Table 2:

Comparison of Model Performances for Predicting Favorable Neurological Outcome at Discharge Based on Various Strategies for Constructing Derivation and Validation Data

Model	Split-by-time study design (AUC, 95%CI)	Split-by-site study design (AUC, 95%CI)	Split-by-random study design (AUC, 95%CI)
CASPRI	0.73 (0.73-0.74)	0.74 (0.74-0.75)*	0.74 (0.74-0.75)*
SVM	0.78 (0.78-0.79)	0.79 (0.79-0.79)	0.79 (0.78-0.79)
LR	0.79 (0.79-0.80)	0.79 (0.79-0.80)	0.80 (0.79-0.80)
RF	0.79 (0.79-0.79)	0.79 (0.79-0.80)	0.80 (0.79-0.81)
MLP	0.80 (0.80-0.80)	0.80 (0.80-0.80)	0.81 (0.80-0.81)
XGBoost	0.81 (0.80-0.81)	0.81 (0.81-0.81)	0.81 (0.80-0.81)

^*Potential data leakage: the test data in the split-by-site and the split-by-random study design may include observations before 2009, which was used to derive the CASPRI model

AUC: Area Under the receiver operating characteristic Curve

CI: Confidence Interval

CASPRI: Cardiac Arrest Survival Post-Resuscitation In-hospital score

SVM: Support Vector Machine

LR: Logistic Regression

RF: Random Forest

MLP: Multi-Layer Perceptron

XGBoost: eXtreme Gradient Boosted machine