Đề tài loét tỳ đè
Hà Tấn Đức
13/10/2020
1. Đọc dữ liệu
options (scipen = 999)
options (digits = 2)
library(readxl)
files = list.files(path = "C:/Users/ADMIN/OneDrive/others/Cac de tai/Ths DD Tran", pattern = "*.xlsx", full.names = T)
tbl = sapply(files, read_excel, simplify= F)
library (dplyr)
d = tbl%>%bind_rows (.id = "path")
names (d)## [1] "path" "doe" "dot" "id1" "id2" "name" "age"
## [8] "gender" "phone1" "phone2" "doa" "hoa" "moa" "doi"
## [15] "hoi" "moi" "dep" "md" "mdicd" "co1" "co1icd"
## [22] "co2" "co2icd" "co3" "co3icd" "tem" "sys" "dia"
## [29] "pul" "br" "fio2" "po2" "hco3" "ph" "na"
## [36] "ka" "cre" "bili" "akf" "hct" "leuco" "pla"
## [43] "gcs" "dou" "lou" "sen" "hum" "act" "mov"
## [50] "nut" "frit" "bs" "hof" "vaso1" "dose1" "vaso2"
## [57] "dose2" "vou" "ope" "do" "ho" "mo" "ko"
## [64] "ro" "po" "ab" "doab" "toab" "hoab" "moab"
## [71] "et" "det" "to" "dto" "mv" "dmv" "uc"
## [78] "duc" "turn" "bath" "nr" "wm" "am" "acm"
## [85] "pil" "wp" "son" "ddis" "hdis" "mdis" "oc"
## [92] "p1" "d1p1" "g1d1" "d2p1" "g1d2" "d3p1" "g1d3"
## [99] "d4p1" "g1d4" "d5p1" "g1d5" "d6p1" "g1d6" "d7p1"
## [106] "g1d7" "d8p1" "g1d8" "d9p1" "g1d9" "d10p1" "g1d10"
## [113] "max1" "status1" "p2" "d1p2" "g2d1" "d2p2" "g2d2"
## [120] "d3p2" "g2d3" "d4p2" "g2d4" "d5p2" "g2d5" "d6p2"
## [127] "g2d6" "d7p2" "g2d7" "d8p2" "g2d8" "d9p2" "g2d9"
## [134] "d10p2" "g2d10" "max2" "status2" "p3" "d1p3" "g3d1"
## [141] "d2p3" "g3d2" "d3p3" "g3d3" "d4p3" "g3d4" "d5p3"
## [148] "g3d5" "d6p3" "g3d6" "d7p3" "g3d7" "d8p3" "g3d8"
## [155] "d9p3" "g3d9" "d10p3" "g3d10" "max3" "status3" "p4"
## [162] "d1p4" "g4d1" "d2p4" "g4d2" "d3p4" "g4d3" "d4p4"
## [169] "g4d4" "d5p4" "g4d5" "d6p4" "g4d6" "d7p4" "g4d7"
## [176] "d8p4" "g4d8" "d9p4" "g4d9" "d10p4" "g4d10" "max4"
## [183] "status4" "p5" "d1p5" "g5d1" "d2p5" "g5d2" "d3p5"
## [190] "g5d3" "d4p5" "g5d4" "d5p5" "g5d5" "d6p5" "g5d6"
## [197] "d7p5" "g5d7" "d8p5" "g5d8" "d9p5" "g5d9" "d10p5"
## [204] "g5d10" "max5" "status5" "status"2. Biên tập dữ liệu
# Thời điểm nhập viện
library (magrittr)
d$toa = paste (d$doa, sep=' ', d$hoa) %>% paste(sep = ':', d$moa)
# Thời điểm vào ICU
d$toi = paste (d$doi, sep=' ', d$hoi) %>% paste(sep = ':', d$moi)
# Thời điểm thực hiện phẫu thuật
d$tto = paste (d$do, sep=' ', d$ho) %>% paste(sep = ':', d$mo)
# Thời điểm ra khỏi khoa ICU
d$tdis = paste (d$ddis, sep=' ', d$hdis) %>% paste(sep = ':', d$mdis)
# Số ngày nằm tại ICU
d$losi = (d$ddis - d$doi)/(24*60*60)
#tạo biến số PaO2/FiO2
d$po2fio2 = d$po2/(d$fio2/100)3. Lọc dữ liệu chỉ gồm những ca vào khoa ICU chưa xuất hiện loét
library (dplyr)
d1<- d %>% filter(d$lou == 0| d$lou == 1)4. Mục tiêu 1: Xác định loét tỳ đè ở khoa ICU
library (DescTools)
Desc(factor (d$lou))## ------------------------------------------------------------------------------
## factor(d$lou) (factor)
##
## length n NAs unique levels dupes
## 224 197 27 4 4 y
## 87.9% 12.1%
##
## level freq perc cumfreq cumperc
## 1 0 130 66.0% 130 66.0%
## 2 1 27 13.7% 157 79.7%
## 3 2 20 10.2% 177 89.8%
## 4 3 20 10.2% 197 100.0%
Bệnh chính khi vào khoa ICU
Desc(factor (d$md))## ------------------------------------------------------------------------------
