天津医药 ›› 2025, Vol. 53 ›› Issue (11): 1208-1213.doi: 10.11958/20251200

• 临床研究 • 上一篇    下一篇

老年糖尿病性白内障患者术源性散光的发生风险及预测模型建立

刘妍(), 孙红, 孙敬文()   

  1. 哈尔滨二四二医院眼科(邮编 150069)
  • 收稿日期:2025-04-01 修回日期:2025-07-15 出版日期:2025-11-15 发布日期:2025-11-19
  • 通讯作者: △E-mail: 2518222944@qq.com
  • 作者简介:刘妍(1990),女,主治医师,主要从事白内障诊治方面研究。E-mail:13704807741@163.com
  • 基金资助:
    黑龙江省卫生健康委科研课题(20220707020638)

Occurrence risk establishment of predictive mode of surgically induced astigmatism in elderly patients with diabetic cataract

LIU Yan(), SUN Hong, SUN Jingwen()   

  1. Department of Ophthalmology, Harbin 242 Hospital, Harbin 150069, China
  • Received:2025-04-01 Revised:2025-07-15 Published:2025-11-15 Online:2025-11-19
  • Contact: △E-mail: 2518222944@qq.com

摘要:

目的 构建并验证老年糖尿病性白内障患者术源性散光(SIA)风险预测列线图模型。方法 选取行白内障超声乳化术治疗的309例患者为研究对象。根据术后是否发生SIA,将患者分为SIA组(158例)和非SIA组(151例)。采用多因素Logistic回归分析影响糖尿病性白内障患者发生SIA的因素,构建SIA风险预测列线图模型,并采用受试者工作特征(ROC)曲线、校准曲线及决策曲线分析进行模型验证。结果 SIA组患者年龄、晶状体核硬度Ⅲ—Ⅳ级比例、切口大小≥3.00 mm比例、切口形状为梯形透明角膜切口比例、角膜切口长度≥1.75 mm比例及角膜水平直径均高于非SIA组(P<0.05);2组患者性别、体质量指数、糖尿病病程、有无高血压史、有无心血管疾病史、糖尿病视网膜病变分级、眼轴长度、前房深度、中央角膜厚度、全角膜屈光力、散光轴位、超声乳化时间差异均无统计学意义(P>0.05)。多因素Logistic回归分析显示,切口大小、切口形状、角膜切口长度及角膜水平直径是糖尿病性白内障患者发生SIA的影响因素(P<0.05);基于上述4个影响因素构建预测糖尿病性白内障患者发生SIA的列线图模型。ROC曲线分析显示,预测SIA的曲线下面积为0.810(95%CI:0.761~0.860);Hosmer-Lemeshow检验及校准曲线分析显示,该列线图模型拟合情况较好(χ2=11.142,P=0.194);决策曲线分析显示,当高风险阈值概率0.35~0.8时,模型的临床净获益率>0。结论 基于糖尿病性白内障患者发生SIA的因素构建的SIA风险预测列线图模型具有良好的区分度、校准度及临床实用性。

关键词: 白内障, 散光, 超声乳化白内障吸除术, 糖尿病, 列线图, 术源性散光

Abstract:

Objective To construct and verify the risk profile model of surgically induced astigmatism (SIA) in elderly patients with diabetic catarac. Methods A total of 309 patients admitted to our hospital for phacoemulsification were selected as the study objects. Patients were divided into the SIA group (n=158) and the non-SIA group (n=151) according to whether SIA occurred after surgery. Multivariate Logistic regression analysis was used to analyze the factors influencing the occurrence of SIA in diabetic cataract patients, and the nomogram model of SIA in diabetic cataract patients was constructed. ROC curve, calibration curve and decision curve were used for evaluation and verification of the model. Results The patient age and the lens nucleus hardness level Ⅲ-Ⅳ, incision size ≥3.00 mm, incision shape as trapezoidal transparent corneal incision, corneal incision length ≥1.75 mm and horizontal diameter of the cornea were significantly higher in the SIA group than of the non-SIA group (P<0.05). There were no significant differences in gender, body mass index (BMI), duration of diabetes, history of hypertension, history of cardiovascular disease, grading of diabetic retinopathy, axial length, anterior chamber depth, central corneal thickness, total corneal refractive power, astigmatism axis position and ultrasound phacoemulsification time between the two groups of patients (P>0.05). Multivariate Logistic regression results showed that incision size, incision shape, corneal incision length and corneal horizontal diameter were the factors affecting the occurrence of SIA in diabetic cataract patients (P<0.05). The R software was used to incorporate four influencing factors to generate a nomogram model that could be used to predict the occurrence of SIA in diabetic cataract patients. ROC curve analysis results showed that the area under the curve (AUC) value of this histogram to predict SIA in diabetic cataract patients was 0.810 (95%CI=0.761-0.860). Hosmer-Lemeshow test and calibration curve analysis showed that the model fit well (χ2=11.142, P=0.194). The results of decision curve analysis showed that when the probability of high risk threshold 0.35-0.8, the clinical net benefit rate of the column graph model was greater than 0. Conclusion Incision size, incision shape, corneal incision length and corneal horizontal diameter are influential factors for the occurrence of SIA in patients with diabetic cataract. Based on the above influential factors, the columniogram model for predicting the occurrence risk of SIA in patients with diabetic cataract has good differentiation, accuracy and clinical applicability.

Key words: cataract, astigmatism, phacoemulsification, diabetes mellitus, nomograms, operative astigmatism

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