Table 9. Evaluation of logistic regression in non-cervical cohort only (Wald test) and leave-one-out cross-validation (LOOCV).

Model: $l={\beta }_0+{\beta }_{11}{x}_1+{\beta }_{12}{x}_1^2+{\beta }_2{x}_2+{\beta }_3{x}_3+{\beta }_4{x}_4+{\beta }_5{x}_5+{\beta }_6{x}_6+{\beta }_7{x}_7+{\beta }_8{x}_8+{\beta }_9{x}_9$, where $x_1:$ average MAP; $x_2$ : average HR; $x_3:$ length of surgery (min); $x_4:$ days to AIS discharge (days); $x_5:$ age; $x_6:$ AIS admission D (‘yes’,’no’); $x_7:$ AIS admission C (‘yes’,’no’); $x_8:$ AIS admission B (‘yes’,’no’); $x_9:$ AIS admission A (‘yes’,’no’); (AIS admission E was set as the reference level for AIS admission variable and is part of the intercept) (final n = 93)
LOOCV: average observed accuracy = 0.688; average kappa statistic = 0.362
Predictor	Coef. estimate (logit)	Std. error	z-Value	p-Value
Intercept	${\beta }_0$= –1.883	352.4	–0.005	0.996
Average MAP ($x_1$)	${\beta }_{11}$= –0.206	4.713	–0.044	0.965
Average MAP ($x_1^2$)	${\beta }_{12}$= –8.064	7.643	–1.055	0.291
Average HR ($x_2$)	${\beta }_2$= –0.0002	0.0649	0.004	0.997
Length of surgery ($x_3$)	${\beta }_3$= 0.0018	0.0054	0.336	0.737
Days to AIS discharge ($x_4$)	${\beta }_4$= 0.076	0.0613	1.240	0.215
Age ($x_5$)	${\beta }_5$= –0.0047	0.051	–0.921	0.357
AIS admission D ($x_6$)	${\beta }_6$= 1.727	3.524	0.005	0.996
AIS admission C ($x_7$)	${\beta }_7$= 3.557	5.782	0.005	0.996
AIS admission B ($x_8$)	${\beta }_8$= 1.738	3.524	0.005	0.995
AIS admission A ($x_9$)	${\beta }_9$= 1.686	3.524	0.005	0.996