PurposeTo compare the difference and agreement in central corneal thickness (CCT), keratometry (K), anterior chamber depth (ACD), aqueous depth (AQD), and lens thickness (LT) measured with CASIA 2 and IOLMaster 700 in patients with cataract.MethodsA total of 81 patients with cataract (81 eyes) scheduled for phacoemulsification were prospectively collected from March to May, 2020 in the cataract department of Zhongshan Ophthalmic Center, Sun Yat-sen University, including 43 males and 38 females with age of 61.5 ± 10.6 years. CCT, anterior Kf, anterior Ks, real Kf, real Ks, ACD, AQD, and LT were measured with CASIA 2 and IOLMaster 700. Paired t-test, intraclass correlation coefficients (ICCs), 95% limit of agreement (95% LoA), and Bland-Altman plots were performed and used to analyze the difference and agreement between the two devices.ResultsThere was no statistically significant difference in anterior K measurement with the CASIA 2 (44.3 ± 1.66 mm) and IOLMaster 700 (44.31 ± 1.67 mm, P = 0.483). Differences among the CCT, anterior Kf, real Kf, real Ks, ACD, AQD, and LT measured by the two instruments were statistically significant (P < 0.001). The ICCs of CCT, anterior Kf, anterior Ks, real Kf, real Ks, ACD, AQD, and LT measurements between the two devices were 0.892, 0.991, 0.991, 0.827, 0.817, 0.937, 0.926, and 0.997, respectively. The 95% LoA between CASIA 2 and IOLMaster 700 was −30.06 to 0.43 μm for CCT, −0.3 to 0.48 D for anterior Kf, −0.46 to −0.43 D for anterior Ks, −1.49 to −0.49 D for real Kf, −1.62 to −0.49 D for Real Ks, −0.03 to 0.24 mm for ACD, 0.04 to 0.25 mm for AQD, and −0.06 to 0.09 mm for LT.ConclusionAnterior Kf, anterior Ks, ACD, AQD, and LT have excellent agreement between the two devices. CCT, real Kf, and real Ks have moderate agreement between the two devices. It is recommended to use anterior Kf, anterior Ks, ACD, AQD, and LT interchangeably between CASIA 2 and IOLMaster 700.

PurposeThe purpose of this study was to investigate the hotspots and research trends of ophthalmology research.MethodOphthalmology research literature published between 2017 and 2021 was obtained in the Web of Science Core Collection database. The bibliometric analysis and network visualization were performed with the VOSviewer and CiteSpace. Publication-related information, including publication volume, citation counts, countries, journals, keywords, subject categories, and publication time, was analyzed.ResultsA total of 10,469 included ophthalmology publications had been cited a total of 7,995 times during the past 5 years. The top countries and journals for the number of publications were the United States and the Ophthalmology. The top 25 global high-impact documents had been identified using the citation ranking. Keyword co-occurrence analysis showed that the hotspots in ophthalmology research were epidemiological characteristics and treatment modalities of ocular diseases, artificial intelligence and fundus imaging technology, COVID-19-related telemedicine, and screening and prevention of ocular diseases. Keyword burst analysis revealed that “neural network,” “pharmacokinetics,” “geographic atrophy,” “implementation,” “variability,” “adverse events,” “automated detection,” and “retinal images” were the research trends of research in the field of ophthalmology through 2021. The analysis of the subject categories demonstrated the close cooperation relationships that existed between different subject categories, and collaborations with non-ophthalmology-related subject categories were increasing over time in the field of ophthalmology research.ConclusionsThe hotspots in ophthalmology research were epidemiology, prevention, screening, and treatment of ocular diseases, as well as artificial intelligence and fundus imaging technology and telemedicine. Research trends in ophthalmology research were artificial intelligence, drug development, and fundus diseases. Knowledge from non-ophthalmology fields is likely to be more involved in ophthalmology research.

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Introduction This study aimed to evaluate the publication delays and correlative factors of peer-reviewed ophthalmology journals. Methods The ophthalmology journals listed in the Journal Citation Report 2020 were retrieved from the Web of Science database. The first original research article of each journal issue from January to December 2020 was extracted, and its submission, final revision, acceptance, and publication dates were obtained. Information on impact factors, advance online publication (AOP) status, open access (OA) rate and acceptance rate in 2020 was also collected. The correlations between publication delays and potential associated factors were analyzed. Results A total of 58 ophthalmology journals were included and information on 685 articles was collected. The median times from submission to acceptance, from acceptance to publication, and from submission to publication were 118.0 (IQR, 74.0–185.0) days, 31.0 (IQR, 15.0–64.0) days, and 161.0 (IQR, 111.0–232.0) days, respectively. A higher impact factor was correlated with shorter delays of acceptance and publication (P < 0.05). There was a positive correlation between acceptance rates and publication delays (r = 0.726, P = 0.007). Forty-seven (81.03%) journals provided AOP. There was no statistically significant difference for impact factors and publication delays between journal with and without AOP (all P > 0.05). No correlation between OA rate and publication delays or impact factors was detected (all P > 0.05). Conclusions Journals with higher impact factors and lower acceptance rates tend to have quicker publication processes. No significant associations were detected between publication delays and AOP or OA rate.