data<-read.csv("C:/R_work/ECMO905.csv")
head(data)
Unit.number Name Sex Age Date Year Holiday Insertion.time
1 `08243022 이영순 1 49 20090511 2009 1 1
2 13034861 윤기정 1 77 20090518 2009 1 NA
3 14186610 임지현 1 33 20090722 2009 1 1
4 14340394 이수맹 0 67 20091007 2009 1 1
5 10870744 김창길 0 56 20100212 2010 1 0
6 11071670 이영익 0 67 20100217 2010 1 0
ECMO.duration Death Height Weight BMI Diagnosis Smoking CAD CVA PAD
1 8 1 NA NA NA Myocarditis 2 1 1 1
2 24 0 NA NA NA ACS 2 1 1 1
3 8 2 NA NA NA ARDS 2 1 1 1
4 15 0 NA NA NA ACS 0 0 1 1
5 5 0 1.65 68 29.76 ACS 2 1 1 1
6 2 0 1.70 65 26.37 ARDS 2 1 1 1
DM HBP Indication Mode CA OHCA CPR.duration CA.ECMO.Time EKG Weaning
1 1 1 0 0 1 NA NA NA 2 0
2 1 0 0 0 1 NA NA NA 2 0
3 1 1 1 1 1 NA NA NA 2 0
4 0 0 0 0 0 1 37 37 0 0
5 1 0 0 0 0 1 25 25 0 1
6 1 1 1 1 0 1 210 210 2 1
Vent Intu.day HD ICU.stay CRRT CRRT.duration CAG PCI GCS Bleeding
1 0 8 30 11 0 8 1 1 15 1
2 0 27 31 31 1 NA 0 1 5 1
3 0 27 28 28 1 NA 1 1 15 0
4 0 17 17 17 0 13 0 0 3 1
5 0 5 5 5 0 3 0 0 3 1
6 0 3 43 3 1 NA 1 1 12 1
Tamponade Pulmo AKI Liver.failure MOF Sepsis Stroke Leg.ischemia WBC
1 1 1 0 1 1 1 1 1 16400
2 1 1 0 1 1 1 1 1 5230
3 1 0 1 1 0 0 1 1 18030
4 1 0 0 1 0 1 1 1 9670
5 1 1 0 1 1 1 1 1 10930
6 1 1 0 1 1 0 1 1 17950
Hct PLT Sodium K Lactate PH HCO3 BUN Cr Glucose Albumin
1 43.0 248 143.2 3.9 10.6 7.20 15.9 20.1 2.3 184 4.7
2 30.1 154 143.2 3.1 NA 7.49 22.0 6.3 1.0 153 4.2
3 37.8 55 148.9 3.4 NA 7.59 23.3 22.3 1.3 150 3.1
4 36.0 54 144.8 3.4 NA 7.26 9.0 20.1 1.5 56 2.2
5 44.8 293 136.8 3.2 NA 7.18 13.4 15.9 1.5 200 2.5
6 22.3 70 143.2 6.5 NA 7.14 10.9 48.9 2.5 488 1.6
Total..bilirubin CRP D.dimer CK.MB Troponin PRC FFP PC Cryo
1 1.1 0.31 2.29 30.95 3.050 5 3 72 0
2 0.5 1.03 NA 3.97 0.298 22 7 61 0
3 1.1 8.22 11.28 219.50 1.300 4 19 40 0
4 0.5 13.34 1.03 8.91 0.088 35 9 136 0
5 0.6 0.07 NA 3.47 0.020 10 0 18 0
6 0.3 23.27 0.44 4.38 0.036 24 5 42 0
data1=data[data$Death<2,-c(1,2,5)]
data1$Survive=ifelse(data1$Death==0,0,1)
table(data1$Death)
0 1
51 22
library(compareGroups)
data1$Sex=ifelse(data1$Sex==1,"Female","Male")
data1$Holiday=ifelse(data1$Holiday==1,"Not Holiday","Holiday")
data1$Insertion.time=ifelse(data1$Insertion.time==1,"Emergency","Elective")
data1$Death=ifelse(data1$Death==1,"Survivor","Non-survivor")
data1$Smoking=ifelse(data1$Smoking==1,"No","Yes")
data1$CAD=ifelse(data1$CAD==1,"No","Yes")
data1$CVA=ifelse(data1$CVA==1,"No","Yes")
data1$PAD=ifelse(data1$PAD==1,"No","Yes")
data1$DM=ifelse(data1$DM==1,"No","Yes")
