Statistical analysis
REGRESSION
SPSS software (version 26.0, SPSS Inc., IBM, Chicago, IL, USA) was used for statistical analysis of the data. Quantitative variables are expressed as the mean ± standard deviation (SD) or median (25th percentile; 75th percentile) and were compared by independent t test or a nonparametric test (Mann–Whitney). Categorical variables are expressed as numbers (percentages) and were compared by the chi-square test. P < 0.05 was considered statistically significant. The variables that met the criteria in univariate analysis were introduced into multivariate stepwise logistic regression to construct a prediction model in the training set. Both univariate analysis and multivariate analysis showed that P < 0.05 was significantly different. The accuracy of the model for the diagnosis of HRS was evaluated by the area under the ROC curve (AUC). Welch-corrected t-test was used to analyze the model values of the HRS group and the non-HRS group in the training set, the validation set and the whole population. P < 0.05 indicated that the difference was statistically significant.