## factor(d$md) (factor)
##
## length n NAs unique levels dupes
## 224 223 1 78 78 y
## 99.6% 0.4%
##
## level freq perc cumfreq cumperc
## 1 viem phoi 67 30.0% 67 30.0%
## 2 nhoi mau nao 14 6.3% 81 36.3%
## 3 soc nhiem khuan 11 4.9% 92 41.3%
## 4 nhoi mau co tim 10 4.5% 102 45.7%
## 5 soc nhiem trung 9 4.0% 111 49.8%
## 6 choang nhiem trung 6 2.7% 117 52.5%
## 7 nhiem trung huyet 5 2.2% 122 54.7%
## 8 suy than man 5 2.2% 127 57.0%
## 9 soc tim 4 1.8% 131 58.7%
## 10 suy tim 4 1.8% 135 60.5%
## 11 soc niem trung 3 1.3% 138 61.9%
## 12 tran khi mang phoi 3 1.3% 141 63.2%
## ... etc.
## [list output truncated]
5. Mục tiêu 2: Tỷ lệ loét tỳ đè có tiến triển tốt
library (DescTools)
Desc (factor (d$status))## ------------------------------------------------------------------------------
## factor(d$status) (factor - dichotomous)
##
## length n NAs unique
## 224 67 157 2
## 29.9% 70.1%
##
## freq perc lci.95 uci.95'
## 0 65 97.0% 89.8% 99.2%
## 1 2 3.0% 0.8% 10.2%
##
## ' 95%-CI (Wilson)
library (tableone)
vars= c ("age", 'tem', 'sys', 'dia', 'pul', 'br', 'po2fio2', 'na', 'ka', 'cre', 'bili', 'hct', 'leuco', 'pla', 'gcs', 'bs', 'vou','losi',
'dep', 'gender', 'ko', 'ro', 'po', 'mv', 'uc', 'turn', 'bath', 'nr', 'wm', 'am', 'acm', 'pil', 'wp', 'son', 'oc')
cat= c ('dep', 'gender', 'ko', 'ro', 'po', 'mv', 'uc', 'turn', 'bath', 'nr', 'wm', 'am', 'acm', 'pil', 'wp', 'son', 'oc')
tab1= CreateTableOne (vars= vars, factorVars= cat, data= d, strata= c("status"))
t = print (tab1, quote= F, noSpace= T, printToggle= T, nonnormal= c("age", 'tem', 'sys', 'dia', 'pul', 'br', 'po2fio2', 'na', 'ka', 'cre', 'bili', 'hct', 'leuco', 'pla', 'gcs', 'bs', 'vou','losi'))## Stratified by status
## 0 1
## n 65 2
## age (median [IQR]) 72.00 [67.00, 81.00] 87.50 [86.75, 88.25]
## tem (median [IQR]) 37.50 [37.00, 38.50] 37.15 [37.08, 37.22]
## sys (median [IQR]) 120.00 [90.00, 130.00] 135.00 [132.50, 137.50]
## dia (median [IQR]) 70.00 [60.00, 80.00] 80.00 [75.00, 85.00]
## pul (median [IQR]) 100.00 [90.00, 118.00] 120.00 [120.00, 120.00]
## br (median [IQR]) 0.00 [0.00, 0.00] 0.00 [0.00, 0.00]
## po2fio2 (median [IQR]) 223.79 [149.12, 315.00] NA [NA, NA]
## na (median [IQR]) 137.00 [131.00, 141.00] 127.50 [127.25, 127.75]
## ka (median [IQR]) 3.60 [3.20, 4.40] 3.60 [3.50, 3.70]
## cre (median [IQR]) 1.00 [0.60, 1.80] 0.55 [0.48, 0.62]
## bili (median [IQR]) 12.50 [4.20, 36.40] NA [NA, NA]
## hct (median [IQR]) 30.80 [27.25, 35.05] 32.05 [31.42, 32.67]
## leuco (median [IQR]) 12.70 [10.38, 16.40] 10.05 [7.12, 12.98]
## pla (median [IQR]) 218.00 [148.00, 295.00] 382.50 [226.25, 538.75]
## gcs (median [IQR]) 10.00 [7.00, 10.00] NA [NA, NA]
## bs (median [IQR]) 11.00 [10.00, 11.00] 9.50 [9.25, 9.75]
## vou (median [IQR]) 1800.00 [900.00, 2600.00] 400.00 [300.00, 500.00]
## dep (%)
## 1 20 (30.8) 1 (50.0)
## 2 14 (21.5) 0 (0.0)
## 3 30 (46.2) 1 (50.0)
## 4 1 (1.5) 0 (0.0)
## gender = 1 (%) 37 (56.9) 1 (50.0)
## ko (%)
## 0 56 (96.6) 1 (100.0)
## 1 1 (1.7) 0 (0.0)
## 2 0 (0.0) 0 (0.0)
## 3 1 (1.7) 0 (0.0)
## ro (%)
## 0 14 (87.5) 0 (NaN)
## 1 0 (0.0) 0 (NaN)
## 2 2 (12.5) 0 (NaN)
## 3 0 (0.0) 0 (NaN)
## po (%)
## 1 0 (0.0) 0 (NaN)
## 8 0 (0.0) 0 (NaN)
## 9 0 (0.0) 0 (NaN)
## 10 0 (0.0) 0 (NaN)
## 11 1 (100.0) 0 (NaN)
## mv = 1 (%) 59 (93.7) 2 (100.0)
## uc = 1 (%) 49 (79.0) 2 (100.0)
## turn = 2 (%) 34 (52.3) 1 (50.0)
## bath = 2 (%) 8 (12.3) 0 (0.0)
## nr (%)
## 1 1 (1.5) 0 (0.0)
## 2 62 (95.4) 2 (100.0)
## 3 2 (3.1) 0 (0.0)
## wm = 0 (%) 58 (100.0) 1 (100.0)
## am = 1 (%) 58 (100.0) 1 (100.0)
## acm = 1 (%) 0 (0.0) 0 (0.0)
## pil = 1 (%) 58 (100.0) 1 (100.0)
## wp = 1 (%) 0 (0.0) 0 (0.0)
## son = 2 (%) 62 (100.0) 2 (100.0)
## oc = 1 (%) 30 (46.2) 0 (0.0)
## Stratified by status
## p test
## n
## age (median [IQR]) 0.071 nonnorm
## tem (median [IQR]) 0.235 nonnorm
## sys (median [IQR]) 0.207 nonnorm
## dia (median [IQR]) 0.351 nonnorm
## pul (median [IQR]) 0.125 nonnorm
## br (median [IQR]) 0.488 nonnorm
## po2fio2 (median [IQR]) NA nonnorm
## na (median [IQR]) 0.046 nonnorm
## ka (median [IQR]) 0.971 nonnorm
## cre (median [IQR]) 0.135 nonnorm
## bili (median [IQR]) NA nonnorm
## hct (median [IQR]) 0.805 nonnorm
## leuco (median [IQR]) 0.501 nonnorm
## pla (median [IQR]) 0.883 nonnorm
## gcs (median [IQR]) NA nonnorm
## bs (median [IQR]) 0.114 nonnorm
## vou (median [IQR]) 0.044 nonnorm
## dep (%) 0.874
## 1
## 2
## 3
## 4
## gender = 1 (%) 1.000
## ko (%) NaN
## 0
## 1
## 2
## 3
## ro (%) NaN
## 0
## 1
## 2
## 3
## po (%) NaN
## 1
## 8
## 9
## 10
## 11
## mv = 1 (%) 1.000
## uc = 1 (%) 1.000
## turn = 2 (%) 1.000
## bath = 2 (%) 1.000
## nr (%) 0.953
## 1
## 2
## 3
## wm = 0 (%) NA
## am = 1 (%) NA
## acm = 1 (%) NaN
## pil = 1 (%) NaN
## wp = 1 (%) NaN
## son = 2 (%) NaN
## oc = 1 (%) 0.5686. Mục tiêu 3: Các yếu tố nguy cơ có liên quan đến diễn biến loét tỳ đè.
#Phân tích đơn biến
library (questionr)
odds.ratio (glm (d$status ~ I(age/10), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.0000002402824651268 0.0000000000000000161 0.05 0.072 .
