ECMO
tnskadl2
Friday, August 29, 2014
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data<-read.csv("C:/R_work/ECMO5.csv",header=T)head(data)## Unit.number Name Sex Age Date Year Holiday Insertion.time
## 1 759044 여옥자 1 72 20130413 2013 0 0
## 2 16389573 남숙재 0 78 20121121 2012 1 1
## 3 15639671 이혜원 1 20 20110917 2011 0 0
## 4 16923465 최준택 0 55 20131026 2013 0 1
## 5 13412734 라길주 0 67 20100323 2010 1 1
## 6 6778542 이원희 1 75 20111214 2011 1 1
## ECMO.duration Death Height Weight BMI Diagnosis Smoking CAD CVA PAD
## 1 24 0 1.57 60.85 29.97 ACS 2 0 1 1
## 2 1 0 1.55 52.30 26.51 Pump failure 0 0 1 1
## 3 19 1 1.62 54.00 24.72 Pump failure 2 1 1 1
## 4 2 0 NA NA NA ACS 2 1 1 1
## 5 14 0 1.65 60.00 26.26 ACS 2 1 1 1
## 6 2 0 1.50 45.00 24.49 ACS 2 1 1 1
## DM HBP Liver.dz Lung.dz Indication Mode CA OHCA CPR.duration
## 1 0 0 1 1 0 0 1 NA NA
## 2 1 0 1 1 0 0 0 1 11
## 3 1 1 1 1 0 0 0 1 8
## 4 1 1 1 1 0 0 0 1 20
## 5 0 0 1 1 0 0 1 NA NA
## 6 1 1 1 1 0 0 1 NA NA
## CA.ECMO.Time EKG Weaning Vent Intubation..day Hospital.day ICU.stay CRRT
## 1 NA 2 0 0 27 42 27 1
## 2 11 1 1 0 1 3 1 1
## 3 50 2 0 0 35 50 38 1
## 4 20 0 1 0 0 0 0 0
## 5 NA 2 0 0 19 20 20 1
## 6 NA 2 1 0 2 4 4 1
## CRRT.duration CAG PCI GCS Bleeding Tamponade Pulmo AKI Liver.failure MOF
## 1 NA 0 1 10 1 1 1 1 1 0
## 2 NA 0 1 3 1 1 1 1 1 1
## 3 NA 1 1 15 0 1 1 1 1 1
## 4 1 1 1 4 0 1 1 0 1 1
## 5 NA 0 1 3 0 1 1 1 1 0
## 6 NA 0 1 15 1 0 1 1 1 1
## Sepsis Stroke Nerve.injury Leg.ischemia WBC Hct PLT Sodium K BUN
## 1 0 1 1 1 12510 31.4 175 139.2 4.0 27.8
## 2 1 1 1 1 19470 32.2 193 142.1 4.5 34.8
## 3 1 1 0 0 10890 32.5 214 136.0 4.0 7.1
## 4 1 1 1 1 9210 35.1 125 151.6 4.0 8.8
## 5 0 1 1 1 18230 26.5 334 139.2 4.1 49.9
## 6 1 1 1 1 15670 36.2 154 150.5 3.0 40.1
## Cr Glucose Albumin Total..bilirubin CRP D.dimer CK.MB Troponin PRC
## 1 1.1 372 2.6 1.0 2.19 NA 27.170 1.240 150
## 2 1.0 103 3.5 1.0 17.54 NA 3.010 NA 0
## 3 0.8 236 3.6 0.6 0.06 1.58 0.704 0.010 50
## 4 0.7 409 2.1 0.3 0.02 17.00 123.000 1.760 43
## 5 1.3 230 4.1 0.5 7.24 4.97 84.460 9.410 42
## 6 1.2 310 3.5 0.7 15.95 1.67 246.900 0.079 38
## FFP PC Cryo
## 1 39 202 0
## 2 0 0 0
## 3 23 146 0
## 4 18 10 8
## 5 5 170 0
## 6 11 20 10str(data)## 'data.frame': 78 obs. of 67 variables:
## $ Unit.number : Factor w/ 78 levels "`08243022","10279578",..: 63 40 29 50 11 62 27 7 48 43 ...
## $ Name : Factor w/ 76 levels "강신윤","강신훈",..: 34 16 53 69 17 47 28 15 74 57 ...
## $ Sex : int 1 0 1 0 0 1 0 1 1 0 ...
## $ Age : int 72 78 20 55 67 75 2 61 48 71 ...
## $ Date : int 20130413 20121121 20110917 20131026 20100323 20111214 20140117 20140414 20130910 20130307 ...
## $ Year : int 2013 2012 2011 2013 2010 2011 2014 2014 2013 2013 ...
## $ Holiday : int 0 1 0 0 1 1 1 1 1 1 ...
## $ Insertion.time : int 0 1 0 1 1 1 0 0 1 0 ...
## $ ECMO.duration : num 24 1 19 2 14 2 9 11 8 6 ...
## $ Death : int 0 0 1 0 0 0 1 1 1 0 ...
## $ Height : num 1.57 1.55 1.62 NA 1.65 1.5 0.91 1.52 NA 1.7 ...
## $ Weight : num 60.9 52.3 54 NA 60 ...
## $ BMI : num 30 26.5 24.7 NA 26.3 ...
## $ Diagnosis : Factor w/ 9 levels "ACS","ARDS","Drug Intoxication",..: 1 7 7 1 1 1 2 2 2 2 ...
## $ Smoking : int 2 0 2 2 2 2 2 2 2 2 ...
## $ CAD : int 0 0 1 1 1 1 1 1 1 1 ...
## $ CVA : int 1 1 1 1 1 1 1 1 1 1 ...
## $ PAD : int 1 1 1 1 1 1 1 1 1 1 ...
## $ DM : int 0 1 1 1 0 1 1 1 1 0 ...
## $ HBP : int 0 0 1 1 0 1 1 1 1 1 ...
## $ Liver.dz : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Lung.dz : int 1 1 1 1 1 1 0 0 1 1 ...
## $ Indication : int 0 0 0 0 0 0 1 1 1 1 ...
## $ Mode : int 0 0 0 0 0 0 1 1 1 1 ...
## $ CA : int 1 0 0 0 1 1 1 1 0 1 ...
## $ OHCA : int NA 1 1 1 NA NA NA NA 1 NA ...
## $ CPR.duration : int NA 11 8 20 NA NA NA NA 2 NA ...
## $ CA.ECMO.Time : int NA 11 50 20 NA NA NA NA 57 NA ...
## $ EKG : int 2 1 2 0 2 2 2 2 2 2 ...
## $ Weaning : int 0 1 0 1 0 1 0 0 0 1 ...
## $ Vent : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Intubation..day : Factor w/ 29 levels "","0","1","10",..: 17 3 20 2 11 12 25 7 6 26 ...
