河北医科大学学报 ›› 2025, Vol. 46 ›› Issue (7): 818-825.doi: 10.3969/j.issn.1007-3205.2025.07.012

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非动脉炎性前部缺血性视神经病变对侧眼发病的临床预测模型建立

  

  1. 1.河北医科大学第二医院眼科，河北 石家庄 050000；2.河北省眼科医院眼科，河北 邢台 054001；3.河北医科大学
    第二医院转化医学中心，河北 石家庄 050000；4.河北医科大学第二医院教务处，河北 石家庄050000

  • 出版日期:2025-07-25 发布日期:2025-07-24
  • 作者简介:郭从容（1975-），女，河北石家庄人，河北医科大学第二医院副主任医师，医学博士，从事眼科疾病诊治研究。

  • 基金资助:
    河北省自然科学基金资助项目（H2023206905）

Establishment of a clinical prediction model for the onset of contralateral eye in non-arteritic anterior ischemic optic neuropathy

  1. 1.Department of Ophthalmology, the Second Hospital of Hebei Medical University, Shijiazhuang 050000, 
    China; 2.Department of Ophthalmology, Hebei Eye Hospital, Xingtai 054001, China; 3.Department of 
    Translational Science, the Second Hospital of Hebei Medical University, Shijiazhuang 050000, 
    China; 4.Department of Academic Affairs, the Second Hospital of 
    Hebei Medical University, Shijiazhuang 050000,China

  • Online:2025-07-25 Published:2025-07-24

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摘要： 目的 探讨非动脉炎性前部缺血性视神经病变（non-arteritic anterior ischemic optic neuropathy,NAION）对侧眼发病的危险因素，构建临床预测模型并进行评估。
方法 选择2018年10月—2021年12月于河北医科大学第二医院眼病中心住院诊治的NAION患者151例，随访至2022年12月，获取其临床资料，统计对侧眼的发病情况。采用最小绝对收缩选择算子(least absolute shrinkage and selection operator,LASSO)回归分析方法和K折（本研究为10折）交叉验证来筛选预测因子，应用多因素Logistic回归分析建立预测模型。采用受试者工作特征(receiver operating characteristic,ROC)曲线，Hosmer-Lemeshow检验，决策曲线分析（decision curve analysis,DCA）评价预测模型及临床实用度。
结果 通过LASSO回归分析，从23个变量中确定了9个预测因子，即年龄（Age）、入院视力（V1）、脑梗死（急性缺血性卒中）（acute ischemic stroke，AIS）、糖尿病（diabetes mellitus，DM）、空腹血糖（fasting blood-glucose,FBG）、高血压(high blood pressure，HBP)、总胆固醇（total cholesterol，TC）、对侧眼有无埋藏性视盘玻璃膜疣（optic disc drusen,ODD）、杯盘比（cup/disc ratio，C/D）。用这9个预测因子构建的模型显示出良好的预测能力，ROC曲线下面积为0.85，Hosmer-Lemeshow检验（P=0.239）。DCA曲线表明，当模型中的患者的风险阈值在5%~94%之间时，可从此模型中获益，提示此模型具有较高的临床应用价值。
结论 DM、HBP、TC、ODD和小C/D是NAION患者对侧眼发病的独立危险因素。年龄、入院视力、AIS和FBG水平与NAION对侧眼发病密切相关，据此建立预测模型具有良好的预测效能。


关键词: 视神经病变, 缺血性, 危险因素, 临床预测模型

Abstract: Objective To explore the risk factors for the onset of contralateral eye in non-arteritic anteritic anterior ischemic optic neuropathy (NAION), and to construct clinical prediction models for evaluation. 
Methods A total of 151 patients with NAION who were hospitalized in the Eye Center of the Second Hospital of Hebei Medical University from October 2018 to December 2021 were included in the study.The follow-up period was ended until December 2022 to obtain their clinical data and calculate the NAION incidence of the contralateral eye. The Least absolute shrinkage and selection operator (LASSO) regression analysis method and K-fold (10-fold in this study) Cross-validation were used to screen the predictive factors, and Multivariate logistic regression analysis was used to construct a prediction model. The receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test, decision curve analysis (DCA) were used to evaluate the prediction model and its clinical practicability. 
Results Nine predictive factors were identified from 23 variables, namely age, visual acuity at admission (V1), acute ischemic stroke (AIS), diabetes mellitus (DM), fasting blood-glucose (FBG), high blood pressure (HBP), total cholesterol (TC), optic disc drusen (ODD) in the contralateral eye, and cup/disc ratio (C/D) by the LASSO regression analysis. The prediction model constructed with the 9 predictors showed good predictive ability, with area under the ROC of 0.85, using Hosmer-Lemeshow test (P=0.239). In the DCA, when the risk threshold of patients in the model ranged from 5% to 94%, patients could benefit from this model, indicating that the model had high clinical application value. 
Conclusion DM, HBP, TC, ODD, small C/D are independent risk factors for the onset of contralateral eye of NAION patients. Age, V1, AIS, and FBG levels are closely associated with the onset of contralateral eye of NAION patients. Thus, the prediction model based on this has good predictive efficacy. 


Key words: optic neuropathy, ischemic, risk factors, clinical prediction model

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