[Preventive early intervention strategies for neurodevelopmental disorders of high-risk infants]. / é«˜å±å„¿ç¥žç»å‘è‚²éšœç¢é¢„é˜²æ€§æ—©æœŸå¹²é¢„ç ”ç©¶è¿›å±•.

Neurodevelopmental disorders in children have become a significant global public health concern, impacting child health worldwide. In China, the current intervention model for high-risk infants involves early diagnosis and early treatment. However, in recent years, overseas studies have explored novel preventive early intervention strategies for neurodevelopmental disorders in high-risk infants, achieving promising results. This article provides a comprehensive review of the optimal timing, methods, and intervention models of the preventive early intervention strategies for neurodevelopmental disorders in high-risk infants. The aim is to enhance the awareness and knowledge of healthcare professionals regarding preventive early intervention strategies for neurodevelopmental disorders in high-risk infants, facilitate clinical research and application of such interventions in China, and ultimately reduce the incidence of neurodevelopmental disorders in this high-risk population.

Serum disease-specific IgG Fc glycosylation as potential biomarkers for nonproliferative diabetic retinopathy using mass spectrometry.

OBJECTIVE: To explore the potential of serum disease-specific immunoglobulin G (DSIgG) glycosylation as a biomarker for the diagnosis of nonproliferative diabetic retinopathy (NPDR). METHODS: A total of 387 consecutive diabetic patients presenting in an eye clinic without proliferative diabetic retinopathy (DR) were included and divided into those with nondiabetic retinopathy (NDR) (n = 181) and NPDR (n = 206) groups. Serum was collected from all patients for DSIgG separation. The enriched glycopeptides of the tryptic digests of DSIgG were detected using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Patients were randomly divided into discovery and validation sets (1:1). The differences in glycopeptide ratios between the groups were compared by using Student's t-test or the Mann-Whitney U test. The predictive ability of the model was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS: DSIgG1 G1FN/G0FN, G2N/G2, G2FN/G2N and DSIgG2 G1F/G0F, G1FN/G0FN, G2N/G1N, G2S/G2 were significantly different between NDR and NPDR patients (p < 0.05) in both the discovery and validation sets. The prediction model that was built comprising the seven glycopeptide ratios showed good NPDR prediction performance with an AUC of 0.85 in the discovery set and 0.87 in the validation set. CONCLUSION: DSIgG Fc N-glycosylation ratios were associated with NPDR and can be used as potential biomarkers for the early diagnosis of DR.

Chinese Guideline on the Management of Polypoidal Choroidal Vasculopathy (2022).

Background In mainland China, patients with neovascular age-related macular degeneration (nAMD) have approximately an 40% prevalence of polypoidal choroidal vasculopathy (PCV). This disease leads to recurrent retinal pigment epithelium detachment (PED), extensive subretinal or vitreous hemorrhages, and severe vision loss. China has introduced various treatment modalities in the past years and gained comprehensive experience in treating PCV.Methods A total of 14 retinal specialists nationwide with expertise in PCV were empaneled to prioritize six questions and address their corresponding outcomes, regarding opinions on inactive PCV, choices of anti-vascular endothelial growth factor (anti-VEGF) monotherapy, photodynamic therapy (PDT) monotherapy or combined therapy, patients with persistent subretinal fluid (SRF) or intraretinal fluid (IRF) after loading dose anti-VEGF, and patients with massive subretinal hemorrhage. An evidence synthesis team conducted systematic reviews, which informed the recommendations that address these questions. This guideline used the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach to assess the certainty of evidence and grade the strengths of recommendations. Results The panel proposed the following six conditional recommendations regarding treatment choices. (1) For patients with inactive PCV, we suggest observation over treatment. (2) For treatment-na?ve PCV patients, we suggest either anti-VEGF monotherapy or combined anti-VEGF and PDT rather than PDT monotherapy. (3) For patients with PCV who plan to initiate combined anti-VEGF and PDT treatment, we suggest later/rescue PDT over initiate PDT. (4) For PCV patients who plan to initiate anti-VEGF monotherapy, we suggest the treat and extend (T&E) regimen rather than the pro re nata (PRN) regimen following three monthly loading doses. (5) For patients with persistent SRF or IRF on optical coherence tomography (OCT) after three monthly anti-VEGF treatments, we suggest proceeding with anti-VEGF treatment rather than observation. (6) For PCV patients with massive subretinal hemorrhage (equal to or more than four optic disc areas) involving the central macula, we suggest surgery (vitrectomy in combination with tissue-plasminogen activator (tPA) intraocular injection and gas tamponade) rather than anti-VEGF monotherapy. Conclusions Six evidence-based recommendations support optimal care for PCV patients' management.

