Reporte Dr. Omar Quintero
MDatos
2022-08-10
Análisis de datos para tesis del Dr. Omar Quintero
la base d
library(readxl)
demogradromar <- read_excel("C:/Users/fidel/OneDrive - CINVESTAV/PROYECTO MDatos/TRABAJOS/Dr Omar quintero entrega 12-08/demogradromar.xlsx")
View(demogradromar)
dbomar <- demogradromar
#para hacer las tablas trabajaremos con los siguientes paquetes
#Trabajamos con estos paquetes
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4
## ✔ tibble 3.1.7 ✔ dplyr 1.0.9
## ✔ tidyr 1.2.0 ✔ stringr 1.4.0
## ✔ readr 2.1.2 ✔ forcats 0.5.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(magrittr)##
## Attaching package: 'magrittr'## The following object is masked from 'package:purrr':
##
## set_names## The following object is masked from 'package:tidyr':
##
## extractlibrary(gt)
names(dbomar)## [1] "paquete" "sexo" "edad"
## [4] "peso" "talla" "gporh"
## [7] "dx" "díasextraccion" "cantidadpg"
## [10] "mortalidad28d" "tiepouci" "ventilaciondias"
## [13] "vasoactivocardiacodias" "soporterenaldias" "eventosinfecciosos"
## [16] "eventosadbersos"str(dbomar)## tibble [26 × 16] (S3: tbl_df/tbl/data.frame)
## $ paquete : chr [1:26] "Gfresco" "Gfresco" "Gfresco" "Gfresco" ...
## $ sexo : chr [1:26] "Masculino" "Masculino" "Masculino" "Masculino" ...
## $ edad : num [1:26] 60 30 21 23 22 24 56 24 24 45 ...
## $ peso : num [1:26] 82.5 79 79 91 87 ...
## $ talla : num [1:26] 176 180 189 172 187 163 170 176 180 175 ...
## $ gporh : chr [1:26] "O Positivo" "O Positivo" "A Positivo" "O Positivo" ...
## $ dx : chr [1:26] "TCE Severo" "TCE Severo" "TCE Severo" "TCE Severo" ...
## $ díasextraccion : num [1:26] 15 15 15 15 14 14 14 14 13 13 ...
## $ cantidadpg : num [1:26] 2 1 1 2 1 2 2 2 3 1 ...
## $ mortalidad28d : chr [1:26] "SI" "NO" "NO" "NO" ...
## $ tiepouci : num [1:26] 10 3 9 6 10 8 10 16 7 6 ...
## $ ventilaciondias : num [1:26] 28 1 9 5 8 6 7 16 7 6 ...
## $ vasoactivocardiacodias: num [1:26] 10 1 8 5 7 5 7 16 6 5 ...
## $ soporterenaldias : num [1:26] 0 0 0 0 0 0 0 0 0 0 ...
## $ eventosinfecciosos : chr [1:26] "SI" "NO" "SI" "SI" ...
## $ eventosadbersos : chr [1:26] "NO" "NO" "NO" "NO" ...dbomar$tiepouci = as.numeric(dbomar$tiepouci)
dbomar %>% gt()| paquete | sexo | edad | peso | talla | gporh | dx | díasextraccion | cantidadpg | mortalidad28d | tiepouci | ventilaciondias | vasoactivocardiacodias | soporterenaldias | eventosinfecciosos | eventosadbersos |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Gfresco | Masculino | 60 | 82.5 | 176 | O Positivo | TCE Severo | 15 | 2 | SI | 10 | 28 | 10 | 0 | SI | NO |
| Gfresco | Masculino | 30 | 79.0 | 180 | O Positivo | TCE Severo | 15 | 1 | NO | 3 | 1 | 1 | 0 | NO | NO |
| Gfresco | Masculino | 21 | 79.0 | 189 | A Positivo | TCE Severo | 15 | 1 | NO | 9 | 9 | 8 | 0 | SI | NO |
| Gfresco | Masculino | 23 | 91.0 | 172 | O Positivo | TCE Severo | 15 | 2 | NO | 6 | 5 | 5 | 0 | SI | NO |
| Gfresco | Masculino | 22 | 87.0 | 187 | O Positivo | TCE Severo | 14 | 1 | NO | 10 | 8 | 7 | 0 | SI | NO |
| Gfresco | Masculino | 24 | 64.0 | 163 | O Positivo | TCE Severo | 14 | 2 | NO | 8 | 6 | 5 | 0 | SI | NO |
| Gfresco | Masculino | 56 | 67.5 | 170 | O Positivo | TCE Severo | 14 | 2 | NO | 10 | 7 | 7 | 0 | SI | NO |
| Gfresco | Masculino | 24 | 96.5 | 176 | A Positivo | TCE Severo | 14 | 2 | SI | 16 | 16 | 16 | 0 | SI | NO |
| Gfresco | Masculino | 24 | 98.0 | 180 | O Positivo | TCE Severo | 13 | 3 | NO | 7 | 7 | 6 | 0 | SI | NO |
| Gfresco | Masculino | 45 | 100.5 | 175 | O Positivo | TCE Severo | 13 | 1 | NO | 6 | 6 | 5 | 0 | SI | NO |
| Gfresco | Masculino | 32 | 87.0 | 187 | O Positivo | TCE Severo | 12 | 3 | NO | 8 | 4 | 4 | 0 | NO | NO |
| Gfresco | Femenino | 65 | 67.5 | 165 | O Positivo | TCE Severo | 10 | 1 | NO | 3 | 1 | 1 | 0 | NO | NO |
| Gfresco | Femenino | 28 | 91.0 | 178 | B Positivo | TCE Severo | 7 | 1 | SI | 12 | 19 | 12 | 0 | SI | NO |
| Gestandard | Femenino | 28 | 105.0 | 178 | B Negativo | TCE Severo | 38 | 2 | NO | 3 | 1 | 1 | 0 | SI | NO |
| Gestandard | Femenino | 44 | 49.0 | 156 | A Positivo | TCE Severo | 38 | 3 | NO | 8 | 14 | 5 | 0 | SI | NO |
| Gestandard | Masculino | 28 | 105.0 | 178 | A Positivo | TCE Severo | 26 | 3 | NO | 3 | 1 | NA | 0 | NO | NO |
| Gestandard | Masculino | 21 | 87.5 | 166 | A Positivo | TCE Severo | 24 | 1 | NO | 12 | 10 | 9 | 0 | SI | NO |
| Gestandard | Femenino | 45 | 58.0 | 160 | A Positivo | TCE Severo | 23 | 1 | NO | 16 | 16 | 12 | 0 | NO | NO |
| Gestandard | Femenino | 77 | 60.0 | 156 | A Positivo | TCE Severo | 18 | 3 | NO | 10 | 23 | 8 | 0 | SI | NO |
| Gestandard | Masculino | 45 | 93.0 | 169 | O Positivo | TCE Severo | 18 | 3 | SI | 15 | 19 | 15 | 0 | SI | NO |
| Gestandard | Masculino | 25 | 87.0 | 172 | O Positivo | TCE Severo | 17 | 2 | NO | 15 | 35 | 11 | 0 | SI | NO |
