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Abstract Background To determine the prevalence and associations of asteroid hyalosis (AH) in a Chinese population-based cohort. Methods The retrospective, cross-sectional, population-based Beijing Eye Study 2011 included 3468 individuals with a mean age of 64.6 ± 9.8 years (range: 50–93 years). Participants underwent detailed ophthalmic examinations including fundus photographs for diagnosis of AH. Data on systemic and ocular factors were collected for all participants according to the standardized protocol. Multiple linear regression and multivariate Logistic regression analysis were performed. Results Fundus photographs were gradable in 3419 subjects. AH was detected in 63 (0.9%, 95% CI: 0.7%, 1.1%) eyes of 53 (1.6%, 95% CI: 1.1%, 2.0%) subjects. AH was bilateral in 18.9%. Mean age of all subjects with AH was 69.2 ± 9.5 years (median, 71.0 years; range, 51–91 years), mean spherical equivalent was 0.63 ± 1.53D (median, 0.75 D; range, -4.12 to 4.00D). In multivariate analysis, prevalence of AH was associated with elder age (P = 0.014, OR 1.057), thicker lens (P = 0.032, OR 3.887), higher spherical equivalent (P = 0.017, OR 1.396). Conclusions In adult Chinese in Beijing, the prevalence of AH was 0.9% for eyes or 1.6% for subjects. AH was associated with elder age, thicker lens, and higher spherical equivalent. It was not associated with diabetes or other systemic indicators.

Background: To determine the prevalence and associations of asteroid hyalosis (AH) in a Chinese population-based cohort.Methods: The retrospective, cross-sectional, population-based Beijing Eye Study 2011 included 3468 individuals with a mean age of 64.6 ± 9.8 years (range: 50-93 years). Participants underwent detailed ophthalmic examinations including fundus photographs for diagnosis of AH. Data on systemic and ocular factors were collected for all participants according to the standardized protocol. Multiple linear regression and multivariate Logistic regression analysis were performed.Results: Fundus photographs were gradable in 3419 subjects. AH was detected in 63 (0.9%, 95% CI: 0.7%, 1.1%) eyes of 53 (1.6%, 95% CI: 1.1%, 2.0%) subjects. AH was bilateral in 18.9%. Mean age of all subjects with AH was 69.2 ± 9.5 years (median, 71.0 years; range, 51-91 years), mean spherical equivalent was 0.63 ± 1.53D (median, 0.75 D; range, -4.12 to 4.00D). In multivariate analysis, prevalence of AH was associated with elder age (P = 0.014, OR 1.057), thicker lens (P = 0.032, OR 3.887), higher spherical equivalent (P = 0.017, OR 1.396).Conclusions: In adult Chinese in Beijing, the prevalence of AH was 0.9% for eyes or 1.6% for subjects. AH was associated with elder age, thicker lens, and higher spherical equivalent. It was not associated with diabetes or other systemic indicators. [ABSTRACT FROM AUTHOR]

Lei Shao, Chuan Zhang, Li Dong, Wen Da Zhou, Rui Heng Zhang, Wen Bin Wei Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence: Wen Bin WeiBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 1 Dong Jiao Min Xiang, Dong Cheng District, Beijing, 100730, People’s Republic of ChinaTel +86-10-58269516Fax +86-10-6512 5617Email weiwenbintr@163.comPurpose: To explore the prevalence and associations of vitreous macular traction (VMT) in Chinese population.Methods: A population-based cross-sectional study with 3468 individuals (mean age of 64.6 ± 9.8 years) based on Beijing Eye Study 2011. Participants underwent detailed ophthalmic examinations, including spectral domain optical coherence tomography (SD-OCT). VMT was defined as abnormal posterior vitreous detachment with anatomical deformation of the fovea, which may include pseudocyst, macular schisis, cystoid macular edema, and subretinal fluid.Main Outcome Measure: Prevalence of VMT.Results: A VMT was detected in 151 (2.3%) eyes (prevalence rate (mean ± SE): 2.3± 0.2%; 95% CI: 1.9%, 2.7%) of 80 (2.4%) subjects (prevalence rate: 2.4± 0.3%; 95% CI: 1.9%, 2.9%). Mean age of all subjects with VMT was 70.1± 8.7 years (median, 70.0 years; range, 50– 90 years), mean refractive error was − 0.22 ± 2.38D (median, 0.25 D; range, − 15.00 to 5.25D). In multivariate analysis, prevalence of VMT was associated with elder age (P=0.001, OR 1.06), female gender (P = 0.036, OR 1.77), subfoveal retinal thickness (P = 0.005, OR 1.01), and subfoveal choroidal thickness (P = 0.026, OR 0.10).Conclusion: In adult Chinese in Greater Beijing, the prevalence of VMT was 2.3% for eyes or 2.4% for subjects. While it was associated with elder age, female gender, thicker subfoveal retinal thickness and thinner subfoveal choroidal thickness.Keywords: vitreous macular traction, optical coherence tomography, the Beijing Eye Study

PurposeTo predict the fundus tessellation (FT) severity with machine learning methods.MethodsA population-based cross-sectional study with 3,468 individuals (mean age of 64.6 ± 9.8 years) based on Beijing Eye Study 2011. Participants underwent detailed ophthalmic examinations including fundus images. Five machine learning methods including ordinal logistic regression, ordinal probit regression, ordinal log-gamma regression, ordinal forest and neural network were used.Main Outcome MeasureFT precision, recall, F1-score, weighted-average F1-score and AUC value.ResultsObserved from the in-sample fitting performance, the optimal model was ordinal forest, which had correct classification rate (precision) of 81.28%, while 34.75, 93.73, 70.03, and 24.82% in each classified group by FT severity. The AUC value was 0.7249. And the F1-score was 65.05%, weighted-average F1-score was 79.64% on the whole dataset. For out-of-sample prediction performance, the optimal model was ordinal logistic regression, which had precision of 77.12% on the validation dataset, while 19.57, 92.68, 64.74, and 6.76% in each classified group by FT severity. The AUC value was 0.7187. The classification accuracy of light FT group was the highest, while that of severe FT group was the lowest. And the F1-score was 54.46%, weighted-average F1-score was 74.19% on the whole dataset.ConclusionsThe ordinal forest and ordinal logistic regression model had the strong prediction in-sample and out-sample performance, respectively. The threshold ranges of the ordinal forest model for no FT and light, moderate, severe FT were [0, 0.3078], [0.3078, 0.3347], [0.3347, 0.4048], [0.4048, 1], respectively. Likewise, the threshold ranges of ordinal logistic regression model were ≤ 3.7389, [3.7389, 10.5053], [10.5053, 13.9323], > 13.9323. These results can be applied to guide clinical fundus disease screening and FT severity assessment.