## I(age/10) 4.2748785455031246272 0.9469260640089370851 56.80 0.134
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ tem, data= d, family= binomial))## OR
## (Intercept) 3911774406793359399062886444644462.000000000000
## tem 0.115153892423
## 2.5 %
## (Intercept) 0.000000000441
## tem 0.000030267745
## 97.5 %
## (Intercept) 15383796885773097543086440004884002264022260846406228800688226044400622620844228208266806668200800288820048606262084020062046688886628404428040426242204222206828064066.00
## tem 1.61
## p
## (Intercept) 0.35
## tem 0.33odds.ratio (glm (d$status ~ I(sys/10), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.02718 0.00261 0.62 0.001 **
## I(sys/10) 1.00961 NA 1.09 0.877
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ I(dia/10), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.000384750083 0.000000000669 0.57 0.13
## I(dia/10) 1.784835958602 0.652026390640 8.37 0.37odds.ratio (glm (d$status ~ I(pul/10), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.0005472010 0.0000000541 0.39 0.06 .
## I(pul/10) 1.4361335177 0.7811291500 2.87 0.27
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ I(br/10), data= d, family= binomial))## OR 2.5 %
## (Intercept) 0.038462 0.006293
## I(br/10) 0.000765 NA
## 97.5 %
## (Intercept) 0.12
## I(br/10) 3746498023853917030822648402266660244602028202284000260002266880046062806268464464284602466248248604040604226866846866426488840002242.00
## p
## (Intercept) 0.0000061 ***
## I(br/10) 1
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ I(na/5), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.142260816 0.000000625 11.74 0.51
## I(na/5) 0.943638134 0.794127427 1.47 0.60odds.ratio (glm (d$status ~ I(ka/5), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.0427878 0.0000437 2.91 0.27
## I(ka/5) 0.6357266 0.0010146 2068.36 0.91odds.ratio (glm (d$status ~ cre, data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.7787896941 0.0148743807 304.83 0.92
## cre 0.0117862837 0.0000000616 1.13 0.30odds.ratio (glm (d$status ~ I(hct/10), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.0285183 0.0000836 67.8 0.29
## I(hct/10) 1.0341087 0.0706308 4.7 0.97odds.ratio (glm (d$status ~ I(leuco/10), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.14464 0.00461 3.09 0.26
## I(leuco/10) 0.27179 0.00792 2.12 0.40odds.ratio (glm (d$status ~ I(pla/50), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.0033285 0.0000385 0.06 0.0014 **
## I(pla/50) 1.4667308 0.9100687 2.49 0.0946 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ bs, data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 454.49758 0.00205 1339712824.47 0.37
## bs 0.38713 0.07550 1.26 0.18odds.ratio (glm (d$status ~ I(vou/100), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.6463 0.0358 11.97 0.76
## I(vou/100) 0.6763 0.3130 0.96 0.17odds.ratio (glm (d$status ~ losi, data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.03199 0.00293 0.1 0.0000017 ***
## losi 1.00065 0.99934 NA 0.9
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ factor (d$dep), data= d, family= binomial))## OR 2.5 %
## (Intercept) 0.0500000000 0.0027859330
## factor(d$dep)2 0.0000000636 NA
## factor(d$dep)3 0.6666666667 0.0253679889
## factor(d$dep)4 0.0000000636 NA
## 97.5 %
## (Intercept) 0.24
## factor(d$dep)2 239030640816738745982800640442288048466260868800260240660460620642860686880864046608600684802288822820466444662808408866004206086006804660040206840420688086866466046048266866000882844848048002668240226.00
## factor(d$dep)3 17.51
## factor(d$dep)4 Inf
## p
## (Intercept) 0.0035 **
## factor(d$dep)2 0.9954
## factor(d$dep)3 0.7788
## factor(d$dep)4 0.9988
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ factor (d$gender), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.0357 0.0020 0.17 0.0011 **
## factor(d$gender)1 0.7568 0.0291 19.70 0.8461
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ factor (d$turn), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.03226 0.00181 0.15 0.00073 ***
## factor(d$turn)2 0.91176 0.03505 23.72 0.94870
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ factor (d$bath), data= d, family= binomial))## OR 2.5 %
## (Intercept) 0.0350877193 0.0057489515
## factor(d$bath)2 0.0000000907 NA
## 97.5 %
## (Intercept) 0.11
## factor(d$bath)2 14020412208757789480082222220042206606024026682640426626028620428688264648082088286086686686480048024426042020022800028620264802864006246848486282206240066420268080428680460684806246224088620844406288082262282280600682824608820682880888660822464602202828440040402020648.00
## p
## (Intercept) 0.0000032 ***
## factor(d$bath)2 1
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1odds.ratio (glm (d$status ~ factor (d$nr), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.00000000865 NA Inf 1
## factor(d$nr)2 3730606.22558304016 0.00000000000 NA 1
## factor(d$nr)3 1.00000000012 0.00000000000 NA 1odds.ratio (glm (d$status ~ factor (d$nr), data= d, family= binomial))## OR 2.5 % 97.5 % p
## (Intercept) 0.00000000865 NA Inf 1
## factor(d$nr)2 3730606.22558304016 0.00000000000 NA 1
## factor(d$nr)3 1.00000000012 0.00000000000 NA 1Phương tiện chống loét
odds.ratio (glm (d$oc ~ factor (d$status), data= d, family= binomial))## OR 2.5 %
## (Intercept) 0.8571428571 0.5234521307
## factor(d$status)1 0.0000000745 NA
## 97.5 %
## (Intercept) 1.39
## factor(d$status)1 3029043047925420098886820022860644044642468604668260862422808428280088828088262288420668282662848408422688486.00
## p
## (Intercept) 0.54
## factor(d$status)1 0.99- Tỷ lệ giới của đối tượng nghiên cứu xuất hiện loét (đã thực hiện, biến số lou)
- Tỷ lệ tuổi của đối tượng nghiên cứu xuất hiện loét
library (DescTools)
Desc(factor (d$lou) ~ d$age)## ------------------------------------------------------------------------------