Temporal trends in ocular manifestations of HIV/AIDS patients in the past 18 years in a tertiary hospital in China.

PURPOSE: To investigate the ocular manifestation changes in human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) patents in a tertiary eye clinic in China over the past 18 years. METHODS: In this retrospective cross-sectional study, 264 HIV/AIDS patients (528 eyes) were recruited at the Department of Ophthalmology, Peking Union Medical College Hospital, from 2001 to 2018. Patients underwent ophthalmic examinations, including best-corrected visual acuity (BCVA), slit-lamp microscopy, and indirect ophthalmoscopy, and completed a registration form including demographic characteristics, medical history, and immune status data. Kruskal-Wallis test or Mann-Whitney test was used to compare continuous variables, and Pearson's chi-squared test or Fisher's exact test was performed to compare categorical variables. RESULTS: Regarding demographic characteristics, there was a significant increasing trend in male patients, sexual transmission, and HIV/AIDS-syphilis coinfection (all P < 0.001). For systemic features, more patients received cART, and fewer patients had systemic syndromes after 2003 (P < 0.001). For ocular manifestations, there were no significant changes between time intervals in CMVR and HIV retinopathy patients (P = 0.149, P = 0.643), but the proportion of patients with uveitis increased from 1.14% to 19.32% (P < 0.001). CONCLUSION: CMVR was the most common ocular compilation in HIV/AIDS patients, followed by uveitis and HIV retinopathy. The proportion of patients with CMVR and HIV retinopathy was stable over time, but the proportion of patients with uveitis showed a significant increasing trend. Therefore, immediate ophthalmic examination should be performed at the point of care or as soon as possible after entry into the health care system.

Automated detection of severe diabetic retinopathy using deep learning method.

PURPOSE: The purpose of this study is to develop and validate the intelligent diagnosis of severe DR with lesion recognition based on color fundus photography. METHODS: The Kaggle public dataset for DR grading is used in the project, including 53,576 fundus photos in the test set, 28,101 in the training set, and 7,025 in the validation set. We randomly select 4,192 images for lesion annotation. Inception V3 structure is adopted as the classification algorithm. Both 299 × 299 pixel images and 896 × 896 pixel images are used as the input size. ROC curve, AUC, sensitivity, specificity, and their harmonic mean are used to evaluate the performance of the models. RESULTS: The harmonic mean and AUC of the model of 896 × 896 input are higher than those of the 299 × 299 input model. The sensitivity, specificity, harmonic mean, and AUC of the method with 896 × 896 resolution images as input for severe DR are 0.925, 0.907, 0.916, and 0.968, respectively. The prediction error mainly occurs in moderate NPDR, and cases with more hard exudates and cotton wool spots are easily predicted as severe cases. Cases with preretinal hemorrhage and vitreous hemorrhage are easily identified as severe cases, and IRMA is the most difficult lesion to recognize. CONCLUSIONS: We have studied the intelligent diagnosis of severe DR based on color fundus photography. This artificial intelligence-based technology offers a possibility to increase the accessibility and efficiency of severe DR screening.

Using artificial intelligence reading label system in diabetic retinopathy grading training of junior ophthalmology residents and medical students.