data1$HBP=ifelse(data1$HBP==1,"No","Yes")
data1$Indication=ifelse(data1$Indication==1,"Respiratory","Cardiology")
data1$Mode=ifelse(data1$Mode==1,"VV","VA")
data1$CA=ifelse(data1$CA==1,"No","Yes")
data1$OHCA=ifelse(data1$OHCA==1,"IHCA","OHCA")
data1$EKG=ifelse(data1$EKG==0,"Asystole",
ifelse(data1$EKG==1,"PEA","ETC"))
data1$Weaning=ifelse(data1$Weaning==1,"Fail","Success")
data1$Vent=ifelse(data1$Vent==1,"No","Yes")
data1$CRRT=ifelse(data1$CRRT==1,"No","Yes")
data1$CAG=ifelse(data1$CAG==1,"No","Yes")
data1$PCI=ifelse(data1$PCI==1,"No","Yes")
data1$Bleeding=ifelse(data1$Bleeding==1,"No","Yes")
data1$Tamponade=ifelse(data1$Tamponade==1,"No","Yes")
data1$Pulmo=ifelse(data1$Pulmo==1,"No","Yes")
data1$AKI=ifelse(data1$AKI==1,"No","Yes")
data1$Liver.failure=ifelse(data1$Liver.failure==1,"No","Yes")
data1$MOF=ifelse(data1$MOF==1,"No","Yes")
data1$Sepsis=ifelse(data1$Sepsis==1,"No","Yes")
data1$Stroke=ifelse(data1$Stroke==1,"No","Yes")
data1$Leg.ischemia=ifelse(data1$Leg.ischemia==1,"No","Yes")
mosaicplot(~Year+Death,data=data1,color=TRUE,main="Distribution of ECMO")
res=compareGroups(Survive~.,data=data1)
res
-------- Summary of results by groups of 'Survive'---------
var N p.value method selection
1 Sex 73 0.812 categorical ALL
2 Age 73 0.034** continuous normal ALL
3 Year 73 0.026** continuous normal ALL
4 Holiday 73 1.000 categorical ALL
5 Insertion.time 72 0.729 categorical ALL
6 ECMO.duration 73 0.170 continuous normal ALL
7 Death 73 <0.001** categorical ALL
8 Height 64 0.684 continuous normal ALL
9 Weight 66 0.910 continuous normal ALL
10 BMI 64 0.629 continuous normal ALL
11 Diagnosis 73 0.175 categorical ALL
12 Smoking 73 0.476 categorical ALL
13 CAD 73 0.320 categorical ALL
14 CVA 73 1.000 categorical ALL
15 PAD 73 . categorical ALL
16 DM 73 0.196 categorical ALL
17 HBP 73 0.188 categorical ALL
18 Indication 73 0.747 categorical ALL
19 Mode 73 0.747 categorical ALL
20 CA 73 0.132 categorical ALL
21 OHCA 38 1.000 categorical ALL
22 CPR.duration 38 0.065* continuous normal ALL
23 CA.ECMO.Time 38 0.074* continuous normal ALL
24 EKG 73 0.041** categorical ALL
25 Weaning 73 <0.001** categorical ALL
26 Vent 73 0.088* categorical ALL
27 HD 73 <0.001** continuous normal ALL
28 ICU.stay 73 <0.001** continuous normal ALL
29 CRRT 73 0.243 categorical ALL
30 CRRT.duration 29 0.175 continuous normal ALL
31 CAG 73 0.231 categorical ALL
32 PCI 73 0.476 categorical ALL
33 GCS 73 0.002** continuous normal ALL