## factor(d$lou) ~ d$age
##
## Summary:
## n pairs: 224, valid: 195 (87.1%), missings: 29 (12.9%), groups: 4
##
##
## 0 1 2 3
## mean 67.162 72.385 70.684 73.550
## median 67.000 73.000 71.000 71.500
## sd 15.049 13.529 13.905 11.090
## IQR 22.000 20.500 15.500 11.000
## n 130 26 19 20
## np 66.667% 13.333% 9.744% 10.256%
## NAs 0 1 1 0
## 0s 0 0 0 0
##
## Kruskal-Wallis rank sum test:
## Kruskal-Wallis chi-squared = 5, df = 3, p-value = 0.2
## Warning:
## Grouping variable contains 27 NAs (12.1%).
##
##
##
## Proportions of factor(d$lou) in the quantiles of d$age:
##
## Q1 Q2 Q3 Q4
## 0 78.0% 65.3% 60.4% 62.5%
## 1 8.0% 16.3% 10.4% 18.8%
## 2 8.0% 8.2% 12.5% 10.4%
## 3 6.0% 10.2% 16.7% 8.3%
- NB loét có đặt nội khí quản, thở máy, sonde tiểu, son dạ dày,…
d$outcome = d$lou
d$outcome [d$lou == 0]= 0
d$outcome [d$lou != 0]= 1
library (tableone)
vars= c ("age", 'tem', 'sys', 'dia', 'pul', 'br', 'po2fio2', 'na', 'ka', 'cre', 'bili', 'hct', 'leuco', 'pla', 'gcs', 'bs', 'vou','losi',
'dep', 'gender', 'ko', 'ro', 'po', 'mv', 'uc', 'turn', 'bath', 'nr', 'wm', 'am', 'acm', 'pil', 'wp', 'son', 'oc')
cat= c ('dep', 'gender', 'ko', 'ro', 'po', 'mv', 'uc', 'turn', 'bath', 'nr', 'wm', 'am', 'acm', 'pil', 'wp', 'son', 'oc')
tab2= CreateTableOne (vars= vars, factorVars= cat, data= d, strata= c("outcome"))## Warning in CreateTableOne(vars = vars, factorVars = cat, data = d, strata = c("outcome")): Dropping variable(s) losi due to unsupported class.## Warning in sqrt(sqSmds): NaNs producedt2 = print (tab2, quote= F, noSpace= T, printToggle= T, nonnormal= c("age", 'tem', 'sys', 'dia', 'pul', 'br', 'po2fio2', 'na', 'ka', 'cre', 'bili', 'hct', 'leuco', 'pla', 'gcs', 'bs', 'vou','losi'))## Stratified by outcome
## 0 1
## n 130 67
## age (median [IQR]) 67.00 [57.00, 79.00] 72.00 [65.00, 81.00]
## tem (median [IQR]) 37.00 [37.00, 38.00] 37.50 [37.00, 38.50]
## sys (median [IQR]) 120.00 [90.00, 140.00] 120.00 [95.00, 130.00]
## dia (median [IQR]) 70.00 [60.00, 80.00] 70.00 [60.00, 80.00]
## pul (median [IQR]) 100.00 [90.00, 119.00] 100.00 [90.00, 119.00]
## br (median [IQR]) 0.00 [0.00, 22.00] 0.00 [0.00, 0.00]
## po2fio2 (median [IQR]) 223.60 [160.00, 309.03] 219.22 [147.62, 309.71]
## na (median [IQR]) 135.50 [132.00, 138.00] 137.00 [131.00, 141.00]
## ka (median [IQR]) 3.70 [3.40, 4.30] 3.60 [3.20, 4.40]
## cre (median [IQR]) 1.00 [0.70, 1.67] 1.00 [0.60, 1.95]
## bili (median [IQR]) 10.80 [0.17, 26.30] 12.90 [4.30, 41.20]
## hct (median [IQR]) 33.65 [28.70, 40.00] 30.80 [27.20, 35.00]
## leuco (median [IQR]) 13.80 [10.40, 18.20] 12.55 [10.33, 16.60]
## pla (median [IQR]) 244.00 [137.00, 304.00] 218.00 [147.00, 292.50]
## gcs (median [IQR]) 5.50 [5.00, 8.25] 10.00 [9.25, 10.75]
## bs (median [IQR]) 12.00 [11.00, 13.00] 11.00 [10.00, 11.00]
## vou (median [IQR]) 1400.00 [600.00, 2400.00] 1700.00 [800.00, 2600.00]
## dep (%)
## 1 43 (33.1) 22 (32.8)
## 2 31 (23.8) 13 (19.4)
## 3 55 (42.3) 31 (46.3)
## 4 1 (0.8) 1 (1.5)
## gender = 1 (%) 65 (50.0) 38 (56.7)
## ko (%)
## 0 124 (98.4) 59 (96.7)
## 1 2 (1.6) 1 (1.6)
## 2 0 (0.0) 0 (0.0)
## 3 0 (0.0) 1 (1.6)
## ro (%)
## 0 21 (91.3) 15 (88.2)
## 1 0 (0.0) 0 (0.0)
## 2 1 (4.3) 2 (11.8)
## 3 1 (4.3) 0 (0.0)
## po (%)
## 1 0 (0.0) 0 (0.0)
## 8 1 (50.0) 0 (0.0)
## 9 1 (50.0) 0 (0.0)
## 10 0 (0.0) 0 (0.0)
## 11 0 (0.0) 1 (100.0)
## mv = 1 (%) 101 (80.2) 60 (92.3)
## uc = 1 (%) 83 (66.9) 51 (79.7)
## turn = 2 (%) 71 (54.6) 35 (52.2)
## bath = 2 (%) 15 (11.5) 8 (11.9)
## nr (%)
## 1 7 (5.4) 2 (3.0)
## 2 119 (91.5) 63 (94.0)
## 3 4 (3.1) 2 (3.0)
## wm = 0 (%) 126 (100.0) 60 (100.0)
## am = 1 (%) 126 (100.0) 60 (100.0)
## acm = 1 (%) 1 (0.8) 0 (0.0)
## pil = 1 (%) 125 (99.2) 60 (100.0)
## wp = 1 (%) 1 (0.8) 0 (0.0)
## son = 2 (%) 127 (98.4) 64 (100.0)
## oc = 1 (%) 59 (47.6) 31 (46.3)
## Stratified by outcome
## p test
## n
## age (median [IQR]) 0.029 nonnorm
## tem (median [IQR]) 0.021 nonnorm
## sys (median [IQR]) 0.771 nonnorm
## dia (median [IQR]) 0.967 nonnorm
## pul (median [IQR]) 0.452 nonnorm
## br (median [IQR]) 0.040 nonnorm
## po2fio2 (median [IQR]) 0.654 nonnorm
## na (median [IQR]) 0.515 nonnorm
## ka (median [IQR]) 0.390 nonnorm
## cre (median [IQR]) 0.565 nonnorm
## bili (median [IQR]) 0.684 nonnorm
## hct (median [IQR]) 0.015 nonnorm
## leuco (median [IQR]) 0.222 nonnorm
## pla (median [IQR]) 0.608 nonnorm
## gcs (median [IQR]) 0.050 nonnorm
## bs (median [IQR]) <0.001 nonnorm
## vou (median [IQR]) 0.145 nonnorm
## dep (%) 0.855
## 1
## 2
## 3
## 4
## gender = 1 (%) 0.457
## ko (%) NaN
## 0
## 1
## 2
## 3
## ro (%) NaN
## 0
## 1
## 2
## 3
## po (%) NaN
## 1
## 8
## 9
## 10
## 11
## mv = 1 (%) 0.048
## uc = 1 (%) 0.097
## turn = 2 (%) 0.868
## bath = 2 (%) 1.000
## nr (%) 0.745
## 1
## 2
## 3
## wm = 0 (%) NA
## am = 1 (%) NA
## acm = 1 (%) 1.000
## pil = 1 (%) 1.000
## wp = 1 (%) 1.000
## son = 2 (%) 0.805
## oc = 1 (%) 0.983- Điểm Braden: …(thấp nhất, cao nhất), yếu tố liên quan giửa điểm Braden đến tiến triển loét (đã thực hiện)
library (DescTools)