| Gestandard | Masculino | 41 | 91.0 | 164 | O Positivo | TCE Severo | 17 | 2 | SI | 6 | 6 | 6 | 0 | SI | NO |
| Gestandard | Femenino | 35 | 88.5 | 163 | A Positivo | TCE Severo | 17 | 1 | SI | 8 | 8 | 8 | 0 | SI | NO |
| Gestandard | Femenino | 44 | 59.8 | 167 | O Positivo | TCE Severo | 16 | 5 | NO | 7 | 18 | 6 | 0 | SI | NO |
| Gestandard | Femenino | 72 | 63.0 | 163 | A Positivo | TCE Severo | 16 | 1 | SI | 15 | 15 | 15 | 0 | SI | NO |
| Gestandard | Masculino | 31 | 60.0 | 165 | O Positivo | TCE Severo | 16 | 1 | NO | 7 | 18 | 6 | 0 | SI | NO |
Tabla 1
En esta tabla se incluyerón las variables demografias y de los objetivos primarios y secundarios
library(gtsummary)
tb1demo<- dbomar %>% select(paquete, sexo, edad, peso, talla, gporh, dx, díasextraccion,
cantidadpg, mortalidad28d, tiepouci,ventilaciondias, vasoactivocardiacodias,
soporterenaldias, eventosinfecciosos,eventosadbersos) %>% tbl_summary (by=paquete,
type = list(tiepouci ~ "continuous")) %>%
add_p() %>% add_overall()## Warning for variable 'edad':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'peso':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'talla':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## There was an error in 'add_p()/add_difference()' for variable 'dx', p-value omitted:
## Error in stats::chisq.test(x = c("TCE Severo", "TCE Severo", "TCE Severo", : 'x' and 'y' must have at least 2 levels## Warning for variable 'díasextraccion':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'tiepouci':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ventilaciondias':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'vasoactivocardiacodias':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## There was an error in 'add_p()/add_difference()' for variable 'soporterenaldias', p-value omitted:
## Error in stats::chisq.test(x = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, : 'x' and 'y' must have at least 2 levels## There was an error in 'add_p()/add_difference()' for variable 'eventosadbersos', p-value omitted:
## Error in stats::chisq.test(x = c("NO", "NO", "NO", "NO", "NO", "NO", "NO", : 'x' and 'y' must have at least 2 levelstb1demo## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead| Characteristic | Overall, N = 261 | Gestandard, N = 131 | Gfresco, N = 131 | p-value2 |
|---|---|---|---|---|
| sexo | 0.10 | |||
| Femenino | 9 (35%) | 7 (54%) | 2 (15%) | |
| Masculino | 17 (65%) | 6 (46%) | 11 (85%) | |
| edad | 32 (24, 45) | 41 (28, 45) | 28 (24, 45) | 0.2 |
| peso | 87 (65, 91) | 87 (60, 91) | 87 (79, 91) | 0.4 |
| talla | 171 (164, 178) | 165 (163, 169) | 176 (172, 180) | 0.004 |
| gporh | 0.062 | |||
| A Positivo | 9 (35%) | 7 (54%) | 2 (15%) | |
| B Negativo | 1 (3.8%) | 1 (7.7%) | 0 (0%) | |
| B Positivo | 1 (3.8%) | 0 (0%) | 1 (7.7%) | |
| O Positivo | 15 (58%) | 5 (38%) | 10 (77%) | |
| dx | ||||
| TCE Severo | 26 (100%) | 13 (100%) | 13 (100%) | |
| díasextraccion | 16 (14, 18) | 18 (17, 24) | 14 (13, 15) | <0.001 |
| cantidadpg | 0.7 | |||
| 1 | 11 (42%) | 5 (38%) | 6 (46%) | |
| 2 | 8 (31%) | 3 (23%) | 5 (38%) | |
| 3 | 6 (23%) | 4 (31%) | 2 (15%) | |
| 5 | 1 (3.8%) | 1 (7.7%) | 0 (0%) | |
| mortalidad28d | >0.9 | |||
| NO | 19 (73%) | 9 (69%) | 10 (77%) | |
| SI | 7 (27%) | 4 (31%) | 3 (23%) | |
| tiepouci | 8.0 (6.2, 11.5) | 8.0 (7.0, 15.0) | 8.0 (6.0, 10.0) | 0.6 |
| ventilaciondias | 8 (6, 18) | 15 (8, 18) | 7 (5, 9) | 0.13 |
| vasoactivocardiacodias | 7.0 (5.0, 10.0) | 8.0 (6.0, 11.2) | 6.0 (5.0, 8.0) | 0.2 |
| Unknown | 1 | 1 | 0 | |
| soporterenaldias | 0 (0%) | 0 (0%) | 0 (0%) | |
| eventosinfecciosos | >0.9 | |||
| NO | 5 (19%) | 2 (15%) | 3 (23%) | |
| SI | 21 (81%) | 11 (85%) | 10 (77%) | |
| eventosadbersos | ||||
| NO | 26 (100%) | 13 (100%) | 13 (100%) | |
| 1 n (%); Median (IQR) | ||||
| 2 Fisher's exact test; Wilcoxon rank sum test | ||||
Análisis de datos cuantitativos (variables continuas)
Tabla 2. Se muestra las variables cuantitativas
library(readxl)
continuasdromar <- read_excel("C:/Users/fidel/OneDrive - CINVESTAV/PROYECTO MDatos/TRABAJOS/Dr Omar quintero entrega 12-08/continuasdromar.xlsx")
View(continuasdromar)
continuasdromar %>% tbl_summary(by=paquete) %>% add_p()## Warning for variable 'TAM_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TAM_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TAM_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FC_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FC_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FC_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FR_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FR_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FR_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TEMP_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TEMP_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TEMP_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'GC_FICK POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'GC_Indexado PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN_pH_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pH_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pCO2_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pCO2_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN_pO2_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. HCO3 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. HCO3 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. BE PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. BE POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. SO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. SO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pH PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pH POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pCO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pCO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. HCO3 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. HCO3 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. BE PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. BE POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. SO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'Hb PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'Hb POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'HTC PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'HTC POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LEUCOS PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LEUCOS POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'PROCA PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'PROCA POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LACTATO PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LACTATO POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead| Characteristic | gestandard, N = 131 | gfresco, N = 131 | p-value2 |
|---|---|---|---|
| paqueteg | 0.3 | ||
| 1 | 5 (38%) | 6 (46%) | |
| 2 | 2 (15%) | 5 (38%) | |
| 3 | 5 (38%) | 2 (15%) | |
| 5 | 1 (7.7%) | 0 (0%) | |
| TA_PRE | 0.7 | ||
| 100/58 | 0 (0%) | 1 (7.7%) | |
| 104/52 | 0 (0%) | 1 (7.7%) | |
| 106/66 | 0 (0%) | 1 (7.7%) | |
| 107/53 | 1 (7.7%) | 0 (0%) | |
| 108/55 | 1 (7.7%) | 0 (0%) | |
| 114/59 | 1 (7.7%) | 0 (0%) | |
| 115/57 | 1 (7.7%) | 1 (7.7%) | |
| 116/55 | 1 (7.7%) | 0 (0%) | |
| 119/83 | 0 (0%) | 1 (7.7%) | |
| 120/105 | 1 (7.7%) | 0 (0%) | |
| 124/61 | 0 (0%) | 1 (7.7%) | |
| 124/74 | 0 (0%) | 1 (7.7%) | |
| 124/78 | 0 (0%) | 2 (15%) | |
| 130/64 | 0 (0%) | 1 (7.7%) | |
| 132/70 | 1 (7.7%) | 0 (0%) | |
| 135/68 | 1 (7.7%) | 0 (0%) | |
| 135/77 | 0 (0%) | 1 (7.7%) | |
| 141/74 | 1 (7.7%) | 0 (0%) | |
| 143/69 | 0 (0%) | 1 (7.7%) | |
| 147/57 | 0 (0%) | 1 (7.7%) | |
| 156/82 | 1 (7.7%) | 0 (0%) | |
| 158/104 | 1 (7.7%) | 0 (0%) | |
| 189/100 | 1 (7.7%) | 0 (0%) | |
| 90/56 | 1 (7.7%) | 0 (0%) | |
| TA_TRANS | 0.7 | ||
| 107/53 | 0 (0%) | 1 (7.7%) | |
| 109/70 | 0 (0%) | 1 (7.7%) | |
| 112/62 | 1 (7.7%) | 0 (0%) | |
| 113/66 | 0 (0%) | 1 (7.7%) | |
| 115/54 | 1 (7.7%) | 0 (0%) | |
| 115/57 | 1 (7.7%) | 0 (0%) | |
| 121/62 | 0 (0%) | 1 (7.7%) | |
| 122/63 | 1 (7.7%) | 0 (0%) | |
| 124/70 | 0 (0%) | 1 (7.7%) | |
| 125/69 | 0 (0%) | 1 (7.7%) | |
| 125/76 | 0 (0%) | 2 (15%) | |
| 127/63 | 1 (7.7%) | 0 (0%) | |
| 135/68 | 1 (7.7%) | 1 (7.7%) | |
| 135/95 | 1 (7.7%) | 0 (0%) | |
| 136/71 | 1 (7.7%) | 0 (0%) | |
| 136/79 | 1 (7.7%) | 0 (0%) | |
| 137/52 | 0 (0%) | 1 (7.7%) | |
| 140/69 | 0 (0%) | 1 (7.7%) | |
| 146/77 | 1 (7.7%) | 0 (0%) | |
| 148/89 | 1 (7.7%) | 0 (0%) | |
| 153/99 | 1 (7.7%) | 0 (0%) | |
| 92/53 | 1 (7.7%) | 0 (0%) | |
| 95/60 | 0 (0%) | 1 (7.7%) | |
| 98/61 | 0 (0%) | 1 (7.7%) | |
| TA_POST | 0.5 | ||
| 100/60 | 0 (0%) | 1 (7.7%) | |
| 100/78 | 0 (0%) | 1 (7.7%) | |
| 107/68 | 0 (0%) | 1 (7.7%) | |
| 110/51 | 0 (0%) | 1 (7.7%) | |
| 113/64 | 0 (0%) | 1 (7.7%) | |
| 114/54 | 1 (7.7%) | 0 (0%) | |
| 114/57 | 1 (7.7%) | 0 (0%) | |
| 115/69 | 0 (0%) | 1 (7.7%) | |
| 117/52 | 1 (7.7%) | 0 (0%) | |
| 117/74 | 0 (0%) | 1 (7.7%) | |
| 126/65 | 1 (7.7%) | 0 (0%) | |
| 127/66 | 0 (0%) | 1 (7.7%) | |
| 128/61 | 1 (7.7%) | 0 (0%) | |
| 128/72 | 0 (0%) | 1 (7.7%) | |
| 129/61 | 1 (7.7%) | 0 (0%) | |
| 130/76 | 1 (7.7%) | 0 (0%) | |
| 131/83 | 0 (0%) | 2 (15%) | |
| 132/60 | 0 (0%) | 1 (7.7%) | |
| 134/70 | 1 (7.7%) | 0 (0%) | |
| 135/78 | 1 (7.7%) | 0 (0%) | |
| 141/91 | 1 (7.7%) | 0 (0%) | |
| 146/72 | 0 (0%) | 1 (7.7%) | |
| 150/66 | 1 (7.7%) | 0 (0%) | |
| 163/108 | 1 (7.7%) | 0 (0%) | |
| 91/52 | 1 (7.7%) | 0 (0%) | |
| TAM_PRE | 90 (75, 107) | 87 (79, 93) | 0.8 |
| TAM_TRANS | 90 (79, 100) | 83 (80, 90) | 0.2 |
| TAM_POST | 85 (76, 94) | 85 (81, 90) | 0.9 |
| FC_PRE | 89 (75, 100) | 79 (78, 100) | 0.9 |