PURPOSE: Evaluate the efficiency of using an artificial intelligence reading label system in the diabetic retinopathy grading training of junior ophthalmology resident doctors and medical students. METHODS: Loading 520 diabetic retinopathy patients' colour fundus images into the artificial intelligence reading label system. Thirteen participants, including six junior ophthalmology residents and seven medical students, read the images randomly for eight rounds. They evaluated the grading of images and labeled the typical lesions. The sensitivity, specificity, and kappa scores were determined by comparison with the participants' results and diagnosis gold standards. RESULTS: Through eight rounds of reading, the average kappa score was elevated from 0.67 to 0.81. The average kappa score for rounds 1 to 4 was 0.77, and the average kappa score for rounds 5 to 8 was 0.81. The participants were divided into two groups. The participants in Group 1 were junior ophthalmology resident doctors, and the participants in Group 2 were medical students. The average kappa score of Group 1 was elevated from 0.71 to 0.76. The average kappa score of Group 2 was elevated from 0.63 to 0.84. CONCLUSION: The artificial intelligence reading label system is a valuable tool for training resident doctors and medical students in performing diabetic retinopathy grading.

PUMCH experience and strategy for the management of idiopathic macular hole: a retrospective cohort study.

PURPOSE: To introduce and evaluate a modified therapeutic strategy for idiopathic macular holes (IMH). METHODS: A retrospective review of patients with diagnosis of IMH from July 2016 to January 2020 at Peking Union Medical College Hospital. These patients were managed strictly according to our therapeutic strategy. Their comprehensive clinical data were collected and analyzed. RESULTS: 209 eyes suffering stage II to IV IMH were identified. For stage II IMH, the spontaneous closure rate was 8.9%, the initial success rate of intravitreal injections (IVI) of expansile gas and pars plana vitrectomy (PPV) + internal limiting membrane peeling (ILMP) + air tamponade was 84.2% and 100%, respectively. The initial success rate of PPV + ILMP + air tamponade for stage III and stage IV IMH was 89.8% and 86.4%, respectively. Following our intervention strategy, stage II IMH achieved a final IMH closure rate of 100%, stage III of 99% and stage IV of 97%. The final best corrected visual acuity was significantly improved (P < 0.05). Sitting position air-fluid (A-F) exchange alone successfully induced IMH closure in 7/19 eyes that did not achieve IMH closure by initial PPV. For three refractory cases that failed additional PPV + ILM stuffing, intraoperative OCT assisted PPV + sub-retinal BSS injection successfully induced the IMH closure. As the remaining three unclosed IMH cases were dry and stable, no more interventions were conducted. CONCLUSION: The general IMH closure rate based on our therapeutic strategy was satisfactory with a favorable prognosis. IVI expansile gas and sitting position A-F exchange were effective and highly cost-effective under certain circumstances.

Mendelian randomization analysis identified genes pleiotropically associated with central corneal thickness.

OBJECTIVE: To prioritize genes that were pleiotropically or potentially causally associated with central corneal thickness (CCT). METHODS: We applied the summary data-based Mendelian randomization (SMR) method integrating summarized data of genome-wide association study (GWAS) on CCT and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with CCT. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analyses were done for participants of European and East Asian ancestries, separately. RESULTS: We identified multiple genes showing pleiotropic association with CCT in the participants of European ancestry. CLIC3 (ILMN_1796423; PSMR = 4.15 × 10- 12), PTGDS (ILMN_1664464; PSMR = 6.88 × 10- 9) and C9orf142 (ILMN_1761138; PSMR = 8.09 × 10- 9) were the top three genes using the CAGE eQTL data, and RP11-458F8.4 (ENSG00000273142.1; PSMR = 5.89 × 10- 9), LCNL1 (ENSG00000214402.6; PSMR = 5.67 × 10- 8), and PTGDS (ENSG00000107317.7; PSMR = 1.92 × 10- 7) were the top three genes using the GTEx eQTL data. No genes showed significantly pleiotropic association with CCT in the participants of East Asian ancestry after correction for multiple testing. CONCLUSION: We identified several genes pleiotropically associated with CCT, some of which represented novel genes influencing CCT. Our findings provided important leads to a better understanding of the genetic factors influencing CCT, and revealed potential therapeutic targets for the treatment of primary open-angle glaucoma and keratoconus.

Progress of artificial intelligence in diabetic retinopathy screening.

