2.6 Statistical analyses
Categorical variables are expressed as percentages, and continuous variables are expressed as mean (SD) or median (IQR). Differences in baseline characteristics, and laboratory measures between groups were assessed using Chi square test, or Mann-Whitney U test, as appropriate. In the univariate logistic regression analysis, variables associated with a high risk of high DSI (P <0.05) were introduced into the multivariate model. The collinearity between the final model variables was evaluated using the variance inflation factor (VIF). VIF ≤ 5 signified the absence of collinearity between the final model variables. Nomogram were generated based on the results of multivariate logistic regression on the dependent variable using the ’rms’ package in R software (version 4.2.1). In addition, we used the bootstrapping method with 1000 resamples to conduct internal validation. The discriminative power of the model was assessed using the consistency index (C-index), and the goodness of fit is shown in the calibration plot. Statistical analyses were performed using R software (version 4.2.1). P value of <0.05 was considered statistically significant.
RESULTS