Statistical analysis
diabetic vitrectomy, Low vision
REGRESSION, LOW VISION, LOW VISION
Low vision was defined as a BCVA<0.3, according to the standard of the WHO 2015 (The multivariate binary logistic regression analysis considered variables with a P-value<0.1 from the univariate analysis, and stepwise forward regression was used to explore variables with a P-value<0.05 as potential independent predictors. The variance inflation factor was calculated to test for multicollinearity amongst the independent variables. In accordance with the outcomes of the multivariate logistic regression analysis, a nomogram for estimating the probability of long-term low vision after diabetic vitrectomy was built.The discrimination capacities of the predictive indicators were described using receiver operating characteristic (ROC) curves. Generally, a value >0.7 of the area under the ROC curve (AUC) is considered to indicate good discrimination. The threshold of the equation was determined by the maximum Youden Index (sensitivity + specificity - 1). The calibration was tested and depicted using the Hosmer-Lemeshow test and calibration curves. The nomogram was internally validated using the bootstrapping approach, and it was externally validated in an external cohort. All statistics were analyzed using IBM SPSS Statistics ver. 25.0 (SPSS, Chicago, IL, USA) and R software ver. 4.0.1 (R Project for Statistical Computing, Vienna, Austria). A two-sided P-value of<0.05 was considered statistically significant.