.8%-5.7 %, P < 0.001) relatively lower anatomical closure rate. Yet, among studies using the inverted flap technique, baseline iFTMH diameter was not associated with a lower anatomical closure rate (0.2 %, 95%CI, -4.2 %-4.5 %, P > 0.9). The restricted cubic spline model and component-plus-residual plot controlling for age, sex, and symptom duration prior to surgery showed no evident non-linearity in both surgical techniques. Conclusions: The iFTMH diameter is linear and inversely associated with the anatomical closure rate after the ILM peeling technique, but not with the inverted flap technique. The present study supports the use of advanced techniques, e.g., inverted flap technique, in small-medium iFTMH to improve anatomical closure rates.

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.

Development and validation of a nomogram to predict the recurrence of eyelid sebaceous gland carcinoma.

PURPOSE: Eyelid sebaceous gland carcinoma (SGC) is a malignancy with fatal risk, high recurrence rate, and pagetoid spread. Thus, recurrence risk prediction and prompt treatment are extremely important. This study aimed to develop a nomogram to predict SGC recurrence based on potential risk factors. METHODS: We conducted a retrospective study to train and test a nomogram based on the clinical data of 391 patients across our hospital (304) and other grass-roots hospitals (87). After Cox regression, predictors included in the nomogram were selected, and sensitivity, specificity, concordance index (C-index), etc., were calculated to test their discrimination ability. RESULTS: After a median follow-up period of 4.12 years, SGC recurred in 52 (17.11%) patients. The 1-, 2-, and 5-year recurrence-free survival rates were 88.3%, 85.4%, and 81.6%, respectively. We examined five risk factors, such as lymph node metastasis at initial diagnosis (hazard ratio [HR], 2.260; 95% confidence interval [CI], 1.021-5.007), Ki67 (HR, 1.036; 95% CI, 1.020-1.052), histology differentiation degree (HR, 2.274; 95% CI, 1.063-4.865), conjunctival pagetoid infiltration (HR, 2.100; 95% CI, 1.0058-4.167), and orbital involvement (HR, 4.764; 95% CI, 1.436-15.803). The model had good discrimination in both internal and external test sets. The model had good discrimination in both internal and external test sets. The sensitivity of the internal test and external test set were 0.722 and 0.806, respectively, and specificity of the internal test and external test set were 0.886 and 0.893, respectively. CONCLUSION: We examined the potential risk factors for eyelid SGC recurrence and constructed a nomogram, which complements the TNM system in terms of prediction, indicating that our nomogram has the potential to reach clinical significance. This nomogram has the potential to assist healthcare practitioners in promptly detecting patients who are at an elevated risk and in tailoring clinical interventions to meet their individualized needs.

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.

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.