Desc (d$bs)## ------------------------------------------------------------------------------
## d$bs (numeric)
##
## length n NAs unique 0s mean meanCI'
## 224 222 2 13 0 11.95 11.65
## 99.1% 0.9% 0.0% 12.25
##
## .05 .10 .25 median .75 .90 .95
## 9.00 10.00 11.00 11.00 13.00 15.00 17.00
##
## range sd vcoef mad IQR skew kurt
## 13.00 2.26 0.19 1.48 2.00 1.49 2.66
##
## lowest : 8.0 (2), 9.0 (14), 10.0 (33), 11.0 (65), 12.0 (50)
## highest: 16.0 (5), 17.0 (5), 18.0 (5), 19.0 (2), 21.0 (2)
##
## heap(?): remarkable frequency (29.3%) for the mode(s) (= 11)
##
## ' 95%-CI (classic)
- Mức độ loét tỳ đè (độ I, độ II, độ III)
library (reshape2)
d2= melt (d, id= c("id1"), measure.vars= c("p1", "p2", "p3", "p4", "p5"))
names (d2)[names (d2)=='variable']= 'loca'
names (d2)[names (d2)=='value']= 'classi'
d2## id1 loca classi
## 1 20166719 p1 NA
## 2 20170986 p1 NA
## 3 20172998 p1 NA
## 4 20162605 p1 NA
## 5 20177178 p1 NA
## 6 20186486 p1 NA
## 7 20158219 p1 NA
## 8 20163585 p1 NA
## 9 20167575 p1 NA
## 10 20159424 p1 NA
## 11 20167508 p1 NA
## 12 20167237 p1 NA
## 13 20148305 p1 NA
## 14 20230158 p1 1
## 15 20163199 p1 1
## 16 20171304 p1 NA
## 17 20184211 p1 NA
## 18 20169505 p1 NA
## 19 20174623 p1 NA
## 20 20167254 p1 NA
## 21 20163262 p1 NA
## 22 20165724 p1 1
## 23 20167073 p1 NA
## 24 20177112 p1 NA
## 25 20158301 p1 1
## 26 20181063 p1 NA
## 27 20176261 p1 NA
## 28 20167360 p1 1
## 29 20244869 p1 NA
## 30 20248972 p1 NA
## 31 20248912 p1 1
## 32 2022222 p1 1
## 33 20234614 p1 NA
## 34 20234597 p1 NA
## 35 2023876 p1 NA
## 36 20212552 p1 NA
## 37 20182650 p1 1
## 38 20191049 p1 1
## 39 20179164 p1 1
## 40 20196421 p1 NA
## 41 20218653 p1 NA
## 42 20212318 p1 NA
## 43 20212416 p1 NA
## 44 20211072 p1 NA
## 45 20211146 p1 NA
## 46 20212320 p1 NA
## 47 20209330 p1 NA
## 48 20204740 p1 NA
## 49 20204308 p1 NA
## 50 20200085 p1 1
## 51 20205361 p1 NA
## 52 20205332 p1 NA
## 53 20196165 p1 1
## 54 20199506 p1 1
## 55 20196408 p1 NA
## 56 20195722 p1 1
## 57 20192199 p1 1
## 58 20210988 p1 NA
## 59 20204722 p1 NA
## 60 20205498 p1 NA
## 61 20178358 p1 1
## 62 20215240 p1 NA
## 63 20215310 p1 NA
## 64 20214506 p1 1
## 65 2020436 p1 NA
## 66 20214971 p1 NA
## 67 20224458 p1 NA
## 68 20224521 p1 NA
## 69 20217238 p1 NA
## 70 20216317 p1 NA
## 71 20211127 p1 NA
## 72 20190115 p1 NA
## 73 20199793 p1 NA
## 74 20181045 p1 NA
## 75 20185546 p1 1
## 76 20201719 p1 NA
## 77 20190383 p1 NA
## 78 20201323 p1 NA
## 79 20192932 p1 NA
## 80 20170696 p1 1
## 81 20247095 p1 1
## 82 20244282 p1 1
## 83 20242353 p1 6
## 84 20228025 p1 NA
## 85 20241299 p1 1
## 86 20205465 p1 1
## 87 20209150 p1 NA
## 88 20217194 p1 NA
## 89 20219047 p1 NA
## 90 20217191 p1 NA
## 91 20193224 p1 1
## 92 20224412 p1 1
## 93 20283871 p1 NA
## 94 20242105 p1 NA
## 95 20240551 p1 NA
## 96 20226613 p1 NA
## 97 20236785 p1 NA
## 98 234673 p1 NA
## 99 20234570 p1 NA
## 100 20230191 p1 NA
## 101 20219003 p1 1
## 102 20195506 p1 1
## 103 20205279 p1 1
## 104 20234547 p1 1
## 105 20223517 p1 1
## 106 20218994 p1 1
## 107 20224467 p1 1
## 108 20216908 p1 1
## 109 20205146 p1 NA
## 110 20233917 p1 NA
## 111 20212313 p1 NA
## 112 20166635 p1 NA
## 113 20163253 p1 NA
## 114 20172954 p1 NA
## 115 20176951 p1 NA
## 116 20224047 p1 NA
## 117 20199764 p1 1
## 118 20220594 p1 1
## 119 20212384 p1 NA
## 120 20220681 p1 6
## 121 20238651 p1 1
## 122 20202703 p1 NA
## 123 20240571 p1 NA
## 124 20201005 p1 NA
## 125 20196411 p1 NA
## 126 20201689 p1 NA
## 127 20193366 p1 NA
## 128 20198372 p1 NA
## 129 20196094 p1 NA
## 130 20192129 p1 1
## 131 20178692 p1 6
## 132 20188764 p1 NA
## 133 20190532 p1 1
## 134 20185916 p1 NA
## 135 20188454 p1 1
## 136 20187726 p1 NA
## 137 20162158 p1 NA
## 138 20160363 p1 NA
## 139 20182340 p1 NA
## 140 20166651 p1 NA
## 141 20162053 p1 1
## 142 20176345 p1 NA
## 143 20176844 p1 NA
## 144 20166761 p1 NA
## 145 20169554 p1 NA
## 146 20179170 p1 NA
## 147 20214569 p1 NA
## 148 20180903 p1 NA
## 149 20184232 p1 NA
## 150 20157198 p1 1
## 151 20191806 p1 1
## 152 20186672 p1 NA
## 153 20189971 p1 NA
## 154 20184267 p1 NA
## 155 20186662 p1 NA
## 156 20172662 p1 