白内障患者术后晶状体后囊膜混浊发生风险的列线图预测模型构建OA

Objective To construct a nomogram prediction model for the risk of posterior capsular opacification(PCO)after cataract surgery.Methods Totally 364 cataract patients who underwent surgery at our hospital between Jan-uary 2022 and June 2023 were enrolled.Patients were followed up for 2 years postoperatively and divided into the PCO group(n=61)and non-PCO group(n=303)based on PCO occurrence.Lasso-Logistic regression was used to screen pre-dictive variables,construct a nomogram model,and assess its predictive performance.Results The incidence of postoper-ative PCO in the 364 patients was 16.76％(61/364).Lasso-Logistic regression analysis revealed that high myopia(OR=2.844,P=0.002),concomitant diabetes mellitus(OR=2.564,P=0.004),glaucoma(OR=2.588,P=0.029),hydrophilic in-traocular lens implantation(OR=3.595,P＜0.001),and no posterior capsular polishing(OR=2.690,P=0.002)were inde-pendent risk factors for postoperative PCO.The nomogram model constructed based on these five indicators yielded an area under the receiver operating characteristic curve of 0.759(95％CI:0.696-0.822).The calibration curve had a slope close to 1,and the Hosmer-Lemeshow goodness-of-fit test showedx2=7.140,P=0.308.Conclusion High myopia,concomitant diabetes mellitus,glaucoma,hydrophilic intraocular lens implantation,and no posterior capsular polishing are independent risk factors for postoperative PCO after cataract surgery.The nomogram prediction model developed using these indicators has good predictive performance and facilitates early identification and individualized intervention of PCO.