## $ Hospital.day : int 42 3 50 0 20 4 38 38 42 14 ...
## $ ICU.stay : int 27 1 38 0 20 4 8 17 19 9 ...
## $ CRRT : int 1 1 1 0 1 1 1 0 1 0 ...
## $ CRRT.duration : int NA NA NA 1 NA NA NA 4 NA 2 ...
## $ CAG : int 0 0 1 1 0 0 1 1 1 1 ...
## $ PCI : int 1 1 1 1 1 1 1 1 1 1 ...
## $ GCS : int 10 3 15 4 3 15 6 15 7 10 ...
## $ Bleeding : int 1 1 0 0 0 1 0 1 1 1 ...
## $ Tamponade : int 1 1 1 1 1 0 1 1 1 1 ...
## $ Pulmo : int 1 1 1 1 1 1 0 1 1 1 ...
## $ AKI : int 1 1 1 0 1 1 1 0 1 1 ...
## $ Liver.failure : int 1 1 1 1 1 1 1 1 1 1 ...
## $ MOF : int 0 1 1 1 0 1 1 1 1 1 ...
## $ Sepsis : int 0 1 1 1 0 1 1 1 1 1 ...
## $ Stroke : int 1 1 1 1 1 1 0 1 1 1 ...
## $ Nerve.injury : int 1 1 0 1 1 1 1 1 1 1 ...
## $ Leg.ischemia : int 1 1 0 1 1 1 1 1 1 1 ...
## $ WBC : int 12510 19470 10890 9210 18230 15670 18190 7610 13350 6580 ...
## $ Hct : num 31.4 32.2 32.5 35.1 26.5 36.2 19.4 37.8 26.4 27 ...
## $ PLT : int 175 193 214 125 334 154 72 129 313 62 ...
## $ Sodium : num 139 142 136 152 139 ...
## $ K : num 4 4.5 4 4 4.1 3 4 3.5 3.6 3.6 ...
## $ BUN : num 27.8 34.8 7.1 8.8 49.9 40.1 27.2 8.7 20.4 15.8 ...
## $ Cr : num 1.1 1 0.8 0.7 1.3 1.2 0.4 0.7 0.7 0.8 ...
## $ Glucose : int 372 103 236 409 230 310 157 134 205 184 ...
## $ Albumin : num 2.6 3.5 3.6 2.1 4.1 3.5 1.8 2.8 2.2 2.5 ...
## $ Total..bilirubin: num 1 1 0.6 0.3 0.5 0.7 0.3 1.3 2.5 1.2 ...
## $ CRP : num 2.19 17.54 0.06 0.02 7.24 ...
## $ D.dimer : num NA NA 1.58 17 4.97 ...
## $ CK.MB : num 27.17 3.01 0.704 123 84.46 ...
## $ Troponin : num 1.24 NA 0.01 1.76 9.41 0.079 NA 0.234 0.413 0.028 ...
## $ PRC : int 150 0 50 43 42 38 3 12 10 22 ...
## $ FFP : int 39 0 23 18 5 11 0 8 0 37 ...
## $ PC : int 202 0 146 10 170 20 10 36 8 54 ...
## $ Cryo : int 0 0 0 8 0 10 0 0 0 0 ...summary(data)## Unit.number Name Sex Age
## `08243022: 1 이영순 : 2 Min. :0.00 Min. : 2.0
## 10279578 : 1 이영화 : 2 1st Qu.:0.00 1st Qu.:49.2
## 10870744 : 1 강신윤 : 1 Median :0.00 Median :63.0
## 11071670 : 1 강신훈 : 1 Mean :0.41 Mean :59.6
## 11144868 : 1 강정애 : 1 3rd Qu.:1.00 3rd Qu.:72.8
## 11620651 : 1 김기수 : 1 Max. :1.00 Max. :86.0
## (Other) :72 (Other):70
## Date Year Holiday Insertion.time
## Min. :20090511 Min. :2009 Min. :0.000 Min. :0.000
## 1st Qu.:20110644 1st Qu.:2011 1st Qu.:1.000 1st Qu.:0.000
## Median :20121116 Median :2012 Median :1.000 Median :0.000
## Mean :20120933 Mean :2012 Mean :0.859 Mean :0.416
## 3rd Qu.:20131028 3rd Qu.:2013 3rd Qu.:1.000 3rd Qu.:1.000
## Max. :20140804 Max. :2014 Max. :1.000 Max. :1.000
## NA's :1
## ECMO.duration Death Height Weight
## Min. : 0.2 Min. :0.000 Min. :0.91 Min. :11.5
## 1st Qu.: 2.0 1st Qu.:0.000 1st Qu.:1.60 1st Qu.:55.0
## Median : 6.0 Median :0.000 Median :1.65 Median :60.0
## Mean : 7.4 Mean :0.364 Mean :1.64 Mean :60.8
## 3rd Qu.:10.8 3rd Qu.:1.000 3rd Qu.:1.70 3rd Qu.:68.0
## Max. :24.0 Max. :2.000 Max. :1.83 Max. :80.0
## NA's :1 NA's :11 NA's :9
## BMI Diagnosis Smoking