34 Bleeding 73 0.578 categorical ALL
35 Tamponade 73 1.000 categorical ALL
36 Pulmo 73 0.714 categorical ALL
37 AKI 73 0.342 categorical ALL
38 Liver.failure 73 0.308 categorical ALL
39 MOF 73 0.029** categorical ALL
40 Sepsis 73 1.000 categorical ALL
41 Stroke 73 0.088* categorical ALL
42 Leg.ischemia 73 0.579 categorical ALL
43 WBC 73 0.632 continuous normal ALL
44 Hct 73 0.604 continuous normal ALL
45 PLT 73 0.429 continuous normal ALL
46 Sodium 73 0.441 continuous normal ALL
47 K 73 0.017** continuous normal ALL
48 Lactate 48 0.046** continuous normal ALL
49 PH 73 0.103 continuous normal ALL
50 HCO3 73 0.048** continuous normal ALL
51 BUN 73 0.018** continuous normal ALL
52 Cr 73 0.004** continuous normal ALL
53 Glucose 72 0.392 continuous normal ALL
54 Albumin 73 0.676 continuous normal ALL
55 Total..bilirubin 73 0.532 continuous normal ALL
56 CRP 73 0.161 continuous normal ALL
57 D.dimer 49 0.796 continuous normal ALL
58 CK.MB 64 0.829 continuous normal ALL
59 Troponin 62 0.556 continuous normal ALL
60 PRC 72 0.219 continuous normal ALL
61 FFP 72 0.381 continuous normal ALL
62 PC 72 0.087* continuous normal ALL
63 Cryo 72 0.787 continuous normal ALL
-----
Signif. codes: 0 '**' 0.05 '*' 0.1 ' ' 1
createTable(res)
--------Summary descriptives table by 'Survive'---------
_________________________________________________________
0 1 p.overall
N=51 N=22
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Sex: 0.812
Female 20 (39.2%) 10 (45.5%)
Male 31 (60.8%) 12 (54.5%)
Age 63.6 (13.6) 53.3 (19.7) 0.034
Year 2012 (1.41) 2013 (1.44) 0.026
Holiday: 1.000
Holiday 7 (13.7%) 3 (13.6%)
Not Holiday 44 (86.3%) 19 (86.4%)
Insertion.time: 0.729
Elective 28 (56.0%) 14 (63.6%)
Emergency 22 (44.0%) 8 (36.4%)
ECMO.duration 6.86 (6.52) 8.73 (4.61) 0.170
Death: <0.001
Non-survivor 51 (100%) 0 (0.00%)
Survivor 0 (0.00%) 22 (100%)
Height 1.64 (0.08) 1.62 (0.19) 0.684
Weight 60.6 (8.69) 60.2 (14.5) 0.910
BMI 26.7 (3.50) 26.2 (4.04) 0.629
Diagnosis: 0.175
ACS 26 (51.0%) 5 (22.7%)
ARDS 8 (15.7%) 5 (22.7%)
Drug Intoxication 1 (1.96%) 0 (0.00%)
LA myxoma 1 (1.96%) 0 (0.00%)
Myocarditis 2 (3.92%) 4 (18.2%)
PTE 4 (7.84%) 4 (18.2%)
Pump failure 5 (9.80%) 2 (9.09%)
Trauma 1 (1.96%) 1 (4.55%)
VF, VT 3 (5.88%) 1 (4.55%)
Smoking: 0.476
No 6 (11.8%) 4 (18.2%)
Yes 45 (88.2%) 18 (81.8%)
CAD: 0.320
No 40 (78.4%) 20 (90.9%)
Yes 11 (21.6%) 2 (9.09%)
CVA: 1.000
No 48 (94.1%) 21 (95.5%)
Yes 3 (5.88%) 1 (4.55%)
PAD: No 51 (100%) 22 (100%) .
