Fig 1.
The flow chart of this study.
Table 1.
The baseline characteristics of all patients.
Fig 2.
Association between SIRI and AKI using a restricted cubic spline regression model in the training set.
Fig 3.
The waterfall plots and forest plots of the high-SIRI group and low-SIRI group for AKI in pediatric patients.
The waterfall plot of SIRI for each patient of AKI in the training set (A), in the validation set (B), and the subgroup analysis of the SIRI for AKI in pediatric patients in both sets (C).
Table 2.
Logistic regression analysis of high SIRI and low SIRI group for AKI.
Fig 4.
The waterfall plots and forest plots of the high-SIRI group and low-SIRI group for in-hospital mortality in pediatric patients.
The waterfall plot of SIRI for each patient of in-hospital mortality in the training set (A), in the validation set (B), and the subgroup analysis of the SIRI for in-hospital mortality in pediatric patients in both sets (C).
Fig 5.
The SIRI was established to detect the in-hospital mortality of patients in pediatric intensive care units in the training set.
All patients were distinguished into high and low risk based on the SIRI (A), the relationship between survival time and prognosis of patients in the two corresponding groups (B), and the heatmap of other markers between the two groups (C). Receiver operating characteristic (ROC) curve analysis of the SIRI for overall mortality (D), Decision curve analysis of the risk score for the overall mortality (E). Kaplan-Meier curves show the overall mortality of groups with different risks (F).
Table 3.
Clinical outcomes analysis of high and low SIRI groups for all patients.
Table 4.
COX regression analysis of high SIRI and low SIRI group for in-hospital mortality.
Fig 6.
Selection of significant factors associated with AKI in pediatric patients by LASSO regression model.
Fig 7.
The established nomogram for AKI in pediatric patients (A), The calibration curves (B), and the decision curve analysis (C) of the nomogram for AKI in the training set and the validation set.
Table 5.
Logistic regression analysis for the factors of AKI selected by LASSO regression in the training set.