CAD
## Min. :12.5 ACS :34 Min. :0.00 Min. :0.000
## 1st Qu.:24.6 ARDS :14 1st Qu.:0.00 1st Qu.:1.000
## Median :27.1 PTE : 8 Median :2.00 Median :1.000
## Mean :26.8 Myocarditis : 7 Mean :1.32 Mean :0.795
## 3rd Qu.:29.1 Pump failure: 7 3rd Qu.:2.00 3rd Qu.:1.000
## Max. :33.5 VF, VT : 4 Max. :2.00 Max. :1.000
## NA's :11 (Other) : 4
## CVA PAD DM HBP
## Min. :0.000 Min. :1 Min. :0.000 Min. :0.00
## 1st Qu.:1.000 1st Qu.:1 1st Qu.:1.000 1st Qu.:0.00
## Median :1.000 Median :1 Median :1.000 Median :1.00
## Mean :0.949 Mean :1 Mean :0.756 Mean :0.59
## 3rd Qu.:1.000 3rd Qu.:1 3rd Qu.:1.000 3rd Qu.:1.00
## Max. :1.000 Max. :1 Max. :1.000 Max. :1.00
##
## Liver.dz Lung.dz Indication Mode
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:0.000 1st Qu.:0.000
## Median :1.000 Median :1.000 Median :0.000 Median :0.000
## Mean :0.962 Mean :0.923 Mean :0.192 Mean :0.192
## 3rd Qu.:1.000 3rd Qu.:1.000 3rd Qu.:0.000 3rd Qu.:0.000
## Max. :1.000 Max. :1.000 Max. :1.000 Max. :1.000
##
## CA OHCA CPR.duration CA.ECMO.Time
## Min. :0.000 Min. :0.00 Min. : 2.0 Min. : 0.0
## 1st Qu.:0.000 1st Qu.:1.00 1st Qu.: 10.8 1st Qu.: 19.5
## Median :0.000 Median :1.00 Median : 25.0 Median : 39.0
## Mean :0.487 Mean :0.88 Mean : 30.6 Mean : 92.3
## 3rd Qu.:1.000 3rd Qu.:1.00 3rd Qu.: 40.2 3rd Qu.: 48.5
## Max. :1.000 Max. :1.00 Max. :210.0 Max. :1080.0
## NA's :38 NA's :38 NA's :38
## EKG Weaning Vent Intubation..day
## Min. :0.00 Min. :0.000 Min. :0.0000 2 : 7
## 1st Qu.:1.00 1st Qu.:0.000 1st Qu.:0.0000 1 : 6
## Median :2.00 Median :1.000 Median :0.0000 3 : 6
## Mean :1.53 Mean :0.603 Mean :0.0385 4 : 6
## 3rd Qu.:2.00 3rd Qu.:1.000 3rd Qu.:0.0000 6 : 6
## Max. :2.00 Max. :2.000 Max. :1.0000 10 : 4
## (Other):43
## Hospital.day ICU.stay CRRT CRRT.duration
## Min. : 0.0 Min. : 0.0 Min. :0.000 Min. : 1.00
## 1st Qu.: 4.0 1st Qu.: 4.0 1st Qu.:0.000 1st Qu.: 3.00
## Median :18.0 Median : 9.0 Median :1.000 Median : 5.00
## Mean :22.5 Mean :12.7 Mean :0.603 Mean : 6.39
## 3rd Qu.:35.0 3rd Qu.:19.0 3rd Qu.:1.000 3rd Qu.: 8.00
## Max. :86.0 Max. :44.0 Max. :1.000 Max. :20.00
## NA's :1 NA's :1 NA's :47
## CAG PCI GCS Bleeding
## Min. :0.0 Min. :0.000 Min. : 3.00 Min. :0.000
## 1st Qu.:0.0 1st Qu.:0.000 1st Qu.: 4.00 1st Qu.:0.000
## Median :0.5 Median :1.000 Median : 7.00 Median :1.000
## Mean :0.5 Mean :0.718 Mean : 8.26 Mean :0.667
## 3rd Qu.:1.0 3rd Qu.:1.000 3rd Qu.:13.00 3rd Qu.:1.000
## Max. :1.0 Max. :1.000 Max. :15.00 Max. :1.000
##
## Tamponade Pulmo AKI Liver.failure
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:0.000 1st Qu.:1.000
## Median :1.000 Median :1.000 Median :1.000 Median :1.000
## Mean :0.949 Mean :0.872 Mean :0.577 Mean :0.949
## 3rd Qu.:1.000 3rd Qu.:1.000 3rd Qu.:1.000 3rd Qu.:1.000
## Max. :1.000 Max. :1.000 Max. :1.000 Max. :1.000
##
## MOF Sepsis Stroke Nerve.injury
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :1.000 Median :1.000 Median :1.000 Median :1.000
