Reporte de análisis estadístico Dr. Ortiz
MDatos
2022-08-28
Análisis exploratorio de datos (AED)
Para este análisis primero, recodificamos las variables que provienen
de la base de datos.
Además se crea la columna anemia que se clasifica con base al siguiente
criterio:
Hb < 13 g/dl en hombres y < 12 g/dl en mujeres mayores de 18 años
library(readxl)
dbdrortiz <- read_excel("C:/Users/fidel/OneDrive - CINVESTAV/PROYECTO MDatos/TRABAJOS/Dr. Carlos eduardo Ortiz castañeda lunes 22/dbdrortiz.xlsx")
#View(dbdrortiz)
#Se trabajó con los siguientes paquetes
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library(gt)
#El objetivo de este trabajo tiene el de dicotomizar LA VARIABLE CON BASE A LA HB
#creamos la variable anemia
#dbdrortiz <- dbdrortiz %>% mutate(anemia = case_when(
# SEXO == 0 & HB <12 ~ "Positivo",
#SEXO == 1 & HB <13 ~ "Positivo",
#SEXO == 0|1 & HB > 12 | 13 ~ "Negativo"))
#recodificiación de variables
dbdrort<-dbdrortiz <- dbdrortiz %>% mutate(COMORBIDOS=recode(COMORBIDOS, `0`= "NINGUNO",
`1` ="HAS",
`2` ="DM",
`3` = "DISLIPIDEMIA",
`4` = "HIPOTIROIDISMO",
`5` = "OSTEOPOROSIS",
`6` = "INSUFICIENCIA CARDIACA",
`7` = "HIPERURICEMIA",
`9` = "VIH",
`10` = "ESTENOSIS DE VEJIGA",
`11` = "HIPERPARATIROIDISMO",
`1,11` = "HAS + HIPERPARATIROIDISMO",
`1,2` = "HAS + DM",
`1,2,9` = "HAS + DM + VIH",
`1,3` = "HAS + DISLIPIDEMIA",
`1,4` = "HAS + HIPOTIROIDISMO",
`1,5` = "HAS + OSTEOPOROSIS",
`1,6` = "HAS + INSUF CARDIACA",
`1,7` = "HAS + HIPERURICEMIA",),
ERC=recode(ERC, `1` = "ESTADIO 1",
`2` = "ESTADIO 2",
`3A` = "ESTADIO 3A",
`3B` = "ESTADIO 3B",
`4` = "ESTADIO 4",
`5` = "ESTADIO 5"),
INMUNOSUPRESORES=recode(INMUNOSUPRESORES, `1` = "PREDNISONA",
`2` = "INHIBIDOR DE CALCINEURINA",
`3` = "MICOFENOLATO",
`4` = "MTOR",
`5` = "AZATIOPRINA",
`1,2` = "PREDNISONA + INHIB CALCINEURINA",
`1,2,3` = "PREDNISONA + INHIB CALCINEURINA + MICOFELONATO",
`1,2,4` = "PREDNISONA + INHIB CALCINEURINA + MTOR",
`1,2,5` = "PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA",
`1,3` = "PREDNISONA + MICOFELONATO",
`1,3,4` = "PREDNISONA + MICOFELONATO + MTOR",
`1,4,5` = "PREDNISONA + MTOR + AZATIOPRINA",
`2,3` = "INHIB CALCINEURINA + MICOFENOLATO",
`3,4` = "MICOFENOLATO + MTOR"),
AEE=recode(AEE, `1` = "ERITROPOYETINA",
`2` = "DARBEPOETINA",
`3` = "MIRCERA"),
TRANSFUSIONES=recode(TRANSFUSIONES, `1` = "SI"),
TIPO=recode(TIPO,`1` = "TRDVR",
`2` = "TRDVNR",
`3` = "TRDC"),
`FUNCION RETARDADA`=recode(`FUNCION RETARDADA`, `1` = "SI"),
SEXO=recode(SEXO, `0`= "FEMENINO",
`1` = "MASCULINO"),
RESISTENCIA=recode(RESISTENCIA, `0`= "No resistencia", `1`= "Resistencia"))
dbdrort %>% gt()| EXPEDIENTE | EDAD | PESO | SEXO | COMORBIDOS | ERC | CR | U | ALBUMINA | LEUCOS | NEU | LINF | HB | INFECCION | INMUNOSUPRESORES | AEE | DOSIS | IECA/ARA | DOSIS KDIGO | RESISTENCIA | TRANSFUSIONES | TIEMPO | TIPO | EDAD DON | # | FRIA | CALIENTE | FUNCION RETARDADA | Episodios de rechazo | Etiologia ERC |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TOFA700824/1 | 51 | 82.0 | MASCULINO | HAS + DM | ESTADIO 3B | 2.07 | 63.30 | 3.90 | 9.48 | 6.22 | 1.90 | 17.6 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/30DIAS | 1 | 0.18 | No resistencia | SE DESCONOCE | 7 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HAS,DM |