DM: 0.196
No 35 (68.6%) 19 (86.4%)
Yes 16 (31.4%) 3 (13.6%)
HBP: 0.188
No 27 (52.9%) 16 (72.7%)
Yes 24 (47.1%) 6 (27.3%)
Indication: 0.747
Cardiology 42 (82.4%) 17 (77.3%)
Respiratory 9 (17.6%) 5 (22.7%)
Mode: 0.747
VA 42 (82.4%) 17 (77.3%)
VV 9 (17.6%) 5 (22.7%)
CA: 0.132
No 21 (41.2%) 14 (63.6%)
Yes 30 (58.8%) 8 (36.4%)
OHCA: 1.000
IHCA 26 (86.7%) 7 (87.5%)
OHCA 4 (13.3%) 1 (12.5%)
CPR.duration 33.4 (37.2) 16.9 (15.0) 0.065
CA.ECMO.Time 112 (224) 35.2 (16.3) 0.074
EKG: 0.041
Asystole 15 (29.4%) 1 (4.55%)
ETC 33 (64.7%) 20 (90.9%)
PEA 3 (5.88%) 1 (4.55%)
Weaning: <0.001
Fail 43 (84.3%) 0 (0.00%)
Success 8 (15.7%) 22 (100%)
Vent: 0.088
No 0 (0.00%) 2 (9.09%)
Yes 51 (100%) 20 (90.9%)
HD 15.0 (15.6) 41.8 (17.3) <0.001
ICU.stay 9.92 (9.44) 19.7 (9.61) <0.001
CRRT: 0.243
No 28 (54.9%) 16 (72.7%)
Yes 23 (45.1%) 6 (27.3%)
CRRT.duration 5.78 (4.65) 9.17 (5.00) 0.175
CAG: 0.231
No 23 (45.1%) 14 (63.6%)
Yes 28 (54.9%) 8 (36.4%)
PCI: 0.476
No 36 (70.6%) 18 (81.8%)
Yes 15 (29.4%) 4 (18.2%)
GCS 6.88 (4.25) 10.7 (4.51) 0.002
Bleeding: 0.578
No 32 (62.7%) 16 (72.7%)
Yes 19 (37.3%) 6 (27.3%)
Tamponade: 1.000
No 48 (94.1%) 21 (95.5%)
Yes 3 (5.88%) 1 (4.55%)
Pulmo: 0.714
No 44 (86.3%) 20 (90.9%)
Yes 7 (13.7%) 2 (9.09%)
AKI: 0.342
No 27 (52.9%) 15 (68.2%)
Yes 24 (47.1%) 7 (31.8%)
Liver.failure: 0.308
No 47 (92.2%) 22 (100%)
Yes 4 (7.84%) 0 (0.00%)
MOF: 0.029
No 35 (68.6%) 21 (95.5%)
Yes 16 (31.4%) 1 (4.55%)
Sepsis: 1.000
No 45 (88.2%) 19 (86.4%)
Yes 6 (11.8%) 3 (13.6%)
Stroke: 0.088
No 51 (100%) 20 (90.9%)
Yes 0 (0.00%) 2 (9.09%)
Leg.ischemia: 0.579
No 49 (96.1%) 20 (90.9%)
Yes 2 (3.92%) 2 (9.09%)
WBC 13814 (8323) 13009 (5637) 0.632
Hct 34.3 (7.27) 35.3 (7.98) 0.604
PLT 166 (100) 148 (78.2) 0.429
Sodium 142 (5.28) 141 (5.91) 0.441
K 4.36 (1.08) 3.93 (0.45) 0.017
Lactate 7.13 (5.48) 4.00 (4.52) 0.046
PH 7.24 (0.16) 7.32 (0.21) 0.103
HCO3 13.8 (5.12) 17.0 (6.54) 0.048
BUN 29.0 (17.7) 20.9 (10.3) 0.018
Cr 1.64 (1.23) 1.05 (0.41) 0.004
Glucose 209 (108) 192 (59.6) 0.392
Albumin 2.95 (0.86) 3.04 (0.78) 0.676
Total..bilirubin 1.21 (1.37) 1.42 (1.26) 0.532
CRP 6.19 (7.69) 9.78 (10.6) 0.161
D.dimer 9.86 (12.2) 8.94 (11.4) 0.796
CK.MB 36.8 (47.6) 33.0 (72.6) 0.829
Troponin 1.56 (3.52) 1.13 (2.17) 0.556
PRC 27.0 (27.6) 20.1 (18.2) 0.219
FFP 12.2 (14.3) 9.33 (11.4) 0.381
PC 54.6 (62.3) 35.0 (33.2) 0.087
Cryo 1.90 (4.88) 1.62 (3.61) 0.787
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data1$EKG1=ifelse(data1$EKG=="ETC","ETC", "Asystole/PEA")
head(data1)
Sex Age Year Holiday Insertion.time ECMO.duration Death
1 Female 49 2009 Not Holiday Emergency 8 Survivor
2 Female 77 2009 Not Holiday <NA> 24 Non-survivor
4 Male 67 2009 Not Holiday Emergency 15 Non-survivor
5 Male 56 2010 Not Holiday Elective 5 Non-survivor
6 Male 67 2010 Not Holiday Elective 2 Non-survivor
7 Male 76 2010 Not Holiday Elective 5 Non-survivor
Height Weight BMI Diagnosis Smoking CAD CVA PAD DM HBP Indication