## Mean :0.769 Mean :0.859 Mean :0.962 Mean :0.962
## 3rd Qu.:1.000 3rd Qu.:1.000 3rd Qu.:1.000 3rd Qu.:1.000
## Max. :1.000 Max. :1.000 Max. :1.000 Max. :1.000
##
## Leg.ischemia WBC Hct PLT
## Min. :0.000 Min. : 610 Min. :18.1 Min. : 17.0
## 1st Qu.:1.000 1st Qu.: 8808 1st Qu.:30.7 1st Qu.: 97.5
## Median :1.000 Median :12330 Median :35.1 Median :144.5
## Mean :0.949 Mean :13493 Mean :34.8 Mean :162.1
## 3rd Qu.:1.000 3rd Qu.:16602 3rd Qu.:40.0 3rd Qu.:215.5
## Max. :1.000 Max. :48290 Max. :53.8 Max. :414.0
##
## Sodium K BUN Cr Glucose
## Min. :128 Min. :2.40 Min. : 6.3 Min. :0.40 Min. : 50
## 1st Qu.:139 1st Qu.:3.62 1st Qu.:15.6 1st Qu.:0.90 1st Qu.:136
## Median :141 Median :4.00 Median :20.4 Median :1.20 Median :182
## Mean :141 Mean :4.20 Mean :25.7 Mean :1.44 Mean :203
## 3rd Qu.:144 3rd Qu.:4.50 3rd Qu.:32.2 3rd Qu.:1.50 3rd Qu.:247
## Max. :157 Max. :7.60 Max. :88.9 Max. :8.30 Max. :488
## NA's :2
## Albumin Total..bilirubin CRP D.dimer
## Min. :1.40 Min. :0.30 Min. : 0.02 Min. : 0.05
## 1st Qu.:2.40 1st Qu.:0.50 1st Qu.: 0.43 1st Qu.: 1.21
## Median :2.95 Median :0.90 Median : 2.52 Median : 4.84
## Mean :3.03 Mean :1.24 Mean : 7.05 Mean : 9.84
## 3rd Qu.:3.77 3rd Qu.:1.40 3rd Qu.:13.34 3rd Qu.:15.34
## Max. :4.70 Max. :7.10 Max. :30.25 Max. :45.00
## NA's :1 NA's :1 NA's :26
## CK.MB Troponin PRC FFP
## Min. : 0.70 Min. : 0.010 Min. : 0.0 Min. : 0
## 1st Qu.: 3.01 1st Qu.: 0.034 1st Qu.: 8.0 1st Qu.: 0
## Median : 16.52 Median : 0.232 Median : 18.0 Median : 7
## Mean : 42.42 Mean : 1.430 Mean : 23.9 Mean :11
## 3rd Qu.: 40.55 3rd Qu.: 1.225 3rd Qu.: 31.0 3rd Qu.:17
## Max. :300.00 Max. :17.190 Max. :150.0 Max. :72
## NA's :9 NA's :12 NA's :1 NA's :1
## PC Cryo
## Min. : 0.0 Min. : 0.0
## 1st Qu.: 10.0 1st Qu.: 0.0
## Median : 32.0 Median : 0.0
## Mean : 47.1 Mean : 1.7
## 3rd Qu.: 60.0 3rd Qu.: 0.0
## Max. :240.0 Max. :20.0
## NA's :1 NA's :1data1=data[data$Death<2,-c(1,2,5)]data1$Survive=ifelse(data1$Death==0,0,1)hist(data1$Death,col="blue")
library(compareGroups)## Loading required package: Hmisc
## Loading required package: grid
## Loading required package: lattice
## Loading required package: survival
## Loading required package: splines
## Loading required package: Formula
##
## Attaching package: 'Hmisc'
##
## The following objects are masked from 'package:base':
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## format.pval, round.POSIXt, trunc.POSIXt, units
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## Loading required package: xtable
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## Attaching package: 'xtable'
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## The following objects are masked from 'package:Hmisc':
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## label, label<-
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## Loading required package: gdata