NA
## 157 20182689 p1 NA
## 158 20181029 p1 NA
## 159 20180510 p1 NA
## 160 20159642 p1 6
## 161 20170582 p1 NA
## 162 20167360 p1 1
## 163 20193400 p1 NA
## 164 20200133 p1 NA
## 165 20179151 p1 1
## 166 20196214 p1 NA
## 167 20195604 p1 NA
## 168 20195541 p1 NA
## 169 20195169 p1 NA
## 170 20193865 p1 NA
## 171 20196360 p1 NA
## 172 20193362 p1 NA
## 173 20198372 p1 NA
## 174 20190495 p1 NA
## 175 20196094 p1 NA
## 176 20185946 p1 NA
## 177 20186278 p1 NA
## 178 20171401 p1 1
## 179 20180609 p1 NA
## 180 20166600 p1 1
## 181 20180903 p1 NA
## 182 20170986 p1 NA
## 183 20236731 p1 1
## 184 20250444 p1 1
## 185 20242280 p1 1
## 186 20233319 p1 1
## 187 20215247 p1 1
## 188 20229615 p1 NA
## 189 20220663 p1 1
## 190 20224442 p1 1
## 191 20214531 p1 1
## 192 20226184 p1 NA
## 193 20224038 p1 NA
## 194 20215193 p1 NA
## 195 20226670 p1 NA
## 196 20223356 p1 NA
## 197 20224000 p1 NA
## 198 20214048 p1 1
## 199 20215243 p1 NA
## 200 20223975 p1 NA
## 201 20219016 p1 1
## 202 20183960 p1 1
## 203 20224535 p1 NA
## 204 20226665 p1 NA
## 205 20224423 p1 1
## 206 20190533 p1 1
## 207 20223604 p1 1
## 208 20207532 p1 NA
## 209 20224635 p1 NA
## 210 20205494 p1 1
## 211 20236745 p1 NA
## 212 20234608 p1 NA
## 213 20230001 p1 1
## 214 20223933 p1 NA
## 215 20214011 p1 NA
## 216 20224494 p1 1
## 217 20228771 p1 NA
## 218 20233482 p1 1
## 219 20234615 p1 NA
## 220 20234291 p1 NA
## 221 20226636 p1 NA
## 222 20230125 p1 NA
## 223 20163245 p1 NA
## 224 NA p1 NA
## 225 20166719 p2 NA
## 226 20170986 p2 NA
## 227 20172998 p2 NA
## 228 20162605 p2 NA
## 229 20177178 p2 NA
## 230 20186486 p2 NA
## 231 20158219 p2 NA
## 232 20163585 p2 NA
## 233 20167575 p2 NA
## 234 20159424 p2 NA
## 235 20167508 p2 NA
## 236 20167237 p2 NA
## 237 20148305 p2 NA
## 238 20230158 p2 NA
## 239 20163199 p2 8
## 240 20171304 p2 NA
## 241 20184211 p2 NA
## 242 20169505 p2 NA
## 243 20174623 p2 NA
## 244 20167254 p2 NA
## 245 20163262 p2 NA
## 246 20165724 p2 NA
## 247 20167073 p2 NA
## 248 20177112 p2 NA
## 249 20158301 p2 8
## 250 20181063 p2 NA
## 251 20176261 p2 NA
## 252 20167360 p2 NA
## 253 20244869 p2 NA
## 254 20248972 p2 NA
## 255 20248912 p2 NA
## 256 2022222 p2 NA
## 257 20234614 p2 NA
## 258 20234597 p2 NA
## 259 2023876 p2 NA
## 260 20212552 p2 NA
## 261 20182650 p2 NA
## 262 20191049 p2 NA
## 263 20179164 p2 NA
## 264 20196421 p2 NA
## 265 20218653 p2 NA
## 266 20212318 p2 NA
## 267 20212416 p2 NA
## 268 20211072 p2 NA
## 269 20211146 p2 NA
## 270 20212320 p2 NA
## 271 20209330 p2 NA
## 272 20204740 p2 NA
## 273 20204308 p2 NA
## 274 20200085 p2 NA
## 275 20205361 p2 NA
## 276 20205332 p2 NA
## 277 20196165 p2 NA
## 278 20199506 p2 NA
## 279 20196408 p2 NA
## 280 20195722 p2 6
## 281 20192199 p2 NA
## 282 20210988 p2 NA
## 283 20204722 p2 NA
## 284 20205498 p2 NA
## 285 20178358 p2 6
## 286 20215240 p2 NA
## 287 20215310 p2 NA
## 288 20214506 p2 NA
## 289 2020436 p2 NA
## 290 20214971 p2 NA
## 291 20224458 p2 NA
## 292 20224521 p2 NA
## 293 20217238 p2 NA
## 294 20216317 p2 NA
## 295 20211127 p2 NA
## 296 20190115 p2 NA
## 297 20199793 p2 NA
## 298 20181045 p2 NA
## 299 20185546 p2 NA
## 300 20201719 p2 NA
## 301 20190383 p2 NA
## 302 20201323 p2 NA
## 303 20192932 p2 NA
## 304 20170696 p2 NA
## 305 20247095 p2 NA
## 306 20244282 p2 2
## 307 20242353 p2 1
## 308 20228025 p2 NA
## 309 20241299 p2 2
## 310 20205465 p2 5
## 311 20209150 p2 NA
## 312 20217194 p2 NA
## 313 20219047 p2 NA
## 314 20217191 p2 NA
## 315 20193224 p2 6
## 316 20224412 p2 NA
## 317 20283871 p2 NA
## 318 20242105 p2 NA
## 319 20240551 p2 NA
## 320 20226613 p2 NA
## 321 20236785 p2 NA
## 322 234673 p2 NA
## 323 20234570 p2 NA
## 324 20230191 p2 NA
## 325 20219003 p2 2
## 326 20195506 p2 NA
## 327 20205279 p2 NA
## 328 20234547 p2 NA
## 329 20223517 p2 NA
## 330 20218994 p2 NA
## 331 20224467 p2 NA
## 332 20216908 p2 6
## 333 20205146 p2 NA
## 334 20233917 p2 NA
## 335 20212313 p2 NA
## 336 20166635 p2 NA
## 337 20163253 p2 NA
## 338 20172954 p2 NA
## 339 20176951 p2 NA
## 340 20224047 p2 NA
## 341 20199764 p2 NA
## 342 20220594 p2 3
## 343 20212384 p2 NA
## 344 20220681 p2 NA
## 345 20238651 p2 NA
## 346 20202703 p2 NA
## 347 20240571 p2 NA
## 348 20201005 p2 NA
## 349 20196411 p2 NA
## 350 20201689 p2 NA
## 351 20193366 p2 NA
## 352 20198372 p2 NA
## 353 20196094 p2 NA
## 354 20192129 p2 NA
## 355 20178692 p2 NA
## 356 20188764 p2 NA
## 357 20190532 p2 2
## 358 20185916 p2 NA
## 359 20188454 p2 NA
## 360 20187726 p2 NA
## 361 20162158 p2 NA
## 362 20160363 p2 NA
## 363 20182340 p2 NA
## 364 20166651 p2 NA
## 