| GOPE571117/8 | 48 | 57.0 | FEMENINO | HAS + HIPOTIROIDISMO | ESTADIO 3B | 1.84 | 67.40 | 4.30 | 6.25 | 4.28 | 1.25 | 12.2 | NA | PREDNISONA + INHIB CALCINEURINA | DARBEPOETINA | 30/30DIAS | 1 | 0.26 | No resistencia | SE DESCONOCE | 4 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| RAZA780518/2 | 44 | 62.0 | FEMENINO | HIPOTIROIDISMO | ESTADIO 2 | 0.88 | 27.30 | 4.30 | 8.90 | 5.90 | 1.78 | 12.7 | NA | PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA | DARBEPOETINA | 30/30DIAS | 0 | 0.24 | No resistencia | SE DESCONOCE | 17 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| SASM800211/9 | 42 | 57.0 | FEMENINO | NINGUNO | ESTADIO 4 | 2.70 | 94.50 | 4.30 | 10.06 | 6.10 | 3.10 | 12.1 | NA | PREDNISONA + INHIB CALCINEURINA + MTOR | DARBEPOETINA | 40/30 DIAS | 1 | 0.35 | No resistencia | SE DESCONOCE | 16 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| GOMJ520219/8 | 37 | 70.0 | FEMENINO | NINGUNO | ESTADIO 3B | 1.80 | 41.30 | 4.50 | 4.40 | 2.80 | 1.15 | 12.7 | NA | MICOFENOLATO + MTOR | DARBEPOETINA | 30/15 DIAS | 0 | 0.42 | No resistencia | SE DESCONOCE | 12 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| PARS770811/2 | 44 | 80.0 | FEMENINO | NINGUNO | ESTADIO 3B | 1.81 | 77.60 | 3.70 | 5.10 | 2.60 | 1.18 | 9.9 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 40/7DIAS | 1 | 1.00 | Resistencia | SI | 9 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | GLOMERULONEFRITIS POSTESTREPTOCOCICA |
| GUHM680418/2 | 53 | 66.0 | FEMENINO | HAS + OSTEOPOROSIS | ESTADIO 4 | 2.80 | 71.60 | 4.50 | 7.57 | 4.33 | 2.40 | 10.6 | NA | MICOFENOLATO + MTOR | DARBEPOETINA | 40/7DIAS | 1 | 1.20 | Resistencia | SI | 14 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | PREECLAMPSIA |
| PIRR530714/9 | 68 | 51.0 | FEMENINO | HAS | ESTADIO 2 | 0.86 | 34.40 | 4.00 | 3.00 | 2.01 | 0.31 | 8.8 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/7DIAS | 1 | 1.50 | Resistencia | SI | 1 | TRDC | SE DESCONOCE | 1 | 6.9444444444444434E-2 | 30 | SI | 0 | GEFYS |
| FOTM600928/9 | 61 | 53.0 | FEMENINO | HAS + DM | ESTADIO 3B | 1.88 | 44.00 | 3.80 | 4.80 | 2.00 | 1.73 | 11.4 | NA | INHIB CALCINEURINA + MICOFENOLATO | DARBEPOETINA | 60/7DIAS | 1 | 2.20 | No resistencia | SI | 9 | TRDVNR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HAS,DM |
| AEPP 540524/7 | 26 | 78.0 | MASCULINO | NINGUNO | ESTADIO 3B | 3.22 | 163.90 | 4.50 | 6.30 | 4.90 | 0.69 | 12.4 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 30/7DIAS | 0 | 0.76 | No resistencia | SE DESCONOCE | 1 | TRDVR | SE DESCONOCE | 2 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | GEFYS |
| MACP810228/ | 42 | 65.0 | MASCULINO | NINGUNO | ESTADIO 3B | 2.50 | 87.00 | 3.80 | 4.90 | 3.30 | 0.86 | 9.6 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 40/7DIAS | 1 | 1.20 | Resistencia | SI | 3 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| SEHG630729/2 | 58 | 48.5 | FEMENINO | HAS | ESTADIO 3A | 1.20 | 71.20 | 2.80 | 6.90 | 6.07 | 0.32 | 7.0 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/7DIAS | 0 | 1.60 | Resistencia | SI | 5 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HAS |