## gdata: Unable to locate valid perl interpreter
## gdata:
## gdata: read.xls() will be unable to read Excel XLS and XLSX files
## gdata: unless the 'perl=' argument is used to specify the location
## gdata: of a valid perl intrpreter.
## gdata:
## gdata: (To avoid display of this message in the future, please
## gdata: ensure perl is installed and available on the executable
## gdata: search path.)
## gdata: Unable to load perl libaries needed by read.xls()
## gdata: to support 'XLX' (Excel 97-2004) files.
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## gdata: Unable to load perl libaries needed by read.xls()
## gdata: to support 'XLSX' (Excel 2007+) files.
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## gdata: Run the function 'installXLSXsupport()'
## gdata: to automatically download and install the perl
## gdata: libaries needed to support Excel XLS and XLSX formats.
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## Attaching package: 'gdata'
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## The following object is masked from 'package:Hmisc':
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## combine
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## Loading required package: SNPassoc
## Loading required package: haplo.stats
## Loading required package: mvtnorm
## Loading required package: paralleldata1$Sex=ifelse(data1$Sex==1,"Female","Male")
data1$Death=ifelse(data1$Death==1,"Survivor","Non-survivor")
data1$DM=ifelse(data1$DM==1,"No","Yes")
data1$Holiday=ifelse(data1$Holiday==1,"No","Yes")
data1$Insertion.time=ifelse(data1$Insertion.time==1,"No","Yes")
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$HBP=ifelse(data1$HBP==1,"No","Yes")
data1$Liver.dz=ifelse(data1$Liver.dz==1,"No","Yes")
data1$Lung.dz=ifelse(data1$Lung.dz==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$Weaning=ifelse(data1$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$Nerve.injury=ifelse(data1$Nerve.injury==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)## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Some levels of 'Intubation..day' are removed since no observation in that/those levels
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Chi-squared approximation may be incorrect
## Warning: Variables 'PAD', 'Intubation..day' have been removed since some errors occurredres##
##
## -------- Summary of results by groups of 'Survive'---------
##
##
## var N p.value method selection
## 1 Sex 74 1.000 categorical ALL
## 2 Age 74 0.027** continuous normal ALL
## 3 Year 74 0.026** continuous normal ALL
## 4 Holiday 74 1.000 categorical ALL
## 5 Insertion.time 73 0.518 categorical ALL
## 6 ECMO.duration 74 0.352 continuous normal ALL
## 7 Death 74 <0.001** categorical ALL
## 8 Height 64 0.743 continuous normal ALL
## 9 Weight 66 0.959 continuous normal ALL
## 10 BMI 64 0.720 continuous normal ALL
## 11 Diagnosis 74 0.363 categorical ALL
## 12 Smoking 74 0.723 categorical ALL
## 13 CAD 74 0.529 categorical ALL
## 14 CVA 74 1.000 categorical ALL
## 15 DM 74 0.211 categorical ALL
## 16 HBP 74 0.161 categorical ALL
## 17 Liver.dz 74 0.550 categorical ALL
## 18 Lung.dz 74 1.000 categorical ALL
## 19 Indication 74 0.746 categorical ALL
## 20 Mode 74 0.746 categorical ALL
## 21 CA 74 0.115 categorical ALL
## 22 OHCA 39 1.000 categorical ALL
## 23 CPR.duration 39 0.055* continuous normal ALL
## 24 CA.ECMO.Time 39 0.076* continuous normal ALL
## 25 EKG 74 0.002** continuous normal ALL
## 26 Weaning 74 <0.001** categorical ALL
## 27 Vent 74 0.024** categorical ALL
## 28 Hospital.day 74 <0.001** continuous normal ALL
## 29 ICU.stay 74 0.001** continuous