365 20162053 p2 NA
## 366 20176345 p2 NA
## 367 20176844 p2 NA
## 368 20166761 p2 NA
## 369 20169554 p2 NA
## 370 20179170 p2 NA
## 371 20214569 p2 NA
## 372 20180903 p2 NA
## 373 20184232 p2 NA
## 374 20157198 p2 NA
## 375 20191806 p2 NA
## 376 20186672 p2 NA
## 377 20189971 p2 NA
## 378 20184267 p2 NA
## 379 20186662 p2 NA
## 380 20172662 p2 NA
## 381 20182689 p2 NA
## 382 20181029 p2 NA
## 383 20180510 p2 NA
## 384 20159642 p2 NA
## 385 20170582 p2 NA
## 386 20167360 p2 NA
## 387 20193400 p2 NA
## 388 20200133 p2 NA
## 389 20179151 p2 NA
## 390 20196214 p2 NA
## 391 20195604 p2 NA
## 392 20195541 p2 NA
## 393 20195169 p2 NA
## 394 20193865 p2 NA
## 395 20196360 p2 NA
## 396 20193362 p2 NA
## 397 20198372 p2 NA
## 398 20190495 p2 NA
## 399 20196094 p2 NA
## 400 20185946 p2 NA
## 401 20186278 p2 NA
## 402 20171401 p2 2
## 403 20180609 p2 NA
## 404 20166600 p2 NA
## 405 20180903 p2 NA
## 406 20170986 p2 NA
## 407 20236731 p2 NA
## 408 20250444 p2 NA
## 409 20242280 p2 NA
## 410 20233319 p2 NA
## 411 20215247 p2 NA
## 412 20229615 p2 NA
## 413 20220663 p2 NA
## 414 20224442 p2 NA
## 415 20214531 p2 NA
## 416 20226184 p2 NA
## 417 20224038 p2 NA
## 418 20215193 p2 NA
## 419 20226670 p2 NA
## 420 20223356 p2 NA
## 421 20224000 p2 NA
## 422 20214048 p2 NA
## 423 20215243 p2 NA
## 424 20223975 p2 NA
## 425 20219016 p2 NA
## 426 20183960 p2 1
## 427 20224535 p2 NA
## 428 20226665 p2 NA
## 429 20224423 p2 NA
## 430 20190533 p2 1
## 431 20223604 p2 NA
## 432 20207532 p2 NA
## 433 20224635 p2 NA
## 434 20205494 p2 NA
## 435 20236745 p2 NA
## 436 20234608 p2 NA
## 437 20230001 p2 NA
## 438 20223933 p2 NA
## 439 20214011 p2 NA
## 440 20224494 p2 NA
## 441 20228771 p2 NA
## 442 20233482 p2 NA
## 443 20234615 p2 NA
## 444 20234291 p2 NA
## 445 20226636 p2 NA
## 446 20230125 p2 NA
## 447 20163245 p2 NA
## 448 NA p2 NA
## 449 20166719 p3 NA
## 450 20170986 p3 NA
## 451 20172998 p3 NA
## 452 20162605 p3 NA
## 453 20177178 p3 NA
## 454 20186486 p3 NA
## 455 20158219 p3 NA
## 456 20163585 p3 NA
## 457 20167575 p3 NA
## 458 20159424 p3 NA
## 459 20167508 p3 NA
## 460 20167237 p3 NA
## 461 20148305 p3 NA
## 462 20230158 p3 NA
## 463 20163199 p3 NA
## 464 20171304 p3 NA
## 465 20184211 p3 NA
## 466 20169505 p3 NA
## 467 20174623 p3 NA
## 468 20167254 p3 NA
## 469 20163262 p3 NA
## 470 20165724 p3 NA
## 471 20167073 p3 NA
## 472 20177112 p3 NA
## 473 20158301 p3 NA
## 474 20181063 p3 NA
## 475 20176261 p3 NA
## 476 20167360 p3 NA
## 477 20244869 p3 NA
## 478 20248972 p3 NA
## 479 20248912 p3 NA
## 480 2022222 p3 NA
## 481 20234614 p3 NA
## 482 20234597 p3 NA
## 483 2023876 p3 NA
## 484 20212552 p3 NA
## 485 20182650 p3 NA
## 486 20191049 p3 NA
## 487 20179164 p3 NA
## 488 20196421 p3 NA
## 489 20218653 p3 NA
## 490 20212318 p3 NA
## 491 20212416 p3 NA
## 492 20211072 p3 NA
## 493 20211146 p3 NA
## 494 20212320 p3 NA
## 495 20209330 p3 NA
## 496 20204740 p3 NA
## 497 20204308 p3 NA
## 498 20200085 p3 NA
## 499 20205361 p3 NA
## 500 20205332 p3 NA
## 501 20196165 p3 NA
## 502 20199506 p3 NA
## 503 20196408 p3 NA
## 504 20195722 p3 NA
## 505 20192199 p3 NA
## 506 20210988 p3 NA
## 507 20204722 p3 NA
## 508 20205498 p3 NA
## 509 20178358 p3 2
## 510 20215240 p3 NA
## 511 20215310 p3 NA
## 512 20214506 p3 NA
## 513 2020436 p3 NA
## 514 20214971 p3 NA
## 515 20224458 p3 NA
## 516 20224521 p3 NA
## 517 20217238 p3 NA
## 518 20216317 p3 NA
## 519 20211127 p3 NA
## 520 20190115 p3 NA
## 521 20199793 p3 NA
## 522 20181045 p3 NA
## 523 20185546 p3 NA
## 524 20201719 p3 NA
## 525 20190383 p3 NA
## 526 20201323 p3 NA
## 527 20192932 p3 NA
## 528 20170696 p3 NA
## 529 20247095 p3 NA
## 530 20244282 p3 4
## 531 20242353 p3 NA
## 532 20228025 p3 NA
## 533 20241299 p3 NA
## 534 20205465 p3 NA
## 535 20209150 p3 NA
## 536 20217194 p3 NA
## 537 20219047 p3 NA
## 538 20217191 p3 NA
## 539 20193224 p3 NA
## 540 20224412 p3 NA
## 541 20283871 p3 NA
## 542 20242105 p3 NA
## 543 20240551 p3 NA
## 544 20226613 p3 NA
## 545 20236785 p3 NA
## 546 234673 p3 NA
## 547 20234570 p3 NA
## 548 20230191 p3 NA
## 549 20219003 p3 NA
## 550 20195506 p3 NA
## 551 20205279 p3 NA
## 552 20234547 p3 NA
## 553 20223517 p3 NA
## 554 20218994 p3 NA
## 555 20224467 p3 NA
## 556 20216908 p3 NA
## 557 20205146 p3 NA
## 558 20233917 p3 NA
## 559 20212313 p3 NA
## 560 20166635 p3 NA
## 561 20163253 p3 NA
## 562 20172954 p3 NA
## 563 20176951 p3 NA
## 564 20224047 p3 NA
## 565 20199764 p3 NA
## 566 20220594 p3 NA
## 567 20212384 p3 NA
## 568 20220681 p3 NA
## 569 20238651 p3 NA
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## 571 20240571 p3 NA
