Table 8. Evaluation of logistic regression in Cervical cohort (Wald test) and leave-one-out cross-validation (LOOCV).

Model: $l={\beta }_0+{\beta }_{11}{x}_1+{\beta }_{12}{x}_1^2+{\beta }_2{x}_2+{\beta }_3{x}_3+{\beta }_4{x}_4+{\beta }_5{x}_5+{\beta }_6{x}_6+{\beta }_7{x}_7+{\beta }_8{x}_8$, 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’); (AIS admission A was set as the reference level for AIS admission variable and is part of the intercept, no AIS admission E was present in this cohort) (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	${\beta }_0$= 2.747	3.018	0.91	0.363
Average MAP ($x_1$)	${\beta }_{11}$= 7.594	3.056	2.485	0.013*
Average MAP ($x_1^2$)	${\beta }_{12}$= –7.528	3.358	–2.242	0.025*
Average HR ($x_2$)	${\beta }_2$= –0.055	0.034	–1.608	0.108
Length of surgery ($x_3$)	${\beta }_3$= 0.0014	0.0019	0.720	0.472
Days to AIS discharge ($x_4$)	${\beta }_4$= 0.0022	0.012	0.182	0.855
Age ($x_5$)	${\beta }_5$= 0.0079	0.016	0.482	0.630
AIS admission D ($x_6$)	${\beta }_6$= –0.747	0.87	–0.840	0.730
AIS admission C ($x_7$)	${\beta }_7$= 0.745	0.80	0.925	0.355
AIS admission B ($x_8$)	${\beta }_8$= 0.301	0.88	0.346	0.401

*p < 0.05.