1 NA NA NA Myocarditis Yes No No No No No Cardiology
2 NA NA NA ACS Yes No No No No Yes Cardiology
4 NA NA NA ACS Yes Yes No No Yes Yes Cardiology
5 1.65 68 29.76 ACS Yes No No No No Yes Cardiology
6 1.70 65 26.37 ARDS Yes No No No No No Respiratory
7 1.64 68 30.21 ACS No No No No Yes Yes Cardiology
Mode CA OHCA CPR.duration CA.ECMO.Time EKG Weaning Vent Intu.day
1 VA No <NA> NA NA ETC Success Yes 8
2 VA No <NA> NA NA ETC Success Yes 27
4 VA Yes IHCA 37 37 Asystole Success Yes 17
5 VA Yes IHCA 25 25 Asystole Fail Yes 5
6 VV Yes IHCA 210 210 ETC Fail Yes 3
7 VA No <NA> NA NA ETC Success Yes 9
HD ICU.stay CRRT CRRT.duration CAG PCI GCS Bleeding Tamponade Pulmo AKI
1 30 11 Yes 8 No No 15 No No No Yes
2 31 31 No NA Yes No 5 No No No Yes
4 17 17 Yes 13 Yes Yes 3 No No Yes Yes
5 5 5 Yes 3 Yes Yes 3 No No No Yes
6 43 3 No NA No No 12 No No No Yes
7 12 12 No NA Yes Yes 4 No No No No
Liver.failure MOF Sepsis Stroke Leg.ischemia WBC Hct PLT Sodium K
1 No No No No No 16400 43.0 248 143.2 3.9
2 No No No No No 5230 30.1 154 143.2 3.1
4 No Yes No No No 9670 36.0 54 144.8 3.4
5 No No No No No 10930 44.8 293 136.8 3.2
6 No No Yes No No 17950 22.3 70 143.2 6.5
7 No Yes No No No 6790 40.1 173 140.5 3.8
Lactate PH HCO3 BUN Cr Glucose Albumin Total..bilirubin CRP
1 10.6 7.20 15.9 20.1 2.3 184 4.7 1.1 0.31
2 NA 7.49 22.0 6.3 1.0 153 4.2 0.5 1.03
4 NA 7.26 9.0 20.1 1.5 56 2.2 0.5 13.34
5 NA 7.18 13.4 15.9 1.5 200 2.5 0.6 0.07
6 NA 7.14 10.9 48.9 2.5 488 1.6 0.3 23.27
7 NA 7.29 14.9 15.8 0.9 178 3.8 1.1 0.29
D.dimer CK.MB Troponin PRC FFP PC Cryo Survive EKG1
1 2.29 30.95 3.050 5 3 72 0 1 ETC
2 NA 3.97 0.298 22 7 61 0 0 ETC
4 1.03 8.91 0.088 35 9 136 0 0 Asystole/PEA
5 NA 3.47 0.020 10 0 18 0 0 Asystole/PEA
6 0.44 4.38 0.036 24 5 42 0 0 ETC
7 NA 17.70 0.674 14 0 46 0 0 ETC
boxplot(K~Survive,data=data1)
boxplot(PH~Survive,data=data1)
boxplot(HCO3~Survive,data=data1)
data2=data1[data1$EKG1=="ETC",]
data3=data1[data1$EKG1!="ETC",]
cor.test(data1$K,data1$PH)
Pearson's product-moment correlation
data: data1$K and data1$PH
t = -0.9558, df = 71, p-value = 0.3424
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.3341 0.1205
sample estimates:
cor
-0.1127
cor.test(data1$K,data1$HCO3)
Pearson's product-moment correlation
data: data1$K and data1$HCO3
t = -1.81, df = 71, p-value = 0.07445
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.41985 0.02101
sample estimates:
cor
-0.2101
model=glm(Survive~Age+DM+GCS+CA.ECMO.Time+K+HCO3+PH+Cr+CRP+EKG1,data=data1)
summary(model)
Call:
glm(formula = Survive ~ Age + DM + GCS + CA.ECMO.Time + K + HCO3 +
PH + Cr + CRP + EKG1, data = data1)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.450 -0.221 -0.100 0.122 0.920
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.409608 2.898546 1.52 0.140
Age -0.004126 0.004533 -0.91 0.371
DMYes -0.004492 0.154742 -0.03 0.977
GCS 0.013508 0.016248 0.83 0.413
CA.ECMO.Time -0.000605 0.000354 -1.71 0.098 .
