Department of Ophthalmology and Micro-Technology, Yokohama City University, Kanagawa, Japan.
Department of Ophthalmology, The University of Tokyo, Graduate School of Medicine, Tokyo, Japan.
PLoS One. 2021 Mar 23;16(3):e0249073. doi: 10.1371/journal.pone.0249073. eCollection 2021.
A smoking habit can cause various health problems encompassing retinal diseases including central serous chorioretinopathy (CSC). The aim of the current study was to investigate the effect of smoking on the choroidal structure in patients with CSC.
The choroidal vascular index (CVI) was calculated using the binarized OCT images. Baseline parameters (age, refractive error [SE], subfoveal choroidal thickness [SFCT] and CVI) were compared between smokers and non-smokers using Wilcoxon rank sum test. Moreover, the associations between SFCT and the baseline parameters were analyzed using a multivariate linear regression followed by the AICc model selection.
Among 75 CSC patients, 45 patients were smokers and 30 patients were non-smokers. No significant differences in age and SE were seen between the smoking group and the non-smoking group. A significant difference in the SFCT was seen between two groups (382.0 ± 68.2 μm in the smoking group vs. 339.3 ± 52.3 μm in the non-smoking group, p = 0.0038), while no significant difference was observed in the CVI (p = 0.32). The optimal model for SFCT included the variables of age, SE and past history of smoking among the baseline parameters. Additionally, increased pack years was associated with increased SFCT.
Cigarette smoking was associated with an increased SFCT in patients with CSC. Thicker choroid in smoking CSC patients may be an important modulator of the disease.
吸烟习惯可导致各种健康问题，包括视网膜疾病，如中心性浆液性脉络膜视网膜病变（CSC）。本研究旨在探讨吸烟对 CSC 患者脉络膜结构的影响。
使用二值化 OCT 图像计算脉络膜血管指数（CVI）。使用 Wilcoxon 秩和检验比较吸烟者和非吸烟者的基线参数（年龄、屈光不正[SE]、中心凹下脉络膜厚度[SFCT]和 CVI）。此外，使用多元线性回归分析 SFCT 与基线参数之间的相关性，然后使用 AICc 模型选择进行分析。
在 75 例 CSC 患者中，45 例为吸烟者，30 例为非吸烟者。吸烟组和非吸烟组之间的年龄和 SE 无显著差异。两组间 SFCT 存在显著差异（吸烟组为 382.0±68.2μm，非吸烟组为 339.3±52.3μm，p=0.0038），而 CVI 无显著差异（p=0.32）。SFCT 的最佳模型包括基线参数中的年龄、SE 和吸烟史等变量。此外，吸烟包年数与 SFCT 增加有关。
吸烟与 CSC 患者 SFCT 增加有关。吸烟 CSC 患者的脉络膜较厚可能是疾病的重要调节因素。