Diabetic retinopathy (DR) is one of the leading causes of blindness worldwide, and the limited availability of qualified ophthalmologists restricts its early diagnosis. For the past few years, artificial intelligence technology has developed rapidly and has been applied in DR screening. The upcoming technology provides support on DR screening and improves the identification of DR lesions with a high sensitivity and specificity. This review aims to summarize the progress on automatic detection and classification models for the diagnosis of DR.

Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.

AIMS: To establish an automated method for identifying referable diabetic retinopathy (DR), defined as moderate nonproliferative DR and above, using deep learning-based lesion detection and stage grading. MATERIALS AND METHODS: A set of 12,252 eligible fundus images of diabetic patients were manually annotated by 45 licenced ophthalmologists and were randomly split into training, validation, and internal test sets (ratio of 7:1:2). Another set of 565 eligible consecutive clinical fundus images was established as an external test set. For automated referable DR identification, four deep learning models were programmed based on whether two factors were included: DR-related lesions and DR stages. Sensitivity, specificity and the area under the receiver operating characteristic curve (AUC) were reported for referable DR identification, while precision and recall were reported for lesion detection. RESULTS: Adding lesion information to the five-stage grading model improved the AUC (0.943 vs. 0.938), sensitivity (90.6% vs. 90.5%) and specificity (80.7% vs. 78.5%) of the model for identifying referable DR in the internal test set. Adding stage information to the lesion-based model increased the AUC (0.943 vs. 0.936) and sensitivity (90.6% vs. 76.7%) of the model for identifying referable DR in the internal test set. Similar trends were also seen in the external test set. DR lesion types with high precision results were preretinal haemorrhage, hard exudate, vitreous haemorrhage, neovascularisation, cotton wool spots and fibrous proliferation. CONCLUSIONS: The herein described automated model employed DR lesions and stage information to identify referable DR and displayed better diagnostic value than models built without this information.

Anti-tumor effect of single-chain antibody to Reg3a in colorectal cancer.

BACKGROUND: Regenerating protein 3a (Reg3a) is a trophic factor that functions as a stimulus in cell proliferation and neogenesis. Previous studies showed that Reg3a is ectopically upregulated in a majority of colorectal cancers (CRC) and detectable in the serum. METHODS: Single-chain variable fragment targeting Reg3a (scFv-Reg3a) was screened from a phage library. The bioactivity of recombinant Reg3a (rReg3a) and scFv-Reg3a were tested in LoVo and RKO cell lines using MTT, flow cytometry, wound healing and transwell analyses. Whether scFv-Reg3a inhibits tumor growth and enhances 5-fluorouracil (5-FU)-caused cell death were further examined in LoVo cell-transplanted nude BALB/c mice. RESULTS: A scFv-Reg3a from clone C2 was obtained and its binding affinity (KD) to rReg3a was determined to be 4.44 × 10-10. In cultured LoVo and RKO cells, rReg3a promoted but scFv-Reg3a inhibited cell proliferation, survival, migration and invasion. In LoVo cell-xenografted nude mice, administration of rReg3a accelerated tumor growth while scFv-Reg3a suppressed cell proliferation and reinforced 5-FU-induced cell death. CONCLUSION: The newly developed scFv-Reg3a is an anti-cancer agent which is potent to suppress CRC cell proliferation and survival. The use of scFv-Reg3a could enhance the effectiveness of 5-FU-based chemotherapy in the cancerous treatment.

Development of a deep-learning system for detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus images: a pilot study.

PURPOSE: To investigate the detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus imaging system (Optos) with convolutional neural network technology. METHODS: This study included 1500 Optos color images for tessellated fundus confirmation and peripheral retinal lesion (lattice degeneration, retinal breaks, and retinal detachment) assessment. Three retinal specialists evaluated all images and proposed the reference standard when an agreement was achieved. Then, 722 images were used to train and verify a combined deep-learning system of 3 optimal binary classification models trained using seResNext50 algorithm with 2 preprocessing methods (original resizing and cropping), and a test set of 189 images were applied to verify the performance compared to the reference standard. RESULTS: With optimal preprocessing approach (original resizing method for lattice degeneration and retinal detachment, cropping method for retinal breaks), the combined deep-learning system exhibited an area under curve of 0.888, 0.953, and 1.000 for detection of lattice degeneration, retinal breaks, and retinal detachment respectively in tessellated eyes. The referral accuracy of this system was 79.8% compared to the reference standard. CONCLUSION: A deep-learning system is feasible to detect lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field images. And this system may be considered for screening and telemedicine.

