Shi Yi, Zhang Yan-Xin, Jiao Ming-Fei, Ren Xin-Jun, Hu Bo-Jie, Liu Ai-Hua, Li Xiao-Rong
Surgical Retina, Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin 300384, China.
Glaucoma, Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin 300384, China.
World J Diabetes. 2024 Apr 15;15(4):654-663. doi: 10.4239/wjd.v15.i4.654.
Neovascular glaucoma (NVG) is likely to occur after pars plana vitrectomy (PPV) for diabetic retinopathy (DR) in some patients, thus reducing the expected benefit. Understanding the risk factors for NVG occurrence and building effective risk prediction models are currently required for clinical research.
To develop a visual risk profile model to explore factors influencing DR after surgery.
We retrospectively selected 151 patients with DR undergoing PPV. The patients were divided into the NVG (NVG occurrence) and No-NVG (No NVG occurrence) groups according to the occurrence of NVG within 6 months after surgery. Independent risk factors for postoperative NVG were screened by logistic regression. A nomogram prediction model was established using R software, and the model's prediction accuracy was verified internally and externally, involving the receiver operator characteristic curve and correction curve.
After importing the data into a logistic regression model, we concluded that a posterior capsular defect, preoperative vascular endothelial growth factor ≥ 302.90 pg/mL, glycosylated hemoglobin ≥ 9.05%, aqueous fluid interleukin 6 (IL-6) ≥ 53.27 pg/mL, and aqueous fluid IL-10 ≥ 9.11 pg/mL were independent risk factors for postoperative NVG in patients with DR ( < 0.05). A nomogram model was established based on the aforementioned independent risk factors, and a computer simulation repeated sampling method was used to internally and externally verify the nomogram model. The area under the curve (AUC), sensitivity, and specificity of the model were 0.962 [95% confidence interval (95%CI): 0.932-0.991], 91.5%, and 82.3%, respectively. The AUC, sensitivity, and specificity of the external validation were 0.878 (95%CI: 0.746-0.982), 66.7%, and 95.7%, respectively.
A nomogram constructed based on the risk factors for postoperative NVG in patients with DR has a high prediction accuracy. This study can help formulate relevant preventive and treatment measures.
部分糖尿病视网膜病变（DR）患者在接受玻璃体切除术后可能会发生新生血管性青光眼（NVG），从而降低预期疗效。目前临床研究需要了解NVG发生的危险因素并建立有效的风险预测模型。
建立视觉风险预测模型，以探索影响术后DR的因素。
回顾性选取151例接受玻璃体切除术的DR患者。根据术后6个月内NVG的发生情况，将患者分为NVG组（发生NVG）和非NVG组（未发生NVG）。采用逻辑回归筛选术后NVG的独立危险因素。使用R软件建立列线图预测模型，并通过受试者工作特征曲线和校正曲线对模型的预测准确性进行内部和外部验证。
将数据导入逻辑回归模型后，我们得出结论，后囊膜缺损、术前血管内皮生长因子≥302.90 pg/mL、糖化血红蛋白≥9.05%、房水白细胞介素6（IL-6）≥53.27 pg/mL和房水IL-10≥9.11 pg/mL是DR患者术后NVG的独立危险因素（<0.05）。基于上述独立危险因素建立列线图模型，并采用计算机模拟重复抽样方法对列线图模型进行内部和外部验证。模型的曲线下面积（AUC）、敏感性和特异性分别为0.962[95%置信区间（95%CI）：0.932-0.991]、91.5%和82.3%。外部验证的AUC、敏感性和特异性分别为0.878（95%CI：0.746-0.982）、66.7%和95.7%。
基于DR患者术后NVG危险因素构建的列线图具有较高的预测准确性。本研究有助于制定相关的防治措施。