| FC_TRANS | 85 (75, 94) | 85 (73, 92) | 0.7 |
| FC_POST | 82 (61, 92) | 79 (70, 96) | >0.9 |
| FR_PRE | 15.0 (12.0, 16.0) | 17.0 (16.0, 20.0) | 0.011 |
| FR_TRANS | 15.00 (13.00, 16.00) | 17.00 (16.00, 18.00) | 0.018 |
| FR_POST | 15.00 (14.00, 17.00) | 18.00 (17.00, 20.00) | 0.015 |
| SAO2_PRE | 0.14 | ||
| 93 | 0 (0%) | 1 (7.7%) | |
| 94 | 1 (7.7%) | 0 (0%) | |
| 95 | 0 (0%) | 1 (7.7%) | |
| 96 | 4 (31%) | 5 (38%) | |
| 97 | 2 (15%) | 3 (23%) | |
| 98 | 6 (46%) | 1 (7.7%) | |
| 99 | 0 (0%) | 2 (15%) | |
| SAO2_TRANS | 0.7 | ||
| 94 | 1 (7.7%) | 0 (0%) | |
| 95 | 0 (0%) | 1 (7.7%) | |
| 96 | 3 (23%) | 3 (23%) | |
| 97 | 4 (31%) | 2 (15%) | |
| 98 | 3 (23%) | 6 (46%) | |
| 99 | 1 (7.7%) | 0 (0%) | |
| 100 | 1 (7.7%) | 1 (7.7%) | |
| SAO2_POST | >0.9 | ||
| 96 | 3 (23%) | 3 (23%) | |
| 97 | 4 (31%) | 4 (31%) | |
| 98 | 4 (31%) | 3 (23%) | |
| 99 | 1 (7.7%) | 2 (15%) | |
| 100 | 1 (7.7%) | 1 (7.7%) | |
| TEMP_PRE | 36.50 (36.10, 37.00) | 37.50 (37.00, 37.60) | 0.016 |
| TEMP_TRANS | 36.50 (36.30, 37.00) | 37.50 (37.00, 37.70) | 0.010 |
| TEMP_POST | 36.50 (36.20, 37.00) | 37.50 (36.80, 37.70) | 0.018 |
| GC_FICK_PRE | 10 (5, 14) | 8 (7, 9) | 0.4 |
| GC_FICK POST | 8.8 (5.8, 13.3) | 10.3 (8.4, 12.1) | 0.5 |
| GC_Indexado PRE | 5.9 (3.0, 8.0) | 4.2 (3.7, 4.5) | 0.3 |
| GC_Idexado_POST | 5.31 (3.49, 6.37) | 4.95 (4.31, 5.69) | >0.9 |
| Vol._Sistólico_PRE | 86 (69, 184) | 87 (80, 116) | 0.8 |
| Vol. Sistólico_POST | 101 (81, 153) | 125 (101, 154) | 0.5 |
| Vol. Sistólico I._PRE | 59 (34, 97) | 43 (37, 57) | 0.4 |
| Vol_Sistólico_I_POST | >0.9 | ||
| 115.75 | 1 (7.7%) | 0 (0%) | |
| 35.43 | 1 (7.7%) | 0 (0%) | |
| 35.65 | 1 (7.7%) | 0 (0%) | |
| 39.42 | 1 (7.7%) | 0 (0%) | |
| 39.93 | 0 (0%) | 1 (7.7%) | |
| 40.299999999999997 | 1 (7.7%) | 0 (0%) | |
| 48.43 | 0 (0%) | 1 (7.7%) | |
| 51-81 | 0 (0%) | 1 (7.7%) | |
| 51.51 | 0 (0%) | 1 (7.7%) | |
| 51.62 | 0 (0%) | 1 (7.7%) | |
| 55.3 | 0 (0%) | 1 (7.7%) | |
| 57.58 | 0 (0%) | 1 (7.7%) | |
| 59.96 | 1 (7.7%) | 0 (0%) | |
| 61.66 | 1 (7.7%) | 0 (0%) | |
| 65.930000000000007 | 1 (7.7%) | 0 (0%) | |
| 67.31 | 1 (7.7%) | 0 (0%) | |
| 72.66 | 0 (0%) | 1 (7.7%) | |
| 73.77 | 0 (0%) | 1 (7.7%) | |
| 74.81 | 1 (7.7%) | 0 (0%) | |
| 75.81 | 0 (0%) | 1 (7.7%) | |
| 79.5 | 1 (7.7%) | 0 (0%) | |
| 82.4 | 0 (0%) | 1 (7.7%) | |
| 85.12 | 0 (0%) | 1 (7.7%) | |
| 88.42 | 1 (7.7%) | 0 (0%) | |
| 88.58 | 1 (7.7%) | 0 (0%) | |
| 94.9 | 0 (0%) | 1 (7.7%) | |
| VEN_pH_PRE | 7.32 (7.28, 7.40) | 7.36 (7.33, 7.40) | 0.2 |
| VEN. pH_POST | 7.41 (7.32, 7.43) | 7.35 (7.32, 7.41) | 0.3 |
| VEN. pCO2_PRE | 41.0 (33.0, 42.0) | 42.0 (39.0, 46.0) | 0.15 |
| VEN. pCO2_POST | 38 (36, 38) | 44 (40, 49) | 0.030 |
| VEN_pO2_PRE | 47 (43, 50) | 38 (35, 42) | 0.2 |
| VEN. pO2 POST | 45.0 (42.0, 55.0) | 45.0 (41.0, 45.0) | 0.3 |
| VEN. HCO3 PRE | 23.0 (16.8, 24.8) | 26.0 (24.2, 27.2) | 0.048 |
| VEN. HCO3 POST | 26.0 (22.6, 26.0) | 25.3 (22.8, 27.5) | 0.6 |
| VEN. BE PRE | -2.1 (-10.3, -0.2) | -1.3 (-6.2, 0.9) | 0.4 |
| VEN. BE POST | -0.4 (-8.3, 1.0) | -0.2 (-2.4, 1.4) | 0.3 |
| VEN. SO2 PRE | 70 (70, 83) | 68 (65, 70) | 0.061 |
| VEN. SO2 POST | 80.0 (78.0, 80.0) | 75.0 (73.0, 78.0) | 0.2 |
| ART. pH PRE | 7.41 (7.32, 7.44) | 7.41 (7.35, 7.41) | 0.9 |
| ART. pH POST | 7.42 (7.32, 7.45) | 7.42 (7.39, 7.45) | 0.7 |
| ART. pCO2 PRE | 33.0 (30.0, 36.0) | 36.0 (32.0, 40.0) | 0.2 |
| ART. pCO2 POST | 34.0 (33.0, 35.0) | 32.0 (30.0, 41.0) | 0.7 |
| ART. pO2 PRE | 93 (73, 112) | 92 (88, 124) | 0.4 |
| ART. pO2 POST | 114 (95, 116) | 103 (86, 112) | 0.2 |
| ART. HCO3 PRE | 22.3 (19.7, 23.8) | 22.4 (18.8, 26.0) | 0.6 |
| ART. HCO3 POST | 22.1 (19.6, 24.0) | 24.2 (20.9, 24.9) | 0.2 |
| ART. BE PRE | -2.2 (-6.5, -0.4) | -1.8 (-6.4, 1.2) | 0.7 |
| ART. BE POST | -0.4 (-6.0, -0.3) | -0.5 (-2.9, 1.1) | 0.5 |
| ART. SO2 PRE | 97.00 (97.00, 98.00) | 97.00 (97.00, 99.00) | 0.5 |
| ART. SO2 POST | 0.4 | ||
| 95 | 1 (7.7%) | 2 (15%) | |
| 96 | 0 (0%) | 3 (23%) | |
| 97 | 1 (7.7%) | 0 (0%) | |
| 98 | 5 (38%) | 5 (38%) | |
| 99 | 5 (38%) | 3 (23%) | |
| 100 | 1 (7.7%) | 0 (0%) | |
| Hb PRE | 8.00 (7.90, 8.10) | 8.00 (7.30, 8.50) | 0.9 |
| Hb POST | 8.60 (8.40, 9.40) | 8.50 (7.80, 9.00) | 0.6 |
| HTC PRE | 24.7 (23.7, 24.7) | 23.8 (22.0, 27.3) | 0.4 |
| HTC POST | 26.5 (25.4, 28.5) | 25.8 (23.5, 28.5) | 0.6 |
| LEUCOS PRE | 12.8 (10.2, 14.1) | 14.0 (9.6, 14.9) | 0.7 |
| LEUCOS POST | 12.7 (10.8, 13.4) | 13.4 (9.5, 14.1) | >0.9 |
| PROCA PRE | 0.22 (0.07, 0.43) | 0.83 (0.23, 5.58) | 0.031 |
| PROCA POST | 0 (0, 0) | 1 (0, 5) | 0.022 |
| LACTATO PRE | 1.50 (0.80, 2.10) | 1.40 (1.10, 2.90) | 0.4 |
| LACTATO POST | 1.00 (0.70, 1.90) | 1.20 (0.70, 1.90) | >0.9 |
| 1 n (%); Median (IQR) | |||
| 2 Fisher's exact test; Wilcoxon rank sum test; Wilcoxon rank sum exact test | |||
str(continuasdromar)## tibble [26 × 62] (S3: tbl_df/tbl/data.frame)