| SAAA590522/7 | 29 | 66.0 | MASCULINO | NINGUNO | ESTADIO 3A | 1.70 | 40.40 | 4.50 | 8.60 | 6.90 | 1.20 | 12.3 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 30/30DIAS | 1 | 0.90 | No resistencia | SE DESCONOCE | 11 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| SEGN701015/3 | 52 | 68.0 | FEMENINO | HAS | ESTADIO 5 | 3.70 | 77.60 | 3.30 | 9.40 | 6.80 | 1.80 | 11.5 | NA | PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA | DARBEPOETINA | 30/7DIAS | 1 | 0.88 | No resistencia | SE DESCONOCE | 21 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | HAS |
| GASF650121/7 | 33 | 50.0 | FEMENINO | HAS + INSUF CARDIACA | ESTADIO 5 | 11.50 | 176.00 | 3.20 | 6.80 | 4.90 | 1.60 | 7.6 | NA | PREDNISONA | MIRCERA | 75/7DIAS | 1 | 6.00 | Resistencia | SI | 10 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SI | 0 | VEJIGA NEUROGENICA |
| GAHR790316/2 | 43 | 53.0 | FEMENINO | NINGUNO | ESTADIO 2 | 1.05 | 17.30 | 4.60 | 4.70 | 2.50 | 1.50 | 11.2 | NA | MICOFENOLATO + MTOR | DARBEPOETINA | 30/30DIAS | 0 | 1.10 | No resistencia | SE DESCONOCE | 12 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| GUMJ480709/1 | 73 | 78.0 | MASCULINO | NINGUNO | ESTADIO 3B | 1.80 | 62.00 | 4.20 | 4.60 | 2.60 | 1.20 | 12.5 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | ERITROPOYETINA | 4000/30DIAS | 0 | 51.00 | No resistencia | SE DESCONOCE | 3 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | AMILOIDOSIS |
| FABI770502/3 | 37 | 64.0 | FEMENINO | NINGUNO | ESTADIO 3A | 1.20 | 33.00 | 4.40 | 5.80 | 4.10 | 0.99 | 11.0 | NA | INHIB CALCINEURINA + MICOFENOLATO | DARBEPOETINA | 30/30DIAS | 0 | 0.23 | No resistencia | SE DESCONOCE | 8 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | DESCONOCE |
| TANG730922/2 | 48 | 62.0 | FEMENINO | HAS + HIPERURICEMIA | ESTADIO 4 | 3.00 | 66.00 | 3.60 | 3.40 | 1.70 | 0.95 | 7.8 | NA | PREDNISONA + INHIB CALCINEURINA | DARBEPOETINA | 40/7DIAS | 1 | 1.20 | Resistencia | SI | 24 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | HIPOPLASIA RENAL |
| TAMF521218/8 | 29 | 69.0 | FEMENINO | NINGUNO | ESTADIO 4 | 3.50 | 100.00 | 3.80 | 8.70 | 4.80 | 3.50 | 9.3 | NA | PREDNISONA + MTOR + AZATIOPRINA | ERITROPOYETINA | 6000/7DIAS | 1 | 86.00 | No resistencia | SI | 5 | TRDVNR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | GLOMERULONEFRITIS NO ESPECIFICADA |
| LEPI670921/7 | 23 | 60.0 | MASCULINO | NINGUNO | ESTADIO 3B | 2.60 | 96.00 | 4.27 | 8.10 | 6.10 | 1.90 | 12.6 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 40/7DIAS | 0 | 1.30 | No resistencia | SE DESCONOCE | 16 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| MEGG940105/1 | 22 | 72.0 | MASCULINO | NINGUNO | ESTADIO 3B | 2.20 | 62.00 | 4.20 | 6.30 | 3.40 | 1.90 | 12.3 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 30/30DIAS | 1 | 0.20 | No resistencia | SE DESCONOCE | 10 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| DANR760117/2 | 46 | 56.0 | FEMENINO | HIPERURICEMIA | ESTADIO 3B | 1.60 | 77.00 | 4.10 | 4.30 | 3.40 | 0.38 | 9.1 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 40/7DIAS | 0 | 1.40 | Resistencia | SI | 12 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | ERPAD |
