five

Analysis of the effectiveness of transepithelial crosslinking in patients with keratoconus

收藏
DataCite Commons2020-08-26 更新2024-07-27 收录
下载链接:
https://scielo.figshare.com/articles/Analysis_of_the_effectiveness_of_transepithelial_crosslinking_in_patients_with_keratoconus/10258295/1
下载链接
链接失效反馈
官方服务:
资源简介:
Abstract Objective: To evaluate the clinical results of Transepithelial Crosslinking (CXL) by analyzing its efficacy in patients with progressive keratoconus. Methods: Retrospective cross-sectional study with 49 eyes and 37 patients aged 10 to 50 years submitted to the CXL technique in 2017 at the Instituto Panamericano da Visão, in Goiânia, Goiás, Brazil. The Avedro KXL system was programmed in pulsed mode with interval (1/1 second), using 45 mW/cm² with 7.2 J and 0.25% riboflavin solution of Avedro with irradiated corneas for 8 minutes. Data were collected: sex, age, uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), astigmatism, pachymetry at the thinnest point and keratometric astigmatism in the preoperative and postoperative periods at 1, 6 and 12 months. The Kolmogorov-Smirnov, Pearson's Chi-square, Friedman, Dunnett, and the Spearman correlation were used. Results: Twenty-three patients (62.2%) were female and 14 (37.8%) male. The mean age was 27.89 ± 10.89 years. The UDVA and CDVA significantly improved in the preoperative period in relation to 1 month (p = 0.01) and (p <0.001), 6 months (p <0.001 both) and 12 months (p <0.001 both). Astigmatism significantly reduced preoperatively in relation to 6 months (p = 0.02) and 12 months (p = 0.02). The pachymetry at the thinnest point remained constant in the period (p = 0.95). The difference between k2 and k1 (keratometric astigmatism) showed a significant reduction in the preoperative period in relation to 1 month (p = 0.01). Conclusion: The CXL technique was safe and effective in the treatment and stagnation of the disease in patients with progressive keratoconus.
提供机构:
SciELO journals
创建时间:
2019-11-06
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作