Li Jinglan, Li Xuanlong, Lei Mingxing, Li Wanyue, Chen Wenqian, Ma Tianju, Gao Yi, Ye Zi, Li Zhaohui
Medical School of Chinese PLA, Beijing, China.
Department of Ophthalmology, The First Medical Centre, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, China.
Diabetol Metab Syndr. 2022 Aug 26;14(1):124. doi: 10.1186/s13098-022-00892-z.
As one of the severe complications of diabetes mellitus, diabetic retinopathy (DR) is the leading cause of blindness in the working age worldwide. Although panretinal photocoagulation (PRP) was standard treatment, PRP-treated DR still has a high risk of progression. Hence, this study aimed to assess the risk factors and establish a model for predicting worsening diabetic retinopathy (DR-worsening) within five years after PRP.
Patients who were diagnosed with severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy and treated with PRP were included, and those patients were randomly assigned to either a training or validation cohort. The multivariate logistic regression analysis was used to screen potential risk factors for DR-worsening in the training cohort. Then the model was established after including significant independent risk factors and further validated using discrimination and calibration.
A total of 271 patients were included, and 56.46% of patients had an outcome of DR-worsening. In the training cohort (n = 135), age (odds ratio [OR] = 0.94, 95% confidence interval [CI] 0.90-0.98), baseline best corrected visual acuity (logMAR) (OR = 10.74, 95% CI 1.84-62.52), diabetic nephropathy (OR = 9.32, 95% CI 1.49-58.46), and hyperlipidemia (OR = 3.34, 95% CI 1.05-10.66) were screened out as the independent risk factors, which were incorporated into the predictive model. The area under the receiver operating characteristic curve and calibration slope in the training and validation cohort were 0.79, 0.96 (95% CI 0.60-1.31), and 0.79, 1.00 (95% CI 0.66-1.34), respectively. Two risk groups were developed depending on the best cut-off value of the predicted probability, and the actual probability was 34.90% and 82.79% in the low-risk and high-risk groups, respectively (P < 0.001).
This study developed and internally validated a new model to predict the probability of DR-worsening after PRP treatment within five years. The model can be used as a rapid risk assessment system for clinical prediction of DR-worsening and identify individuals at a high risk of DR-worsening at an early stage and prescribe additional treatment.
作为糖尿病的严重并发症之一，糖尿病视网膜病变（DR）是全球工作年龄段人群失明的主要原因。尽管全视网膜光凝（PRP）是标准治疗方法，但接受PRP治疗的DR患者仍有较高的病情进展风险。因此，本研究旨在评估风险因素，并建立一个模型来预测PRP治疗后五年内糖尿病视网膜病变病情恶化（DR恶化）的情况。
纳入诊断为重度非增殖性糖尿病视网膜病变或增殖性糖尿病视网膜病变并接受PRP治疗的患者，并将这些患者随机分配到训练队列或验证队列。采用多因素逻辑回归分析在训练队列中筛选DR恶化的潜在风险因素。然后纳入显著的独立风险因素建立模型，并通过区分度和校准进行进一步验证。
共纳入271例患者，56.46%的患者出现DR恶化结局。在训练队列（n = 135）中，年龄（比值比[OR]=0.94，95%置信区间[CI]0.90 - 0.98）、基线最佳矫正视力（logMAR）（OR = 10.74，95%CI 1.84 - 62.52）、糖尿病肾病（OR = 9.32，95%CI 1.49 - 58.46）和高脂血症（OR = 3.34，95%CI 1.05 - 10.66）被筛选为独立风险因素，并纳入预测模型。训练队列和验证队列中受试者工作特征曲线下面积和校准斜率分别为0.79、0.96（95%CI 0.60 - 1.31）和0.79、1.00（95%CI 0.66 - 1.34）。根据预测概率的最佳截断值分为两个风险组，低风险组和高风险组的实际概率分别为34.90%和82.79%（P < 0.001）。
本研究开发并内部验证了一个新模型，用于预测PRP治疗后五年内DR恶化的概率。该模型可作为一种快速风险评估系统，用于临床预测DR恶化，并在早期识别DR恶化高风险个体并给予额外治疗。
