摘要
Abstract
Objective To investigate the independent risk factors for early-onset cataract(EOC)and construct a no-mogram prediction model for its occurrence.Methods A case-control study was conducted,including 82 EOC patients(EOC group)and 140 non-EOC patients(non-EOC group)from the Department of Ophthalmology at Jiangyou People's Hospital between January 2021 and June 2025.The patients' general information,ophthalmic examination indicators,blood biochemical indicators,and questionnaire data were collected.Lasso regression and multivariate logistic regression were used to analyze and screen independent risk factors,and a nomogram model was constructed.Internal validation was per-formed using the Bootstrap method to evaluate the model's discrimination,calibration,and clinical applicability.Results The EOC group had significantly higher body mass index,diabetes prevalence,daily screen time ≥ 6 hours,fasting blood glu-cose,glycated hemoglobin,C-reactive protein,triglyceride,low-density lipoprotein cholesterol levels,and glucocorticoid use compared to the non-EOC group(all P＜0.05).Multivariate logistic regression analysis identified high body mass index(OR=1.28,95％CI:1.05-1.57),diabetes history(OR=2.04,95％CI:1.18-3.54),daily screen time ≥6 hours(OR=1.82,95％CI:1.30-2.55),elevated C-reactive protein(OR=2.33,95％CI:1.66-3.27),elevated low-density lipoprotein cholesterol(OR=1.71,95％CI:1.19-2.47),and long-term glucocorticoid use(OR=2.95,95％CI:1.60-5.44)as inde-pendent risk factors for EOC.The nomogram model achieved a C-index of 0.856,and the calibration curve showed good consistency.Conclusion This study identifies multiple independent risk factors for EOC and successfully constructs a nomogram model with good predictive performance,which may serve as a practical tool for early screening and risk stratifi-cation of EOC.关键词
早发性白内障/危险因素/列线图/预测模型/Logistic回归Key words
early-onset cataract/risk factors/nomogram/prediction model/Logistic regression分类
医药卫生
