Step no.
|
BL
|
BQ
|
k NN
|
LR
|
HS
|
DS
|
ANN1
|
ANN2
|
---|
1
|
O2ER
|
O2ER
|
Post-CI
|
O2ER
|
O2ER
|
SvO2
|
O2ER
|
O2ER
|
2
|
VCO2
|
DO2I
|
O2ER
|
VCO2
|
VCO2
|
Card-ID
|
Card-ID
|
VO2
|
3
|
Card-ID
|
Card-ID
|
Card-ID
|
Card-ID
|
Card-ID
|
DO2I
|
VO2
|
Card-ID
|
4
|
PVD
|
PVD
|
PVD
|
PVD
|
PVD
|
O2ER
|
PVD
|
PVD
|
5
|
TBU
|
W
|
TBU
|
TBU
|
TBU
|
PVD
|
TBU
|
Gly
|
6
|
EM
|
VD
|
MAP
|
EM
|
EM
|
O2ER
|
Pre-CI
|
Gender
|
7
|
Pre-CI
|
DAP
| |
SAP
|
SAP
|
EM
|
EM
|
MVR
|
8
|
WBC
|
SAP
| |
Pre-CI
|
Pre-CI
|
BSA
|
WBC
|
Cr
|
9
|
SAP
|
Diur
| |
WBC
|
WBC
|
AD
|
Age
|
AVO2
|
10
|
Age
|
Xclamp
| |
SaO2
|
SaO2
|
CHF
|
SaO2
|
Arrhy
|
11
|
PvO2
|
H
| |
PvO2
|
PvO2
|
MVR
|
AD
| |
12
|
SaO2
|
Gender
| |
AD
|
AD
|
O2ER
|
P/F
| |
13
|
AD
| | |
PaO2
|
PaO2
|
MR
|
PVS
| |
14
|
SvO2
| | |
Cr
|
Cr
|
EM
|
Temp
| |
15
|
Xclamp
| | |
CvO2
|
CvO2
|
Card-ID
| | |
16
|
PaO2
| | |
Xclamp
|
Xclamp
|
O2ER
| | |
17
|
[PvO2]
| | |
DO2I
|
DO2I
|
PVD
| | |
18
|
Cr
| | |
W
|
W
|
Diab
| | |
19
|
Intra-CI
| | |
SVRI
|
SVRI
|
VCO2
| | |
20
|
Post-CI
| | |
[VCO2]
|
[VCO2]
|
O2ER
| | |
21
|
[Age]
| | |
Pre-IABP
|
Pre-IABP
|
AD
| | |
22
|
W
| | |
CHF
|
CHF
|
O2ER
| | |
23
|
[Pre-CI]
| | |
[Xclamp]
|
[Xclamp]
|
CHF
| | |
24
|
DO2I
| | | | |
CABG-C
| | |
25
|
[VCO2]
| | | | |
MR
| | |
26
|
Bil
| | | | |
PAH
| | |
27
|
Hb
| | | | |
O2ER
| | |
28
|
[WBC]
| | | | |
IABP
| | |
29
|
SVRI
| | | | |
O2ER
| | |
30
|
[Post-CI]
| | | | |
IABP
| | |
31
|
BSA
| | | | |
O2ER
| | |
32
|
CABG-A
| | | | |
PVS
| | |
33
| | | | | |
IABP
| | |
34
| | | | | |
O2ER
| | |
35
| | | | | |
IABP
| | |
- BL, Bayes linear model; BQ, Bayes quadratic model; k NN, k-nearest neighbour model; LR, logistic regression model; HS, Higgins score system; DS, direct score system; ANN1, one-layer artificial neural network; ANN2, two-layer artificial neural network. Predictor variable abbreviations are indicated in Tables 1-6.