K -0.062913 0.080790 -0.78 0.443
HCO3 0.007142 0.019483 0.37 0.717
PH -0.543038 0.414999 -1.31 0.202
Cr -0.054469 0.078921 -0.69 0.496
CRP 0.009290 0.009752 0.95 0.349
EKG1ETC 0.318728 0.162452 1.96 0.060 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.1479)
Null deviance: 6.3158 on 37 degrees of freedom
Residual deviance: 3.9928 on 27 degrees of freedom
(35 observations deleted due to missingness)
AIC: 46.22
Number of Fisher Scoring iterations: 2
model1=glm(Survive~Age+GCS+CA.ECMO.Time+K+HCO3+EKG1,data=data1)
summary(model1)
Call:
glm(formula = Survive ~ Age + GCS + CA.ECMO.Time + K + HCO3 +
EKG1, data = data1)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.5290 -0.2085 -0.0846 0.0814 0.9116
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.694469 0.434642 1.60 0.120
Age -0.004996 0.004297 -1.16 0.254
GCS 0.013879 0.014841 0.94 0.357
CA.ECMO.Time -0.000546 0.000343 -1.59 0.121
K -0.100673 0.056008 -1.80 0.082 .
HCO3 0.006385 0.015027 0.42 0.674
EKG1ETC 0.295827 0.144800 2.04 0.050 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.1424)
Null deviance: 6.3158 on 37 degrees of freedom
Residual deviance: 4.4159 on 31 degrees of freedom
(35 observations deleted due to missingness)
AIC: 42.05
Number of Fisher Scoring iterations: 2
model2=glm(Survive~Age+GCS+CA.ECMO.Time+K+EKG1,data=data1)
summary(model2)
Call:
glm(formula = Survive ~ Age + GCS + CA.ECMO.Time + K + EKG1,
data = data1)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.5078 -0.1894 -0.0880 0.0692 0.9243
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.783343 0.376098 2.08 0.045 *
Age -0.005103 0.004234 -1.21 0.237
GCS 0.013207 0.014566 0.91 0.371
CA.ECMO.Time -0.000550 0.000338 -1.63 0.114
K -0.102079 0.055190 -1.85 0.074 .