## $ paqueteg : num [1:26] 2 1 1 2 1 2 2 2 3 1 ...
## $ paquete : chr [1:26] "gfresco" "gfresco" "gfresco" "gfresco" ...
## $ TA_PRE : chr [1:26] "124/74" "147/57" "130/64" "106/66" ...
## $ TA_TRANS : chr [1:26] "125/69" "137/52" "140/69" "109/70" ...
## $ TA_POST : chr [1:26] "113/64" "132/60" "146/72" "107/68" ...
## $ TAM_PRE : num [1:26] 90 87 86 79 95 96 68 76 93 82 ...
## $ TAM_TRANS : num [1:26] 87.6 80 93 83 82 72 71 82 90 73 ...
## $ TAM_POST : num [1:26] 80.3 84 97 81 73 85 71 84 90 88 ...
## $ FC_PRE : num [1:26] 85 78 79 93 111 78 113 71 114 100 ...
## $ FC_TRANS : num [1:26] 85 77 75 88 93 92 112 88 105 73 ...
## $ FC_POST : num [1:26] 73 70 75 90 79 96 108 97 100 79 ...
## $ FR_PRE : num [1:26] 20 18 15 20 15 17 15 18 23 16 ...
## $ FR_TRANS : num [1:26] 18 18 16 20 14 16 16 16 19 16 ...
## $ FR_POST : num [1:26] 20 18 14 20 17 20 14 19 21 16 ...
## $ SAO2_PRE : num [1:26] 95 96 96 97 99 99 97 97 93 96 ...
## $ SAO2_TRANS : num [1:26] 95 96 96 98 100 97 98 97 98 98 ...
## $ SAO2_POST : num [1:26] 96 96 96 97 100 97 98 97 98 98 ...
## $ TEMP_PRE : num [1:26] 39 36.3 37.2 37.7 36.8 37.5 37 36.1 38.3 37.6 ...
## $ TEMP_TRANS : num [1:26] 39.3 36.4 37 37.8 37 37.7 37.2 36 38.2 37.6 ...
## $ TEMP_POST : num [1:26] 39 36.4 37 37.8 36.8 37.7 37.3 36 38.2 37.5 ...
## $ GC_FICK_PRE : num [1:26] 7.38 5.07 6.64 8.99 8.85 ...
## $ GC_FICK POST : num [1:26] 10.82 7.69 11.58 9.09 13.84 ...
## $ GC_Indexado PRE : num [1:26] 3.67 2.55 3.26 4.31 4.17 ...
## $ GC_Idexado_POST : num [1:26] 5.39 3.87 5.69 4.36 6.51 4.95 4.31 5.59 9.49 4.08 ...
## $ Vol._Sistólico_PRE : num [1:26] 86.8 65 84.1 96.7 79.8 ...
## $ Vol. Sistólico_POST : num [1:26] 148 110 154 101 175 ...
## $ Vol. Sistólico I._PRE: num [1:26] 43.2 32.7 41.3 46.4 37.5 ...
## $ Vol_Sistólico_I_POST : chr [1:26] "73.77" "55.3" "75.81" "48.43" ...
## $ VEN_pH_PRE : num [1:26] 7.4 7.36 7.41 7.36 7.33 7.35 7.36 7.31 7.25 7.32 ...
## $ VEN. pH_POST : num [1:26] 7.34 7.36 7.32 7.32 7.41 7.32 7.42 7.22 7.29 7.35 ...
## $ VEN. pCO2_PRE : num [1:26] 39 46 45 49 33 41 47 44 36 49 ...
## $ VEN. pCO2_POST : num [1:26] 56 49 46 40 36 52 44 41 38 45 ...
## $ VEN_pO2_PRE : num [1:26] 38 33 32 36 55 39 31 42 62 39 ...
## $ VEN. pO2 POST : num [1:26] 45 41 46 39 45 43 61 32 51 45 ...
## $ VEN. HCO3 PRE : num [1:26] 24.2 24.7 28.5 27.7 26 22.6 26.6 16.8 15.8 25.2 ...
## $ VEN. HCO3 POST : num [1:26] 30.2 25.3 23.7 19 22.8 26.8 28.5 16 18.3 25.9 ...
## $ VEN. BE PRE : num [1:26] -0.6 0.6 3.6 -10 -6.2 -2.8 0.9 -3.6 -10.6 -1.3 ...
## $ VEN. BE POST : num [1:26] 3.3 1.4 -2.4 -8.7 -1.4 0.6 3.7 -5.9 -7.7 -0.2 ...
## $ VEN. SO2 PRE : num [1:26] 70 61 62 66 65 70 60 72 87 68 ...
## $ VEN. SO2 POST : num [1:26] 78 74 78 70 81 74 70 69 81 75 ...
## $ ART. pH PRE : num [1:26] 7.35 7.42 7.48 7.36 7.41 7.41 7.47 7.35 7.29 7.38 ...
## $ ART. pH POST : num [1:26] 7.33 7.4 7.34 7.47 7.45 7.4 7.49 7.42 7.33 7.39 ...
## $ ART. pCO2 PRE : num [1:26] 31 32 36 42 28 41 36 38 39 40 ...
## $ ART. pCO2 POST : num [1:26] 32 38 42 29 30 42 32 40 32 41 ...
## $ ART. pO2 PRE : num [1:26] 124 101 111 79 141 88 169 92 72 69 ...
## $ ART. pO2 POST : num [1:26] 87 82 103 114 108 154 112 74 86 80 ...
## $ ART. HCO3 PRE : num [1:26] 17.1 22.4 26.8 21.1 17.7 26 26.2 21 18.8 23.8 ...
## $ ART. HCO3 POST : num [1:26] 16.9 24.2 22.7 23.7 20.9 26 24.4 25.9 16.9 24.8 ...
## $ ART. BE PRE : num [1:26] -7.5 -3.7 3 -1.8 -6.4 1.2 2.3 -4.2 -7.2 -1.3 ...
## $ ART. BE POST : num [1:26] -8.1 -0.5 -3.1 -1.7 -2.9 1.1 1.2 1.3 -8.3 -0.2 ...
## $ ART. SO2 PRE : num [1:26] 99 98 99 96 99 97 100 97 92 93 ...
## $ ART. SO2 POST : num [1:26] 96 96 98 98 98 99 99 95 96 95 ...
## $ Hb PRE : num [1:26] 8.5 9.8 8.1 7.8 7.5 8 6.7 7.2 7.3 10.6 ...
## $ Hb POST : num [1:26] 9 10.6 8.5 8.2 8.8 8.2 7.8 7 7.2 11.2 ...
## $ HTC PRE : num [1:26] 27.3 27.4 23.8 23.9 22.5 23.3 20.4 22 20.7 34.4 ...
## $ HTC POST : num [1:26] 28.5 29.8 25.1 25.8 26 23.9 23.5 22.1 21.5 33.5 ...
## $ LEUCOS PRE : num [1:26] 7.65 15.22 8.16 9.61 11.92 ...
## $ LEUCOS POST : num [1:26] 7.92 19.28 8.95 15.98 9.49 ...
## $ PROCA PRE : num [1:26] 2.98 10.47 3.49 0.23 0.23 ...
## $ PROCA POST : num [1:26] 19.14 12.47 3.49 0.23 0.05 ...
## $ LACTATO PRE : num [1:26] 0.9 6.8 1.1 1.9 0.6 1.3 2.9 5.5 1.3 1 ...
## $ LACTATO POST : num [1:26] 0.5 4.2 1.2 1.4 0.6 1.6 1.9 4.8 0.7 0.7 ...continuasdromar$Vol_Sistólico_I_POST = as.numeric(continuasdromar$Vol_Sistólico_I_POST)## Warning: NAs introducidos por coercióncontinuasdromar$`ART. SO2 POST` = as.numeric(continuasdromar$`ART. SO2 POST`)
continuasdromar$SAO2_PRE = as.numeric(continuasdromar$SAO2_PRE)
continuasdromar$SAO2_TRANS = as.numeric(continuasdromar$SAO2_TRANS)
continuasdromar$SAO2_POST = as.numeric(continuasdromar$SAO2_POST)
continuasdromar$Vol_Sistólico_I_POST = as.numeric (continuasdromar$Vol_Sistólico_I_POST)
continuasdromar %>% select(paquete, TAM_PRE,TAM_TRANS,TAM_POST,FC_PRE,FC_TRANS,FC_POST,FR_PRE,FR_TRANS,
FR_POST,SAO2_PRE,SAO2_TRANS,SAO2_POST,TEMP_PRE,TEMP_TRANS,TEMP_POST,
GC_FICK_PRE,`GC_FICK POST`, `GC_Indexado PRE`, GC_Idexado_POST,
Vol._Sistólico_PRE, `Vol._Sistólico_PRE`,`Vol. Sistólico_POST`,
`Vol. Sistólico I._PRE`, Vol_Sistólico_I_POST, VEN_pH_PRE,
`VEN. pH_POST`, `VEN. pCO2_PRE`, `VEN. pCO2_POST`,VEN_pO2_PRE,
`VEN. pO2 POST`, `VEN. HCO3 PRE`, `VEN. HCO3 POST`, `VEN. BE PRE`,
`VEN. BE POST`,`VEN. SO2 PRE`, `VEN. SO2 POST`, `ART. pH PRE`,`ART. pH POST`,