THE INCIDENCE, CHARACTERISTICS, MANAGEMENT, PROGNOSIS, AND CLASSIFICATION OF BREAKTHROUGH VITREOUS HEMORRHAGE SECONDARY TO POLYPOIDAL CHOROIDAL VASCULOPATHY.

PURPOSE: To describe breakthrough vitreous hemorrhage secondary to polypoidal choroidal vasculopathy (PCV). METHODS: Patients with the diagnosis of PCV from January 2005 to March 2020 at Peking Union Medical College Hospital were retrospectively reviewed, cases with breakthrough vitreous hemorrhage were analyzed. Subgroup analysis was conducted regarding pachychoroid PCV and nonpachychoroid PCV. RESULTS: Among 722 PCV patients (834 eyes), 103 eyes with breakthrough vitreous hemorrhage (12.4%) were included. Pars plana vitrectomy and proper further interventions could significantly improve the best-corrected visual acuity from logMAR 2.15 ± 0.48 (Snellen 20/2825) to 1.65 ± 0.67 (20/893). Hemorrhagic retinal detachment, baseline central macular thickness, and best-corrected visual acuity were factors associated with final best-corrected visual acuity (P < 0.05). In the pachychoroid PCV group, patients were younger, all had hemorrhagic pigment epithelial detachment, with a higher prevalence of choroidal vascular hyperpermeability and hemorrhagic retinal detachment, thicker subfoveal choroidal thickness, and thinner central macular thickness; besides, the initial pars plana vitrectomy were more complicated, more additional surgeries had to be performed. More eyes in the nonpachychoroid PCV group had received anti-vascular endothelial growth factor or photodynamic therapy, mostly fibrovascular pigment epithelial detachment, the best-corrected visual acuity and the status of the fellow eye were significantly worse. For the final ocular status, more eyes in nonpachychoroid PCV group were taking anti-vascular endothelial growth factor monotherapy, whereas more eyes in pachychoroid PCV group were stable. The choroidal parameters of these two groups were all significantly different. CONCLUSION: Breakthrough vitreous hemorrhage is a troublesome complication of PCV. Pars plana vitrectomy and additional interventions are required for better prognosis. Vitreous hemorrhage secondary to pachychoroid PCV or nonpachychoroid PCV have different characteristics and prognosis.

Activation of quiescent polypoidal choroidal vasculopathy after membrane peeling vitrectomy for epiretinal membrane: a case report.

BACKGROUND: Regular membrane peeling vitrectomy for epiretinal membrane (ERM) patients seldom causes large pigment epithelial detachment (PED). We presented an unusual case of the activation of quiescent polypoidal choroidal vasculopathy (PCV) after membrane peeling vitrectomy for ERM, with an uneven therapeutic process. CASE PRESENTATION: A 75-year-old female patient complained of metamorphopsia in her left eye for 2 years. Her best-corrected visual acuity was 20/160 with a moderate nuclear cataract. An irregular ERM and slight PED were shown in optical coherence tomography (OCT). No obvious orange-red lesion was detected. The patient underwent vitrectomy + ERM peeling + cataract surgery. After the operation, large PED emerged, and indocyanine green angiography (ICGA) confirmed PCV. Four monthly injections of intravitreal ranibizumab were administered, but PED persisted. After focal laser therapy targeted to the polyps combined with ranibizumab treatment, PED was absorbed. CONCLUSIONS: Careful evaluation for PCV before membrane peeling vitrectomy for ERM is important, as indolent PCV may be activated postoperatively. Anti-VEGF therapy accompanied by laser photocoagulation may be more effective for PCV polyps located away from the fovea.

Utility of a public-available artificial intelligence in diagnosis of polypoidal choroidal vasculopathy.