## 572 20201005 p3 NA
## 573 20196411 p3 NA
## 574 20201689 p3 NA
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## 581 20190532 p3 NA
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## 606 20181029 p3 NA
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## 620 20193362 p3 NA
## 621 20198372 p3 NA
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## 635 20215247 p3 NA
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## 654 20190533 p3 6
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## 1041 20169554 p5 NA
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## 1043 20214569 p5 NA
## 1044 20180903 p5 NA
## 1045 20184232 p5 NA
## 1046 20157198 p5 NA
## 1047 20191806 p5 NA
## 1048 20186672 p5 NA
## 1049 20189971 p5 NA
## 1050 20184267 p5 NA
## 1051 20186662 p5 NA
## 1052 20172662 p5 NA
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## 1054 20181029 p5 NA
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## 1057 20170582 p5 NA
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## 1059 20193400 p5 NA
## 1060 20200133 p5 NA
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## 1062 20196214 p5 NA
## 1063 20195604 p5 NA
## 1064 20195541 p5 NA
## 1065 20195169 p5 NA
## 1066 20193865 p5 NA
## 1067 20196360 p5 NA
## 1068 20193362 p5 NA
## 1069 20198372 p5 NA
## 1070 20190495 p5 NA
## 1071 20196094 p5 NA
## 1072 20185946 p5 NA
## 1073 20186278 p5 NA
## 1074 20171401 p5 NA
## 1075 20180609 p5 NA
## 1076 20166600 p5 NA
## 1077 20180903 p5 NA
## 1078 20170986 p5 NA
## 1079 20236731 p5 NA
## 1080 20250444 p5 NA
## 1081 20242280 p5 NA
## 1082 20233319 p5 NA
## 1083 20215247 p5 NA
## 1084 20229615 p5 NA
## 1085 20220663 p5 NA
## 1086 20224442 p5 NA
## 1087 20214531 p5 NA
## 1088 20226184 p5 NA
## 1089 20224038 p5 NA
## 1090 20215193 p5 NA
## 1091 20226670 p5 NA
## 1092 20223356 p5 NA
## 1093 20224000 p5 NA
## 1094 20214048 p5 NA
## 1095 20215243 p5 NA
## 1096 20223975 p5 NA
## 1097 20219016 p5 NA
## 1098 20183960 p5 NA
## 1099 20224535 p5 NA
## 1100 20226665 p5 NA
## 1101 20224423 p5 NA
## 1102 20190533 p5 2
## 1103 20223604 p5 NA
## 1104 20207532 p5 NA
## 1105 20224635 p5 NA
## 1106 20205494 p5 NA
## 1107 20236745 p5 NA
## 1108 20234608 p5 NA
## 1109 20230001 p5 NA
## 1110 20223933 p5 NA
## 1111 20214011 p5 NA
## 1112 20224494 p5 NA
## 1113 20228771 p5 NA
## 1114 20233482 p5 NA
## 1115 20234615 p5 NA
## 1116 20234291 p5 NA
## 1117 20226636 p5 NA
## 1118 20230125 p5 NA
## 1119 20163245 p5 NA
## 1120 NA p5 NAd3= melt (d, id= c("id1"), measure.vars= c("g1d1", "g2d1", "g3d1", "g4d1", "g5d1"))
names (d3)[names (d3)=='variable']= 'loca2'
names (d3)[names (d3)=='value']= 'classi2'Trộn 2 bộ dữ liệu
d4= merge (d2, d3, by= c("id1"), all.x= T, all.y= T)- Mức độ loét và vị trí loét (classi: vị trí loét, classi2: độ loét)
Desc(factor (d4$classi) ~ factor(d4$classi2))## ------------------------------------------------------------------------------
## factor(d4$classi) ~ factor(d4$classi2)
##
## Summary:
## n: 154, rows: 7, columns: 4
##
## Pearson's Chi-squared test:
## X-squared = 16, df = 18, p-value = 0.6
## Log likelihood ratio (G-test) test of independence:
## G = 16, X-squared df = 18, p-value = 0.6
## Mantel-Haenszel Chi-squared:
## X-squared = 0.2, df = 1, p-value = 0.7
##
## Warning message:
## Exp. counts < 5: Chi-squared approx. may be incorrect!!
##
##
## Phi-Coefficient 0.324
## Contingency Coeff. 0.308
## Cramer's V 0.187
##
##
## factor(d4$classi2) 1 2 3 4 Sum
## factor(d4$classi)
##
## 1 freq 35 61 4 1 101
## perc 22.7% 39.6% 2.6% 0.6% 65.6%
## p.row 34.7% 60.4% 4.0% 1.0% .
## p.col 63.6% 67.0% 66.7% 50.0% .
##
## 2 freq 6 14 0 0 20
## perc 3.9% 9.1% 0.0% 0.0% 13.0%
## p.row 30.0% 70.0% 0.0% 0.0% .
## p.col 10.9% 15.4% 0.0% 0.0% .
##
## 3 freq 1 1 0 0 2
## perc 0.6% 0.6% 0.0% 0.0% 1.3%
## p.row 50.0% 50.0% 0.0% 0.0% .
## p.col 1.8% 1.1% 0.0% 0.0% .
##
## 4 freq 3 0 0 0 3
## perc 1.9% 0.0% 0.0% 0.0% 1.9%
## p.row 100.0% 0.0% 0.0% 0.0% .
## p.col 5.5% 0.0% 0.0% 0.0% .
##
## 5 freq 1 1 0 0 2
## perc 0.6% 0.6% 0.0% 0.0% 1.3%
## p.row 50.0% 50.0% 0.0% 0.0% .
## p.col 1.8% 1.1% 0.0% 0.0% .
##
## 6 freq 9 11 1 1 22
## perc 5.8% 7.1% 0.6% 0.6% 14.3%
## p.row 40.9% 50.0% 4.5% 4.5% .
## p.col 16.4% 12.1% 16.7% 50.0% .
##
## 8 freq 0 3 1 0 4
## perc 0.0% 1.9% 0.6% 0.0% 2.6%
## p.row 0.0% 75.0% 25.0% 0.0% .
## p.col 0.0% 3.3% 16.7% 0.0% .
##
## Sum freq 55 91 6 2 154
## perc 35.7% 59.1% 3.9% 1.3% 100.0%
## p.row . . . . .
## p.col . . . . .
## 
- Vị trí và thời gian xuất hiện loét tỳ đè (không có dữ kiện)