EKG1ETC 0.303278 0.141882 2.14 0.040 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.1388)
Null deviance: 6.3158 on 37 degrees of freedom
Residual deviance: 4.4416 on 32 degrees of freedom
(35 observations deleted due to missingness)
AIC: 40.27
Number of Fisher Scoring iterations: 2
model3=glm(Survive~Age+GCS+K,data=data1)
summary(model3)
Call:
glm(formula = Survive ~ Age + GCS + K, data = data1)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.634 -0.260 -0.125 0.325 0.855
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.00046 0.30839 3.24 0.0018 **
Age -0.00857 0.00293 -2.92 0.0047 **
GCS 0.03591 0.01024 3.51 0.0008 ***
K -0.11078 0.05012 -2.21 0.0304 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.162)
Null deviance: 15.370 on 72 degrees of freedom
Residual deviance: 11.177 on 69 degrees of freedom
AIC: 80.18
Number of Fisher Scoring iterations: 2
anova(model2,model1,model,test="Chisq")
Analysis of Deviance Table
Model 1: Survive ~ Age + GCS + CA.ECMO.Time + K + EKG1
Model 2: Survive ~ Age + GCS + CA.ECMO.Time + K + HCO3 + EKG1
Model 3: Survive ~ Age + DM + GCS + CA.ECMO.Time + K + HCO3 + PH + Cr +
CRP + EKG1
Resid. Df Resid. Dev Df Deviance Pr(>Chi)
1 32 4.44
2 31 4.42 1 0.026 0.68
3 27 3.99 4 0.423 0.58
kmodel=glm(Survive~K,data=data1)
summary(kmodel)
Call:
glm(formula = Survive ~ K, data = data1)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.490 -0.336 -0.253 0.623 0.747
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.7380 0.2442 3.02 0.0035 **
K -0.1031 0.0563 -1.83 0.0712 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.2067)
Null deviance: 15.370 on 72 degrees of freedom
Residual deviance: 14.676 on 71 degrees of freedom
AIC: 96.06
Number of Fisher Scoring iterations: 2
plot(Survive~K,data=data1)
plot(Survive~K,data=data2)
plot(Survive~K,data=data3)
curve(predict(kmodel,data.frame(K=x),type="resp"),add=TRUE,col="blue",lty=3)
predict.data = seq(3,8,0.1)
y=plogis(kmodel$coefficients[1]+kmodel$coefficient[2]*predict.data)
xy=data.frame(K=predict.data)
yhat=predict(kmodel,xy,type="link",se.fit=TRUE)
yhat
$fit
1 2 3 4 5 6 7
0.428538 0.418224 0.407909 0.397594 0.387279 0.376964 0.366650
8 9 10 11 12 13 14
0.356335 0.346020 0.335705 0.325391 0.315076 0.304761 0.294446
15 16 17 18 19 20 21
0.284131 0.273817 0.263502 0.253187 0.242872 0.232558 0.222243
22 23 24 25 26 27 28
0.211928 0.201613 0.191298 0.180984 0.170669 0.160354 0.150039
29 30 31 32 33 34 35
0.139725 0.129410 0.119095 0.108780 0.098465 0.088151 0.077836
36 37 38 39 40 41 42
0.067521 0.057206 0.046891 0.036577 0.026262 0.015947 0.005632
43 44 45 46 47 48 49
-0.004682 -0.014997 -0.025312 -0.035627 -0.045942 -0.056256 -0.066571
50 51
-0.076886 -0.087201
$se.fit
1 2 3 4 5 6 7 8 9
0.08748 0.08308 0.07883 0.07478 0.07093 0.06734 0.06405 0.06109 0.05853
10 11 12 13 14 15 16 17 18
0.05642 0.05481 0.05374 0.05325 0.05335 0.05404 0.05530 0.05709 0.05936
19 20 21 22 23 24 25 26 27
0.06206 0.06514 0.06854 0.07222 0.07614 0.08027 0.08457 0.08901 0.09359
28 29 30 31 32 33 34 35 36
0.09827 0.10305 0.10792 0.11285 0.11784 0.12290 0.12799 0.13314 0.13832
37 38 39 40 41 42 43 44 45
0.14353 0.14878 0.15405 0.15935 0.16466 0.17000 0.17536 0.18073 0.18612
46 47 48 49 50 51
0.19153 0.19694 0.20237 0.20781 0.21326 0.21872
$residual.scale
[1] 0.4547
upperlogit=yhat$fit+1.96*yhat$se.fit
lowerlogit=yhat$fit-1.96*yhat$se.fit
ucl=plogis(upperlogit)
lcl=plogis(lowerlogit)
plot(predict.data,y,type="l",ylim=c(0,1),ylab="Predicted probability of survival",xlab="K")
lines(predict.data,ucl,lty=2,lwd=2)
lines(predict.data,lcl,lty=2,lwd=2)