normal ALL
## 30 CRRT 74 0.269 categorical ALL
## 31 CRRT.duration 29 0.175 continuous normal ALL
## 32 CAG 74 0.203 categorical ALL
## 33 PCI 74 0.675 categorical ALL
## 34 GCS 74 0.001** continuous normal ALL
## 35 Bleeding 74 0.374 categorical ALL
## 36 Tamponade 74 1.000 categorical ALL
## 37 Pulmo 74 0.422 categorical ALL
## 38 AKI 74 0.376 categorical ALL
## 39 Liver.failure 74 0.311 categorical ALL
## 40 MOF 74 0.002** categorical ALL
## 41 Sepsis 74 1.000 categorical ALL
## 42 Stroke 74 0.297 categorical ALL
## 43 Nerve.injury 74 0.024** categorical ALL
## 44 Leg.ischemia 74 0.577 categorical ALL
## 45 WBC 74 0.643 continuous normal ALL
## 46 Hct 74 0.537 continuous normal ALL
## 47 PLT 74 0.493 continuous normal ALL
## 48 Sodium 74 0.503 continuous normal ALL
## 49 K 74 0.018** continuous normal ALL
## 50 BUN 74 0.013** continuous normal ALL
## 51 Cr 74 0.004** continuous normal ALL
## 52 Glucose 72 0.532 continuous normal ALL
## 53 Albumin 74 0.634 continuous normal ALL
## 54 Total..bilirubin 73 0.521 continuous normal ALL
## 55 CRP 73 0.198 continuous normal ALL
## 56 D.dimer 48 0.859 continuous normal ALL
## 57 CK.MB 65 0.797 continuous normal ALL
## 58 Troponin 63 0.494 continuous normal ALL
## 59 PRC 74 0.187 continuous normal ALL
## 60 FFP 74 0.338 continuous normal ALL
## 61 PC 74 0.074* continuous normal ALL
## 62 Cryo 74 0.753 continuous normal ALL
## -----
## Signif. codes: 0 '**' 0.05 '*' 0.1 ' ' 1createTable(res)##
## --------Summary descriptives table by 'Survive'---------
##
## _________________________________________________________
## 0 1 p.overall
## N=52 N=22
## <U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF>
## Sex: 1.000
## Female 20 (38.5%) 9 (40.9%)
## Male 32 (61.5%) 13 (59.1%)
## Age 63.8 (13.6) 52.9 (20.0) 0.027
## Year 2012 (1.40) 2013 (1.44) 0.026
## Holiday: 1.000
## No 44 (84.6%) 19 (86.4%)
## Yes 8 (15.4%) 3 (13.6%)
## Insertion.time: 0.518
## No 22 (43.1%) 7 (31.8%)
## Yes 29 (56.9%) 15 (68.2%)
## ECMO.duration 6.75 (6.51) 8.01 (4.65) 0.352
## Death: <0.001
## Non-survivor 52 (100%) 0 (0.00%)
## Survivor 0 (0.00%) 22 (100%)
## Height 1.64 (0.08) 1.63 (0.19) 0.743
## Weight 60.6 (8.69) 60.8 (14.6) 0.959
## BMI 26.7 (3.50) 26.4 (4.07) 0.720
## Diagnosis: 0.363
## ACS 27 (51.9%) 6 (27.3%)
## ARDS 8 (15.4%) 5 (22.7%)
## Drug Intoxication 1 (1.92%) 0 (0.00%)
## LA myxoma 1 (1.92%) 0 (0.00%)
## Myocarditis 2 (3.85%) 3 (13.6%)
## PTE 4 (7.69%) 4 (18.2%)
## Pump failure 5 (9.62%) 2 (9.09%)
## Trauma 1 (1.92%) 1 (4.55%)
## VF, VT 3 (5.77%) 1 (4.55%)
## Smoking: 0.723
## No 7 (13.5%) 4 (18.2%)
## Yes 45 (86.5%) 18 (81.8%)
## CAD: 0.529
## No 40 (76.9%) 19 (86.4%)
## Yes 12 (23.1%) 3 (13.6%)
## CVA: 1.000
## No 49 (94.2%) 21 (95.5%)
## Yes 3 (5.77%) 1 (4.55%)
## DM: 0.211
## No 36 (69.2%) 19 (86.4%)
## Yes 16 (30.8%) 3 (13.6%)
## HBP: 0.161
## No 27 (51.9%) 16 (72.7%)
## Yes 25 (48.1%) 6 (27.3%)
## Liver.dz: 0.550
## No 49 (94.2%) 22 (100%)
## Yes 3 (5.77%) 0 (0.00%)
## Lung.dz: 1.000
## No 48 (92.3%) 20 (90.9%)
## Yes 4 (7.69%) 2 (9.09%)
## Indication: 0.746
## Cardiology 43 (82.7%) 17 (77.3%)
## Respiratory 9 (17.3%) 5 (22.7%)
## Mode: 0.746
## VA 43 (82.7%) 17 (77.3%)
## VV 9 (17.3%) 5 (22.7%)
## CA: 0.115
## No 21 (40.4%) 14 (63.6%)
## Yes 31 (59.6%) 8 (36.4%)
## OHCA: 1.000
## IHCA 27 (87.1%) 7 (87.5%)
## OHCA 4 (12.9%) 1 (12.5%)
## CPR.duration 33.8 (36.7) 16.9 (15.0) 0.055
## CA.ECMO.Time 109 (221) 35.2 (16.3) 0.076
## EKG 1.35 (0.90) 1.86 (0.47) 0.002
## Weaning: <0.001
## Fail 44 (84.6%) 0 (0.00%)
## Success 8 (15.4%) 22 (100%)
## Vent: 0.024
## No 0 (0.00%) 3 (13.6%)
## Yes 52 (100%) 19 (86.4%)
## Hospital.day 14.7 (15.6) 40.9 (18.4) <0.001
## ICU.stay 9.75 (9.43) 18.4 (10.0) 0.001
## CRRT: 0.269
## No 29 (55.8%) 16 (72.7%)
## Yes 23 (44.2%) 6 (27.3%)
## CRRT.duration 5.78 (4.65) 9.17 (5.00) 0.175
## CAG: 0.203
## No 23 (44.2%) 14 (63.6%)
## Yes 29 (55.8%) 8 (36.4%)
## PCI: 0.675
## No 36 (69.2%) 17 (77.3%)
## Yes 16 (30.8%) 5 (22.7%)
## GCS 6.81 (4.24) 10.7 (4.51) 0.001
## Bleeding: 0.374
## No 33 (63.5%) 17 (77.3%)
## Yes 19 (36.5%) 5 (22.7%)
## Tamponade: 1.000
## No 49 (94.2%) 21 (95.5%)
## Yes 3 (5.77%) 1 (4.55%)
## Pulmo: 0.422
## No 45 (86.5%) 21 (95.5%)
## Yes 7 (13.5%) 1 (4.55%)
## AKI: 0.376
## No 28 (53.8%) 15 (68.2%)
## Yes 24 (46.2%) 7 (31.8%)
## Liver.failure: 0.311
## No 48 (92.3%) 22 (100%)
## Yes 4 (7.69%) 0 (0.00%)
## MOF: 0.002
## No 36 (69.2%) 22 (100%)
## Yes 16 (30.8%) 0 (0.00%)
## Sepsis: 1.000
## No 46 (88.5%) 20 (90.9%)
## Yes 6 (11.5%) 2 (9.09%)
## Stroke: 0.297
## No 52 (100%) 21 (95.5%)
## Yes 0 (0.00%) 1 (4.55%)
## Nerve.injury: 0.024
## No 52 (100%) 19 (86.4%)
## Yes 0 (0.00%) 3 (13.6%)
## Leg.ischemia: 0.577
## No 50 (96.2%) 20 (90.9%)
## Yes 2 (3.85%) 2 (9.09%)
## WBC 13751 (8254) 12977 (5665) 0.643
## Hct 34.4 (7.31) 35.7 (8.00) 0.537
## PLT 167 (100) 152 (78.5) 0.493
## Sodium 142 (5.23) 141 (5.82) 0.503
## K 4.36 (1.07) 3.94 (0.45) 0.018
## BUN 28.7 (17.7) 20.2 (10.5) 0.013
## Cr 1.62 (1.23) 1.06 (0.40) 0.004
## Glucose 207 (108) 195 (59.4) 0.532
## Albumin 2.99 (0.88) 3.09 (0.79) 0.634
## Total..bilirubin 1.19 (1.36) 1.41 (1.29) 0.521
## CRP 6.12 (7.73) 9.46 (10.7) 0.198
## D.dimer 9.86 (12.2) 9.21 (11.7) 0.859
## CK.MB 36.2 (47.2) 31.5 (72.9) 0.797
## Troponin 1.53 (3.48) 1.03 (2.17) 0.494
## PRC 26.5 (27.6) 19.2 (18.3) 0.187
## FFP 11.9 (14.2) 8.91 (11.3) 0.338
## PC 53.6 (62.1) 33.4 (33.3) 0.074
## Cryo 1.87 (4.83) 1.55 (3.54) 0.753
## <U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF><U+00AF>교수님 이 항목에서 EKG 를 0:asystole, 1: PEA, 2: 그외 EKG 로 구분 하려고 하는데요. data1\(EKG.=ifelse(data1\)EKG.==1,“PEA”,0,“Asystole”,2,“Etc) 이렇게 넣으니 안되더라구요 ㅠㅠ 어떻게 넣어야 구분이 될까요??
out=lm(Survive~Age+Diagnosis+OHCA+CA.ECMO.Time+EKG+CRRT+GCS+Cr+K,data=data1)
anova(out)## Analysis of Variance Table
##
## Response: Survive
## Df Sum Sq Mean Sq F value Pr(>F)
## Age 1 0.557 0.557 4.23 0.052 .
## Diagnosis 8 1.832 0.229 1.74 0.145
## OHCA 1 0.022 0.022 0.17 0.686
## CA.ECMO.Time 1 0.021 0.021 0.16 0.696
## EKG 1 0.473 0.473 3.59 0.071 .
## CRRT 1 0.084 0.084 0.64 0.433
## GCS 1 0.388 0.388 2.95 0.100
## Cr 1 0.071 0.071 0.54 0.469
## K 1 0.017 0.017 0.13 0.725
## Residuals 22 2.895 0.132
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1P값이 높은 OHCA, CA>ECMO.Time, K 를 빼고 돌리면
out2=lm(Survive~Age+Diagnosis+EKG+CRRT+GCS+Cr,data=data1)
anova(out2)## Analysis of Variance Table
##
## Response: Survive
## Df Sum Sq Mean Sq F value Pr(>F)
## Age 1 1.44 1.438 8.72 0.0045 **
## Diagnosis 8 1.03 0.128 0.78 0.6239
## EKG 1 0.72 0.718 4.35 0.0412 *
## CRRT 1 0.50 0.497 3.01 0.0877 .
## GCS 1 1.36 1.363 8.27 0.0056 **
## Cr 1 0.52 0.524 3.18 0.0797 .
## Residuals 60 9.89 0.165
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1confint(out2)## 2.5 % 97.5 %
## (Intercept) -0.032445 1.071987
## Age -0.014697 -0.000957
## DiagnosisARDS -0.257391 0.327813
## DiagnosisDrug Intoxication -1.060384 0.650712
## DiagnosisLA myxoma -1.184656 0.588292
## DiagnosisMyocarditis -0.381197 0.500980
## DiagnosisPTE -0.111936 0.544462
## DiagnosisPump failure -0.528952 0.185235
## DiagnosisTrauma -0.609700 0.675932
## DiagnosisVF, VT -0.447738 0.462866
## EKG -0.027655 0.229246
## CRRTYes -0.305657 0.137711
## GCS 0.007977 0.053397
## Cr -0.179223 0.010322Diagnosis 를 빼고 돌리면,
out3=lm(Survive~Age+EKG+CRRT+GCS+Cr,data=data1)
