Effects of vitrectomy combined with internal limiting membrane peeling in patients with diabetic macular edema.

BACKGROUND: Diabetic macular edema (DME), a chronic microvascular complication of diabetes, is a leading cause of visual impairment and blindness. Pars plana vitrectomy (PPV) can restore the normal macular structure and reduce macular edema, whereas internal limiting membrane (ILM) peeling is used to treat tractional macular diseases. Despite the advantages, there is limited research on the combined effects of PPV with ILM peeling. AIM: To observe the effects of PPV combined with ILM peeling on postoperative central macular thickness (CMT), best-corrected visual acuity (BCVA), cystoid macular edema (CME) volume, and complications in patients with DME. METHODS: Eighty-one patients (92 eyes) diagnosed with DME at the Beijing Shanqu Liangxiang Hospital between January and December 2022 were randomly divided to undergo PPV alone (control group: 41 patients, 47 eyes) or PPV + ILM peeling (stripping group: 40 patients, 45 eyes); a single surgeon performed all surgeries. The two groups were compared preoperatively and 1 and 3 months postoperatively. RESULTS: Preoperatively, both groups had comparable values of CMT, BCVA, and CME volume (P > 0.05). After surgery (both 1 and 3 months), both groups showed significant reductions in CMT, BCVA, and CME volume compared to preoperative levels, with the stripping group showing more significant reductions compared to the control group (P < 0.05). Further repeated-measures ANOVA analysis for within-group differences revealed significant effects of group and time, and interaction effects for CMT, BCVA, and CME volume (P < 0.05). There were no significant differences in the incidence of complications between the groups (retinal detachment: control = 2, stripping = 1; endophthalmitis: Control = 4, stripping = 1; no cases of secondary glaucoma or macular holes; χ 2 = 0.296, P = 0.587). CONCLUSION: PPV with ILM peeling can significantly improve the visual acuity of patients with DME, reduce CMT, and improve CME with fewer complications.

Analysis of risk and protective factors associated with retinal nerve fiber layer defect in a Chinese adult population.

AIM: To investigate the risk and protective factors associated with the retinal nerve fiber layer defect (RNFLD) in a Chinese adult population. METHODS: This study was a cross-sectional population-based investigation including employees and retirees of a coal mining company in Kailuan City, Hebei Province. All the study participants underwent a comprehensive systemic and ophthalmic examination. RNFLD was diagnosed on fundus photographs. Binary logistic regression was used to investigate the risk and protective factors associated with the RNFLD. RESULTS: The community-based study included 14 440 participants. There were 10 473 participants in our study, including 7120 males (68.0%) and 3353 females (32.0%). The age range was 45-108y, averaging 59.56±8.66y. Totally 568 participants had RNFLD and the prevalence rate was 5.42%. A higher prevalence of RNFLD was associated with older age [P<0.001, odds ratio (OR): 1.032; 95% confidence interval (CI): 1.018-1.046], longer axial length (P=0.010, OR: 1.190; 95%CI: 1.042-1.359), hypertension (P=0.007, OR: 0.639; 95%CI: 0.460-0.887), and diabetes mellitus (P=0.019, OR: 0.684; 95%CI: 0.499-0.939). The protective factors of RNFLD were visual acuity (P=0.038, OR: 0.617; 95%CI: 0.391-0.975), and central anterior chamber depth (P=0.046, OR: 0.595; 95%CI: 0.358-0.990). CONCLUSION: In our cross-sectional community-based study, with an age range of 45-108y, RNFLD is associated with older age, longer axial length, hypertension, and diabetes mellitus. The protective factors of RNFLD are visual acuity and central anterior chamber depth. These can help to predict and evaluate RNFLD related diseases and identify high-risk populations early.

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.

Culture and identification of endothelial progenitor cells from human umbilical cord blood.

AIM: To elucidate a simple method for isolating endothelial progenitor cells (EPCs) from human umbilical cord blood mononuclear cells and observe the endothelial cell-specific expression profile during proliferation and differentiation in vitro. METHODS: Human umbilical cord blood were isolated by Percoll density gradient centrifugation from human cord blood and cultured in vitro. The adherent cells were then identified by immunohistochemical staining and flow cytometric analysis. CD(34), vascular endothelial growth factor receptor-2 (VEGFR-2), EPCs specific antigen CD(133), as well as endothelial cell specific markers CD(31) and vWF were used. The cells were characterized by acetylated LDL (acLDL) up-taking and lectin binding by direct fluorescentstaining. RESULTS: During culture, the attached cells exhibited spindle-shape in early stage, and gradually display endothelium-like cobblestone morphology with outgrowth. On day 7, flow cytometric analysis showed that the positive staining rate of attached cells for CD(133), CD(34) and VEGFR-2 were 17.8%±3.7%, 22.1%±4.4% and 81.5%±5.0%, respectively. While, immunohistochemical staining showed that the adherent cells were positive to CD(31) and vWF at the rate of 92.7%±2.2% and 73.3%±4.2%, respectively. By direct fluorescentstaining, we observed that 83.0%±4.3% of the attached cells were double positive for DiI-acLDL and FITC-UEA-I. CONCLUSION: EPCs can be separated from human cord blood under certain conditions in vitro. This observation may provide a basis for study of relationship between EPCs and retinal neovascularization, as well as further clinical application of EPCs in ischemic retinal lesions.