State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Study Center for Ocular Diseases, Sun Yat-Sen University, Guangzhou, China.
Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Invest Ophthalmol Vis Sci. 2024 Oct 1;65(12):5. doi: 10.1167/iovs.65.12.5.
The purpose of this study was to investigate whether the rapid rate of peripapillary retinal nerve fiber layer (pRNFL) thinning in short-term is associated with the future risk of developing diabetic retinopathy (DR).
This prospective cohort study utilized 4-year follow-up data from the Guangzhou Diabetic Eye Study. The pRNFL thickness was measured by optical coherence tomography (OCT). DR was graded by seven-field fundus photography after dilation of the pupil. Correlations between pRNFL thinning rate and DR were analyzed using logistic regression. The additive predictive value of the prediction model was assessed using the C-index, net reclassification index (NRI), and integrated discriminant improvement index (IDI).
A total of 1012 patients with diabetes (1012 eyes) without DR at both baseline and 1-year follow-up were included in this study. Over the 4-year follow-up, 132 eyes (13%) developed DR. After adjusting for confounding factors, a faster rate of initial pRNFL thinning was significantly associated with the risk of DR (odds ratio per standard deviation [SD] decrease = 1.15, 95% confidence interval [CI] = 1.08 to 1.23, P < 0.001). Incorporating either the baseline pRNFL thickness or its thinning rate into conventional prediction models significantly improved the discriminatory power. Adding the rate of pRNFL thinning further enhanced the discriminative power compared with models with only baseline pRNFL thickness (C-index increased from 0.685 to 0.731, P = 0.040). The IDI and NRI were 0.114 and 0.463, respectively (P < 0.001).
The rate of initial pRNFL thinning was associated with DR occurrence and improved discriminatory power of traditional predictive models. This provides new insights into the management and screening of DR.
本研究旨在探讨短期内视盘周围视网膜神经纤维层(pRNFL)变薄的快速速率是否与糖尿病视网膜病变(DR)未来发生的风险相关。
本前瞻性队列研究使用了广州糖尿病眼病研究的 4 年随访数据。通过光学相干断层扫描(OCT)测量 pRNFL 厚度。通过散瞳后七视野眼底照相对 DR 进行分级。使用逻辑回归分析 pRNFL 变薄率与 DR 之间的相关性。使用 C 指数、净重新分类指数(NRI)和综合判别改善指数(IDI)评估预测模型的附加预测价值。
本研究共纳入了 1012 例糖尿病患者(1012 只眼),这些患者在基线和 1 年随访时均无 DR。在 4 年的随访期间,有 132 只眼(13%)发生了 DR。在调整混杂因素后,初始 pRNFL 变薄的更快速率与 DR 的发生风险显著相关(每标准差下降的优势比=1.15,95%置信区间[CI]为 1.08 至 1.23,P<0.001)。将基线 pRNFL 厚度或其变薄率纳入传统预测模型中均显著提高了判别能力。与仅使用基线 pRNFL 厚度的模型相比,加入 pRNFL 变薄率可进一步提高判别能力(C 指数从 0.685 增加到 0.731,P=0.040)。IDI 和 NRI 分别为 0.114 和 0.463(P<0.001)。
初始 pRNFL 变薄率与 DR 发生相关,并提高了传统预测模型的判别能力。这为 DR 的管理和筛查提供了新的思路。