Establishment and validation of a prognostic nomogram for long-term low vision after diabetic vitrectomy - Guo, Haoxin; Wang, Zhaoxiong; Nie, Zetong; Zhang, Xiang; Wang, Kuan; Duan, Naxin; Bai, Siqiong; Li, Wenbo; Li, Xiaorong; Hu, Bojie (Frontiers in Endocrinology, 2023)
Purpose: We aimed to evaluate the risk factors and develop a prognostic nomogram of long-term low vision after diabetic vitrectomy. Methods: This retrospective study included 186 patients (250 eyes) that underwent primary vitrectomy for proliferative diabetic retinopathy with a minimum follow-up period of one year. Patients were assigned to the training cohort (200 eyes) or validation cohort (50 eyes) at a 4:1 ratio randomly. Based on a cutoff value of 0.3 in best-corrected visual acuity (BCVA) measurement, the training cohort was separated into groups with or without low vision. Univariate and multivariate logistic regression analyses were performed on preoperative systemic and ocular characteristics to develop a risk prediction model and nomogram. The calibration curve and the area under the receiver operating characteristic curves (AUC) were used to evaluate the calibration and discrimination of the model. The nomogram was internally validated using the bootstrapping method, and it was further verified in an external cohort. Results: Four independent risk factors were selected by stepwise forward regression, including tractional retinal detachment (β=1.443, OR=4.235, P<0.001), symptom duration ≥6 months (β=0.954, OR=2.595, P=0.004), preoperative BCVA measurement (β=0.540, OR=1.716, P=0.033), and hypertension (β=0.645, OR=1.905, P=0.044). AUC values of 0.764 (95% CI: 0.699-0.829) in the training cohort and 0.755 (95% CI: 0.619-0.891) in the validation cohort indicated the good predictive ability of the model. Conclusion: The prognostic nomogram established in this study is useful for predicting long-term low vision after diabetic vitrectomy.