目的：建立纳入血清铁蛋白的列线图模型预测糖尿病视网膜病变的发生，并评估该模型。

方法：通过单因素和多因素回归分析，筛选出包括铁蛋白在内的21个变量，确定了糖尿病视网膜病变的危险因素。建立列线图预测模型进行评估和校准。

结果：列线图模型纳入了铁蛋白、糖尿病病程、血红蛋白、尿微量白蛋白、用药规律性以及体重指数等6个变量。纳入血清铁蛋白的预测模型一致性指数为0.813(95%CI：0.748-0.879)。内外部验证的校准曲线表现良好，决策曲线提示阈值概率范围在10%-90%之间，该模型具有较高的净收益值。

结论：血清铁蛋白是糖尿病视网膜病变发生的重要危险因素。一种新的列线图模型，包括体重指数、糖尿病病程、铁蛋白、血红蛋白、尿微量白蛋白、用药规律性，具有较高的预测准确性，可为临床医生提供早期预判。

METHODS:A total of 21 variables, including ferritin, were screened by univariate and multivariate regression analysis to determine the risk factors of diabetic retinopathy. A nomogram prediction model was established for evaluation and calibration.

RESULTS:Ferritin, duration of diabetes, hemoglobin, urine microalbumin, regularity of medication and body mass index were included in the nomogram model. The consistency index of the prediction model with serum ferritin was 0.813(95%CI: 0.748-0.879). The calibration curves of internal and external verification showed good performance, and the probability of the threshold suggested by the decision curve was in the range 10% to 90%. The model had a high net profit value.

CONCLUSIONS:Serum ferritin is an important risk factor for diabetic retinopathy. A new nomogram model, which includes body mass index, duration of diabetes, ferritin, hemoglobin, urine microalbumin and regularity of medication, has a high predictive accuracy and could provide early prediction for clinicians.