`ART. pCO2 PRE`, `ART. pCO2 POST`, `ART. pO2 PRE`, `ART. pO2 POST`,
`ART. HCO3 PRE`, `ART. HCO3 POST`, `ART. BE PRE`, `ART. BE POST`,
`ART. SO2 PRE`, `ART. SO2 POST`,`Hb PRE`,`Hb POST`, `HTC PRE` ,`HTC POST`,
`LEUCOS PRE`, `LEUCOS POST`,`PROCA PRE`,
`PROCA POST` ,`LACTATO PRE`,`LACTATO POST`) %>%
tbl_summary(by=paquete, type = list(where(is.numeric) ~ "continuous")) %>%
add_p() %>% add_overall()## Warning for variable 'TAM_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TAM_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TAM_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FC_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FC_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FC_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FR_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FR_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'FR_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'SAO2_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'SAO2_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'SAO2_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TEMP_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TEMP_TRANS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TEMP_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'GC_FICK POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'GC_Indexado PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN_pH_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pH_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pCO2_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pCO2_POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN_pO2_PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. pO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. HCO3 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. HCO3 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. BE PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. BE POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. SO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'VEN. SO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pH PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pH POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pCO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pCO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. pO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. HCO3 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. HCO3 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. BE PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. BE POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. SO2 PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ART. SO2 POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'Hb PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'Hb POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'HTC PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'HTC POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LEUCOS PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LEUCOS POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'PROCA PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'PROCA POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LACTATO PRE':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LACTATO POST':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead| Characteristic | Overall, N = 261 | gestandard, N = 131 | gfresco, N = 131 | p-value2 |
|---|---|---|---|---|
| TAM_PRE | 88 (76, 94) | 90 (75, 107) | 87 (79, 93) | 0.8 |
| TAM_TRANS | 86 (79, 93) | 90 (79, 100) | 83 (80, 90) | 0.2 |
| TAM_POST | 85 (80, 94) | 85 (76, 94) | 85 (81, 90) | 0.9 |
| FC_PRE | 84 (76, 100) | 89 (75, 100) | 79 (78, 100) | 0.9 |
| FC_TRANS | 85 (75, 93) | 85 (75, 94) | 85 (73, 92) | 0.7 |
| FC_POST | 79 (68, 95) | 82 (61, 92) | 79 (70, 96) | >0.9 |
| FR_PRE | 16.0 (15.0, 18.0) | 15.0 (12.0, 16.0) | 17.0 (16.0, 20.0) | 0.011 |
| FR_TRANS | 16.00 (14.25, 18.00) | 15.00 (13.00, 16.00) | 17.00 (16.00, 18.00) | 0.018 |
| FR_POST | 17.00 (14.25, 18.00) | 15.00 (14.00, 17.00) | 18.00 (17.00, 20.00) | 0.015 |
| SAO2_PRE | 97.00 (96.00, 98.00) | 97.00 (96.00, 98.00) | 96.00 (96.00, 97.00) | 0.5 |
| SAO2_TRANS | 97.00 (96.00, 98.00) | 97.00 (96.00, 98.00) | 98.00 (96.00, 98.00) | 0.8 |
| SAO2_POST | 97.00 (97.00, 98.00) | 97.00 (97.00, 98.00) | 97.00 (97.00, 98.00) | >0.9 |
| TEMP_PRE | 37.00 (36.40, 37.50) | 36.50 (36.10, 37.00) | 37.50 (37.00, 37.60) | 0.016 |
| TEMP_TRANS | 37.00 (36.50, 37.50) | 36.50 (36.30, 37.00) | 37.50 (37.00, 37.70) | 0.010 |
| TEMP_POST | 36.90 (36.40, 37.50) | 36.50 (36.20, 37.00) | 37.50 (36.80, 37.70) | 0.018 |
| GC_FICK_PRE | 9 (7, 13) | 10 (5, 14) | 8 (7, 9) | 0.4 |
| GC_FICK POST | 9.7 (7.7, 12.3) | 8.8 (5.8, 13.3) | 10.3 (8.4, 12.1) | 0.5 |
| GC_Indexado PRE | 4.2 (3.4, 6.4) | 5.9 (3.0, 8.0) | 4.2 (3.7, 4.5) | 0.3 |
| GC_Idexado_POST | 5.13 (4.12, 6.07) | 5.31 (3.49, 6.37) | 4.95 (4.31, 5.69) | >0.9 |
| Vol._Sistólico_PRE | 86 (69, 162) | 86 (69, 184) | 87 (80, 116) | 0.8 |
| Vol. Sistólico_POST | 120 (92, 154) | 101 (81, 153) | 125 (101, 154) | 0.5 |
| Vol. Sistólico I._PRE | 45 (35, 78) | 59 (34, 97) | 43 (37, 57) | 0.4 |
| Vol_Sistólico_I_POST | 66 (52, 80) | 66 (40, 80) | 65 (52, 77) | >0.9 |
| Unknown | 1 | 0 | 1 | |
| VEN_pH_PRE | 7.34 (7.30, 7.40) | 7.32 (7.28, 7.40) | 7.36 (7.33, 7.40) | 0.2 |
