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