PURPOSE: To investigate the feasibility of training an artificial intelligence (AI) on a public-available AI platform to diagnose polypoidal choroidal vasculopathy (PCV) using indocyanine green angiography (ICGA). METHODS: Two methods using AI models were trained by a data set including 430 ICGA images of normal, neovascular age-related macular degeneration (nvAMD), and PCV eyes on a public-available AI platform. The one-step method distinguished normal, nvAMD, and PCV images simultaneously. The two-step method identifies normal and abnormal ICGA images at the first step and diagnoses PCV from the abnormal ICGA images at the second step. The method with higher performance was used to compare with retinal specialists and ophthalmologic residents on the performance of diagnosing PCV. RESULTS: The two-step method had better performance, in which the precision was 0.911 and the recall was 0.911 at the first step, and the precision was 0.783, and the recall was 0.783 at the second step. For the test data set, the two-step method distinguished normal and abnormal images with an accuracy of 1 and diagnosed PCV with an accuracy of 0.83, which was comparable to retinal specialists and superior to ophthalmologic residents. CONCLUSION: In this evaluation of ICGA images from normal, nvAMD, and PCV eyes, the models trained on a public-available AI platform had comparable performance to retinal specialists for diagnosing PCV. The utility of public-available AI platform might help everyone including ophthalmologists who had no AI-related resources, especially those in less developed areas, for future studies.

Dimorphic autoantigenic and protective effects of Reg2 peptide in the treatment of diabetic ß-cell loss.

AIMS: The potential effect of regenerating (Reg) proteins in the treatment of diabetes has been indicated in the past decade, but the clinical use of Reg proteins requires more advances in translational medicine. In the present study, we produced recombinant regenerating protein 2 (rReg2), to prove its protective effect against streptozocin (STZ)-induced diabetes in BALB/c mice. MATERIALS AND METHODS: rReg2 was administrated in STZ-induced diabetic mice. Blood glucose, body weight, serum insulin and islet ß-cell loss were determined. However, Reg2 has also been reported to serve as an autoantigen that induces autoimmune attacks on islets and aggravates diabetic development in non-obese diabetic mice. To address this contradiction, complete Freund's adjuvant was injected to generate a model that was hypersensitive to Reg2. In this model, islet CD8 T-cell infiltration, serum Reg2 antibody and interleukin (IL)-4 and IL-10, and splenic CD4+/interferon (IFN)-γ+ T cells were determined. RESULTS: Direct rReg2 pretreatment preserved islet ß-cell mass against STZ and improved glycaemia, body weight and serum insulin content. The protection against cell death was further confirmed in cultured mouse islets and MIN6 cells. On the other hand, significant elevations of serum Reg2 antibody and splenic CD4+/IFN-γ+ T cells, and decreases in serum IL-4 and IL-10 were detected in rReg2-vaccinated mice, which may contribute to the accelerated diabetes. Interestingly, these mice, upon further rReg2 treatment, exhibited alleviated diabetic conditions with less islet CD8+ T-cell infiltration. CONCLUSION: rReg2 treatment ameliorated STZ-induced diabetes in normal BALB/c mice. By contrast, rReg2 vaccination exacerbated, but further rReg2 treatment alleviated, the severity of STZ-induced diabetes. Thus, the protective effect of rReg2 is predominant over the autoantigenic ß-cell destruction, supporting the potential of rReg2 in the clinical treatment of diabetes.

No Evidence of an Association between Genetic Factors Affecting Response to Vitamin A Supplementation and Myopia: A Mendelian Randomization Study and Meta-Analysis.