| VEN. pH_POST | 7.36 (7.32, 7.42) | 7.41 (7.32, 7.43) | 7.35 (7.32, 7.41) | 0.3 |
| VEN. pCO2_PRE | 41.0 (33.8, 44.8) | 41.0 (33.0, 42.0) | 42.0 (39.0, 46.0) | 0.15 |
| VEN. pCO2_POST | 39 (36, 46) | 38 (36, 38) | 44 (40, 49) | 0.030 |
| VEN_pO2_PRE | 42 (35, 50) | 47 (43, 50) | 38 (35, 42) | 0.2 |
| VEN. pO2 POST | 45.0 (41.2, 50.0) | 45.0 (42.0, 55.0) | 45.0 (41.0, 45.0) | 0.3 |
| VEN. HCO3 PRE | 24.6 (21.4, 26.0) | 23.0 (16.8, 24.8) | 26.0 (24.2, 27.2) | 0.048 |
| VEN. HCO3 POST | 25.6 (22.7, 26.7) | 26.0 (22.6, 26.0) | 25.3 (22.8, 27.5) | 0.6 |
| VEN. BE PRE | -2.0 (-6.2, 0.6) | -2.1 (-10.3, -0.2) | -1.3 (-6.2, 0.9) | 0.4 |
| VEN. BE POST | -0.4 (-5.7, 1.0) | -0.4 (-8.3, 1.0) | -0.2 (-2.4, 1.4) | 0.3 |
| VEN. SO2 PRE | 70 (65, 75) | 70 (70, 83) | 68 (65, 70) | 0.061 |
| VEN. SO2 POST | 78.0 (73.2, 80.0) | 80.0 (78.0, 80.0) | 75.0 (73.0, 78.0) | 0.2 |
| ART. pH PRE | 7.41 (7.35, 7.44) | 7.41 (7.32, 7.44) | 7.41 (7.35, 7.41) | 0.9 |
| ART. pH POST | 7.42 (7.35, 7.45) | 7.42 (7.32, 7.45) | 7.42 (7.39, 7.45) | 0.7 |
| ART. pCO2 PRE | 35.0 (31.2, 38.8) | 33.0 (30.0, 36.0) | 36.0 (32.0, 40.0) | 0.2 |
| ART. pCO2 POST | 33.5 (31.2, 38.0) | 34.0 (33.0, 35.0) | 32.0 (30.0, 41.0) | 0.7 |
| ART. pO2 PRE | 92 (80, 116) | 93 (73, 112) | 92 (88, 124) | 0.4 |
| ART. pO2 POST | 108 (92, 115) | 114 (95, 116) | 103 (86, 112) | 0.2 |
| ART. HCO3 PRE | 22.4 (19.0, 24.2) | 22.3 (19.7, 23.8) | 22.4 (18.8, 26.0) | 0.6 |
| ART. HCO3 POST | 23.9 (20.9, 24.7) | 22.1 (19.6, 24.0) | 24.2 (20.9, 24.9) | 0.2 |
| ART. BE PRE | -2.0 (-6.4, 0.5) | -2.2 (-6.5, -0.4) | -1.8 (-6.4, 1.2) | 0.7 |
| ART. BE POST | -0.5 (-3.1, -0.1) | -0.4 (-6.0, -0.3) | -0.5 (-2.9, 1.1) | 0.5 |
| ART. SO2 PRE | 97.00 (97.00, 99.00) | 97.00 (97.00, 98.00) | 97.00 (97.00, 99.00) | 0.5 |
| ART. SO2 POST | 98.00 (97.25, 99.00) | 98.00 (98.00, 99.00) | 98.00 (96.00, 98.00) | 0.12 |
| Hb PRE | 8.00 (7.53, 8.40) | 8.00 (7.90, 8.10) | 8.00 (7.30, 8.50) | 0.9 |
| Hb POST | 8.55 (8.20, 9.30) | 8.60 (8.40, 9.40) | 8.50 (7.80, 9.00) | 0.6 |
| HTC PRE | 24.0 (22.6, 26.7) | 24.7 (23.7, 24.7) | 23.8 (22.0, 27.3) | 0.4 |
| HTC POST | 25.9 (24.2, 28.5) | 26.5 (25.4, 28.5) | 25.8 (23.5, 28.5) | 0.6 |
| LEUCOS PRE | 12.9 (9.9, 14.9) | 12.8 (10.2, 14.1) | 14.0 (9.6, 14.9) | 0.7 |
| LEUCOS POST | 12.8 (9.5, 13.9) | 12.7 (10.8, 13.4) | 13.4 (9.5, 14.1) | >0.9 |
| PROCA PRE | 0.35 (0.15, 2.69) | 0.22 (0.07, 0.43) | 0.83 (0.23, 5.58) | 0.031 |
| PROCA POST | 0 (0, 2) | 0 (0, 0) | 1 (0, 5) | 0.022 |
| LACTATO PRE | 1.45 (1.00, 2.75) | 1.50 (0.80, 2.10) | 1.40 (1.10, 2.90) | 0.4 |
| LACTATO POST | 1.20 (0.70, 1.90) | 1.00 (0.70, 1.90) | 1.20 (0.70, 1.90) | >0.9 |
| 1 Median (IQR) | ||||
| 2 Wilcoxon rank sum test; Wilcoxon rank sum exact test | ||||
Figuras
Se diseñaron 4 figuras con base al análisis multivariado de las variables continuas que resultaron estadísticamente significativas
Figura 1
Variable: Frecuencia Respitaroria
#PAQUETES PARA ESTE ANALISIS
library(tidyr)
library(dplyr)
library(readr)
library(tidyverse)
library(ggpubr)
library(rstatix)##
## Attaching package: 'rstatix'## The following object is masked from 'package:stats':
##
## filter#FR
FR <- continuasdromar %>% select(paquete, FR_PRE, FR_TRANS, FR_POST)
FR ## # A tibble: 26 × 4
## paquete FR_PRE FR_TRANS FR_POST
## <chr> <dbl> <dbl> <dbl>
## 1 gfresco 20 18 20
## 2 gfresco 18 18 18
## 3 gfresco 15 16 14
## 4 gfresco 20 20 20
## 5 gfresco 15 14 17
## 6 gfresco 17 16 20
## 7 gfresco 15 16 14
## 8 gfresco 18 16 19
## 9 gfresco 23 19 21
## 10 gfresco 16 16 16
## # … with 16 more rowsFRgat<-FR %>%
pivot_longer(
cols = starts_with("F"),
names_to = "variable",
values_to = "valor") %>%
convert_as_factor (variable)
FRgat$variable <- ordered(FRgat$variable, levels = c("FR_PRE", "FR_TRANS", "FR_POST"))
FRplotfac <- ggboxplot(FRgat, x = "variable", y = "valor",
facet.by = "paquete",color="variable", palette = "lancet")
FRplotfac + stat_compare_means(method = "aov", label.y = 8, label.x= 2.5)+
stat_compare_means(
comparisons = list(c("FR_PRE", "FR_TRANS"), c("FR_TRANS", "FR_POST"), c("FR_PRE", "FR_POST")),
label = "p.signif", paired = T)## Warning in wilcox.test.default(c(16, 12, 14, 16, 21, 15, 17, 18, 14, 8, : cannot
## compute exact p-value with ties## Warning in wilcox.test.default(c(16, 12, 14, 16, 21, 15, 17, 18, 14, 8, : cannot
## compute exact p-value with zeroes## Warning in wilcox.test.default(c(16, 12, 14, 16, 21, 15, 17, 18, 14, 8, : cannot
## compute exact p-value with ties## Warning in wilcox.test.default(c(16, 12, 14, 16, 21, 15, 17, 18, 14, 8, : cannot
## compute exact p-value with zeroes## Warning in wilcox.test.default(c(16, 14, 15, 16, 13, 14, 18, 19, 18, 11, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(16, 14, 15, 16, 13, 14, 18, 19, 18, 11, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(20, 18, 15, 20, 15, 17, 15, 18, 23, 16, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(20, 18, 15, 20, 15, 17, 15, 18, 23, 16, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(20, 18, 15, 20, 15, 17, 15, 18, 23, 16, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(20, 18, 15, 20, 15, 17, 15, 18, 23, 16, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(18, 18, 16, 20, 14, 16, 16, 16, 19, 16, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(18, 18, 16, 20, 14, 16, 16, 16, 19, 16, :
## cannot compute exact p-value with zeroes
Figura 2.