anova(out3)## Analysis of Variance Table
##
## Response: Survive
## Df Sum Sq Mean Sq F value Pr(>F)
## Age 1 1.44 1.438 9.22 0.0034 **
## EKG 1 0.92 0.922 5.91 0.0177 *
## CRRT 1 0.73 0.727 4.66 0.0344 *
## GCS 1 1.27 1.266 8.12 0.0058 **
## Cr 1 0.50 0.497 3.19 0.0787 .
## Residuals 68 10.61 0.156
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1confint(out3)## 2.5 % 97.5 %
## (Intercept) 0.060069 0.989091
## Age -0.013379 -0.001884
## EKG -0.002738 0.229068
## CRRTYes -0.308787 0.089654
## GCS 0.007326 0.048989
## Cr -0.168969 0.009407out4=lm(Survive~Age+EKG+CRRT+GCS,data=data1)
anova(out4)## Analysis of Variance Table
##
## Response: Survive
## Df Sum Sq Mean Sq F value Pr(>F)
## Age 1 1.44 1.438 8.93 0.0039 **
## EKG 1 0.92 0.922 5.73 0.0194 *
## CRRT 1 0.73 0.727 4.52 0.0372 *
## GCS 1 1.27 1.266 7.87 0.0065 **
## Residuals 69 11.11 0.161
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1여기에서 P 값이 0.05 이하인 변수들이 생존에 영향을 미칠수 있다고 볼 수 보는 것이죠? 교수님
summary(out4)##
## Call:
## lm(formula = Survive ~ Age + EKG + CRRT + GCS, data = data1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6707 -0.3337 -0.0469 0.2514 0.7594
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.44211 0.23174 1.91 0.0606 .
## Age -0.00792 0.00292 -2.71 0.0084 **
## EKG 0.10581 0.05885 1.80 0.0765 .
## CRRTYes -0.15300 0.09835 -1.56 0.1243
## GCS 0.02965 0.01057 2.80 0.0065 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.401 on 69 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.282, Adjusted R-squared: 0.24
## F-statistic: 6.76 on 4 and 69 DF, p-value: 0.000119Summary 를 돌리면 EKG 와 CRRT 는 P 값이 0.05보다 커져 버리는데 그럼 생존에 영향을 미치는 인자로 보기 어려운 것인가요?
R2 = 28.2% 로 모형이 종속변수 Survive를 28.2%설명할 수 있다.
out=glm(Survive~Age+EKG+CRRT+GCS+Cr,family=binomial,data=data1)
summary(out)##
## Call:
## glm(formula = Survive ~ Age + EKG + CRRT + GCS + Cr, family = binomial,
## data = data1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.733 -0.667 -0.246 0.277 2.224
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.3538 2.0020 0.68 0.4989
## Age -0.0647 0.0264 -2.45 0.0143 *
## EKG 1.1460 0.5513 2.08 0.0376 *
## CRRTYes -0.5450 0.7677 -0.71 0.4778
## GCS 0.2370 0.0842 2.81 0.0049 **
## Cr -1.6979 0.7198 -2.36 0.0183 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 90.066 on 73 degrees of freedom
## Residual deviance: 57.047 on 68 degrees of freedom
## (1 observation deleted due to missingness)
## AIC: 69.05
##
## Number of Fisher Scoring iterations: 6exp(coef(out))## (Intercept) Age EKG CRRTYes GCS Cr
## 3.8721 0.9374 3.1457 0.5799 1.2674 0.1831confint(out)## Waiting for profiling to be done...## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred## 2.5 % 97.5 %
## (Intercept) -2.60432 5.44163
## Age -0.12329 -0.01866
## EKG 0.19637 2.46618
## CRRTYes -2.12547 0.94278
## GCS 0.08441 0.42072
## Cr -3.36234 -0.49399exp(confint(out))## Waiting for profiling to be done...## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred## 2.5 % 97.5 %
## (Intercept) 0.07395 230.8188
## Age 0.88400 0.9815
## EKG 1.21698 11.7773
## CRRTYes 0.11938 2.5671
## GCS 1.08808 1.5231
## Cr 0.03465 0.6102여기에서 CRRT 를 제외한 변수의 P값이 유의하므로 모형에 넣고 돌리면
out2=glm(Survive~Age+EKG+GCS+Cr,family=binomial,data=data1)
summary(out2)##
## Call:
## glm(formula = Survive ~ Age + EKG + GCS + Cr, family = binomial,
## data = data1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.700 -0.695 -0.259 0.302 2.240
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.0416 1.9012 0.55 0.5838
## Age -0.0601 0.0245 -2.45 0.0143 *
## EKG 1.1072 0.5404 2.05 0.0405 *
## GCS 0.2425 0.0838 2.89 0.0038 **
## Cr -1.8117 0.7105 -2.55 0.0108 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 90.066 on 73 degrees of freedom
## Residual deviance: 57.560 on 69 degrees of freedom
## (1 observation deleted due to missingness)
## AIC: 67.56
##
## Number of Fisher Scoring iterations: 6exp(coef(out2))## (Intercept) Age EKG GCS Cr
## 2.8337 0.9417 3.0260 1.2744 0.1634confint(out2)## Waiting for profiling to be done...## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred## 2.5 % 97.5 %
## (Intercept) -2.77808 4.86875
## Age -0.11371 -0.01661
## EKG 0.17504 2.40658
## GCS 0.09109 0.42566
## Cr -3.46329 -0.63211exp(confint(out2))## Waiting for profiling to be done...## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred## 2.5 % 97.5 %
## (Intercept) 0.06216 130.1580
## Age 0.89251 0.9835
## EKG 1.19130 11.0959
## GCS 1.09537 1.5306
## Cr 0.03133 0.5315