The relationship between vitamin A supplementation and myopia has been a topic of debate, with conflicting and inconclusive findings. We aimed to determine whether there is a causal relationship between vitamin A supplementation and the risk of myopia using Mendelian randomization (MR) and meta-analytical methods. Genetic variants from the UK Biobank and FinnGen studies associated with the response to vitamin A supplementation were employed as instrumental variables to evaluate the causal relationship between vitamin A supplementation and myopia. Fixed-effects meta-analysis was then used to combine MR estimates from multiple sources for each outcome. The meta-analysis of MR results found no convincing evidence to support a direct causal relationship between vitamin A supplementation and myopia risk (odds ratio (OR) = 0.99, 95% confidence interval (CI) = 0.82-1.20, I2 = 0%, p = 0.40). The analysis of three out of the four sets of MR analyses indicated no direction of causal effect, whereas the other set of results suggested that higher vitamin A supplementation was associated with a lower risk of myopia (OR = 0.002, 95% CI 1.17 × 10-6-3.099, p = 0.096). This comprehensive MR study and meta-analysis did not find valid evidence of a direct association between vitamin A supplementation and myopia. Vitamin A supplementation may not have an independent effect on myopia, but intraocular processes associated with vitamin A may indirectly contribute to its development.

N-glycosylation of disease-specific haptoglobin for the early screening of diabetic retinopathy.

PURPOSE: Diabetic retinopathy (DR), as one of the microvascular complications of diabetes, is a leading cause of acquired vision loss. Most DR cases are detected in the advanced stage through fundoscopy, making molecular biomarkers urgently needed for early diagnosis of DR. EXPERIMENTAL DESIGN: Serum disease-specific haptoglobin-ß (Hp-ß) chains of 100 patients with type 2 diabetes mellitus (T2DM) and 156 T2DM patients with non-proliferative diabetic retinopathy (NPDR) were separated using polyacrylamide gel electrophoresis. After in-gel digestion and enrichment, the intact N-glycopeptides were detected by mass spectrometry. RESULTS: Fucosylation of Hp-ß was significantly increased and sialylation of Hp-ß was significantly decreased in background DR (BDR, an early-stage DR) patients compared with non-diabetic retinopathy patients (p < 0.05) and yielded area under curves (AUCs) of 0.801 and 0.829 in training and validation groups, respectively, which had an advantage over glycated hemoglobin A1c (AUC ≤ 0.691). Moreover, a significant increase in sialylated Hp-ß was found in severe NPDR patients compared with BDR patients and yielded an AUC of 0.828 to distinguish severe NPDR from BDR. CONCLUSION: Changes in Hp-ß glycosylation are closely related to DR, and may be used for early diagnosis and screening of DR.

The performance of a deep learning system in assisting junior ophthalmologists in diagnosing 13 major fundus diseases: a prospective multi-center clinical trial.

Artificial intelligence (AI)-based diagnostic systems have been reported to improve fundus disease screening in previous studies. This multicenter prospective self-controlled clinical trial aims to evaluate the diagnostic performance of a deep learning system (DLS) in assisting junior ophthalmologists in detecting 13 major fundus diseases. A total of 1493 fundus images from 748 patients were prospectively collected from five tertiary hospitals in China. Nine junior ophthalmologists were trained and annotated the images with or without the suggestions proposed by the DLS. The diagnostic performance was evaluated among three groups: DLS-assisted junior ophthalmologist group (test group), junior ophthalmologist group (control group) and DLS group. The diagnostic consistency was 84.9% (95%CI, 83.0% ~ 86.9%), 72.9% (95%CI, 70.3% ~ 75.6%) and 85.5% (95%CI, 83.5% ~ 87.4%) in the test group, control group and DLS group, respectively. With the help of the proposed DLS, the diagnostic consistency of junior ophthalmologists improved by approximately 12% (95% CI, 9.1% ~ 14.9%) with statistical significance (P < 0.001). For the detection of 13 diseases, the test group achieved significant higher sensitivities (72.2% ~ 100.0%) and comparable specificities (90.8% ~ 98.7%) comparing with the control group (sensitivities, 50% ~ 100%; specificities 96.7 ~ 99.8%). The DLS group presented similar performance to the test group in the detection of any fundus abnormality (sensitivity, 95.7%; specificity, 87.2%) and each of the 13 diseases (sensitivity, 83.3% ~ 100.0%; specificity, 89.0 ~ 98.0%). The proposed DLS provided a novel approach for the automatic detection of 13 major fundus diseases with high diagnostic consistency and assisted to improve the performance of junior ophthalmologists, resulting especially in reducing the risk of missed diagnoses. ClinicalTrials.gov NCT04723160.