Variable: Temperatura corporal
#TEMP
TC <- continuasdromar %>% select(paquete, TEMP_PRE, TEMP_TRANS, TEMP_POST)
TC ## # A tibble: 26 × 4
## paquete TEMP_PRE TEMP_TRANS TEMP_POST
## <chr> <dbl> <dbl> <dbl>
## 1 gfresco 39 39.3 39
## 2 gfresco 36.3 36.4 36.4
## 3 gfresco 37.2 37 37
## 4 gfresco 37.7 37.8 37.8
## 5 gfresco 36.8 37 36.8
## 6 gfresco 37.5 37.7 37.7
## 7 gfresco 37 37.2 37.3
## 8 gfresco 36.1 36 36
## 9 gfresco 38.3 38.2 38.2
## 10 gfresco 37.6 37.6 37.5
## # … with 16 more rowsTCgat<-TC %>%
pivot_longer(
cols = starts_with("TEMP"),
names_to = "variable",
values_to = "valor") %>%
convert_as_factor (variable)
TCgat## # A tibble: 78 × 3
## paquete variable valor
## <chr> <fct> <dbl>
## 1 gfresco TEMP_PRE 39
## 2 gfresco TEMP_TRANS 39.3
## 3 gfresco TEMP_POST 39
## 4 gfresco TEMP_PRE 36.3
## 5 gfresco TEMP_TRANS 36.4
## 6 gfresco TEMP_POST 36.4
## 7 gfresco TEMP_PRE 37.2
## 8 gfresco TEMP_TRANS 37
## 9 gfresco TEMP_POST 37
## 10 gfresco TEMP_PRE 37.7
## # … with 68 more rowsTCgat$variable <- ordered(TCgat$variable, levels = c("TEMP_PRE", "TEMP_TRANS", "TEMP_POST"))
TCplotfac <- ggboxplot(TCgat, x = "variable", y = "valor",
facet.by = "paquete",color="variable", palette = "lancet")
TCplotfac + stat_compare_means(method = "aov", label.y = 35, label.x= 3)+
stat_compare_means(
comparisons = list(c("TEMP_PRE", "TEMP_TRANS"), c("TEMP_TRANS", "TEMP_POST"), c("TEMP_PRE", "TEMP_POST")),
label = "p.signif", paired = T)## Warning in wilcox.test.default(c(36, 36.5, 37, 36.1, 36.5, 37.3, 37.7, 36.4, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(36, 36.5, 37, 36.1, 36.5, 37.3, 37.7, 36.4, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(36, 36.5, 37, 36.1, 36.5, 37.3, 37.7, 36.4, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(36, 36.5, 37, 36.1, 36.5, 37.3, 37.7, 36.4, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(36.2, 36.5, 37, 36.1, 36.6, 37.5, 37.2, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(36.2, 36.5, 37, 36.1, 36.6, 37.5, 37.2, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(39, 36.3, 37.2, 37.7, 36.8, 37.5, 37, 36.1, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(39, 36.3, 37.2, 37.7, 36.8, 37.5, 37, 36.1, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(39, 36.3, 37.2, 37.7, 36.8, 37.5, 37, 36.1, :
## cannot compute exact p-value with ties## Warning in wilcox.test.default(c(39, 36.3, 37.2, 37.7, 36.8, 37.5, 37, 36.1, :
## cannot compute exact p-value with zeroes## Warning in wilcox.test.default(c(39.3, 36.4, 37, 37.8, 37, 37.7, 37.2, 36, :
## cannot compute exact p-value with zeroes
Figura 3
variable: Ven PCO2
#VEN. pCO2
venpco2 <- continuasdromar %>% select(paquete, `VEN. pCO2_PRE`, `VEN. pCO2_POST`)
venpco2 ## # A tibble: 26 × 3
## paquete `VEN. pCO2_PRE` `VEN. pCO2_POST`
## <chr> <dbl> <dbl>
## 1 gfresco 39 56
## 2 gfresco 46 49
## 3 gfresco 45 46
## 4 gfresco 49 40
## 5 gfresco 33 36
## 6 gfresco 41 52
## 7 gfresco 47 44
## 8 gfresco 44 41
## 9 gfresco 36 38
## 10 gfresco 49 45
## # … with 16 more rowscolnames(venpco2)## [1] "paquete" "VEN. pCO2_PRE" "VEN. pCO2_POST"pco2plot<-ggpaired(venpco2 , cond1 = "VEN. pCO2_PRE", cond2 = "VEN. pCO2_POST",
palette = "lancet",color= "paquete",line.color = "gray", point.size = 2, line.size = 0.1) +
facet_grid(~paquete) + stat_compare_means(paired = TRUE)## Warning: `gather_()` was deprecated in tidyr 1.2.0.
## Please use `gather()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.pco2plot
Figura 4
Variable : Ven HCO3
#VEN HCO3
venhco3 <- continuasdromar %>% select(paquete, `ART. HCO3 PRE`, `ART. HCO3 POST`)
venhco3 ## # A tibble: 26 × 3
## paquete `ART. HCO3 PRE` `ART. HCO3 POST`
## <chr> <dbl> <dbl>
## 1 gfresco 17.1 16.9
## 2 gfresco 22.4 24.2
## 3 gfresco 26.8 22.7
## 4 gfresco 21.1 23.7
## 5 gfresco 17.7 20.9
## 6 gfresco 26 26
## 7 gfresco 26.2 24.4
## 8 gfresco 21 25.9
## 9 gfresco 18.8 16.9
## 10 gfresco 23.8 24.8
## # … with 16 more rowscolnames(venhco3)## [1] "paquete" "ART. HCO3 PRE" "ART. HCO3 POST"hco3plot<-ggpaired(venhco3 , cond1 = "ART. HCO3 PRE", cond2 = "ART. HCO3 POST",
palette = "lancet",color= "paquete",line.color = "gray", point.size = 2,
line.size = 0.1, ylim(0, 35)) +
facet_grid(~paquete) + stat_compare_means(paired = TRUE, label.y = 35)
hco3plot + scale_y_continuous(name="value", limits=c(5, 35))## Warning: Removed 1 rows containing non-finite values (stat_boxplot).## Warning: Removed 1 rows containing non-finite values (stat_compare_means).## Warning: Computation failed in `stat_compare_means()`:
## 'x' and 'y' must have the same length## Warning: Removed 1 row(s) containing missing values (geom_path).## Warning: Removed 1 rows containing missing values (geom_point).