| MESF680104/ | 51 | 78.0 | MASCULINO | NINGUNO | ESTADIO 4 | 4.10 | 94.00 | 3.70 | 5.50 | 5.10 | 1.06 | 11.8 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 40/15DIAS | 0 | 0.50 | No resistencia | SE DESCONOCE | 7 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| MATA630110/7 | 28 | 69.5 | MASCULINO | NINGUNO | ESTADIO 3B | 2.40 | 45.80 | 3.60 | 6.30 | 3.20 | 2.50 | 12.5 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/15DIAS | 0 | 0.57 | No resistencia | SE DESCONOCE | 9 | TRDVR | SE DESCONOCE | 2 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| MOQL641209/8 | 29 | 56.0 | FEMENINO | NINGUNO | ESTADIO 2 | 0.90 | 15.00 | 4.30 | 5.00 | 2.90 | 1.60 | 12.1 | NA | MICOFENOLATO + MTOR | DARBEPOETINA | 30/15DIAS | 0 | 0.53 | No resistencia | SE DESCONOCE | 11 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| MEOE640215/3 | 49 | 57.0 | FEMENINO | HIPERURICEMIA | ESTADIO 4 | 2.70 | 94.00 | 3.20 | 11.90 | 10.20 | 0.79 | 11.2 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/15DIAS | 0 | 0.70 | No resistencia | SE DESCONOCE | 4 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | LITIASIS REAL |
| GAHR790316/2 | 43 | 58.0 | FEMENINO | NINGUNO | ESTADIO 2 | 1.05 | 17.33 | 4.60 | 4.70 | 2.50 | 1.60 | 13.2 | NA | MICOFENOLATO + MTOR | DARBEPOETINA | 30/15DIAS | 0 | 0.51 | No resistencia | SE DESCONOCE | 12 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| HUBL620315/2 | 60 | 68.0 | FEMENINO | HAS + DM | ESTADIO 4 | 3.10 | 118.00 | 3.70 | 6.68 | 4.80 | 0.97 | 8.0 | NA | PREDNISONA + MICOFELONATO | MIRCERA | 50/15DIAS | 1 | 1.40 | Resistencia | SI | 26 | TRDVNR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| VABH670604/8 | 30 | 50.0 | FEMENINO | HAS | ESTADIO 2 | 1.20 | 57.00 | 4.40 | 5.40 | 3.80 | 1.30 | 11.3 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/30DIAS | 0 | 0.30 | No resistencia | SE DESCONOCE | 14 | TRDVR | 47 AÑOS | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HAS |
| AICF461004/8 | 31 | 53.0 | FEMENINO | HAS | ESTADIO 2 | 1.00 | 44.00 | 4.30 | 4.70 | 7.50 | 1.78 | 11.5 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/15DIAS | 1 | 0.56 | No resistencia | SE DESCONOCE | 22 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| CUMF731231/1 | 48 | 68.0 | MASCULINO | HAS + DM + VIH | ESTADIO 3B | 1.60 | 64.00 | 4.20 | 9.70 | 7.40 | 1.50 | 10.0 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 40/30DIAS | 0 | 0.29 | No resistencia | SI | 14 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| EISM710304/ | 27 | 59.0 | FEMENINO | HAS | ESTADIO 3B | 1.46 | 68.00 | 3.90 | 10.50 | 7.80 | 1.30 | 11.7 | NA | PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA | MIRCERA | 75/15DIAS | 0 | 2.50 | No resistencia | SI | 5 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | GLOMERULONEFRITIS POSTESTREPTOCOCICA |
| GAFA651229/8 | 32 | 50.0 | FEMENINO | HAS | ESTADIO 5 | 9.70 | 170.00 | 4.50 | 6.10 | 3.50 | 1.90 | 5.0 | NA | PREDNISONA + MICOFELONATO | DARBEPOETINA | 40/7DIAS | 1 | 1.60 | Resistencia | SE DESCONOCE | 14 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | GLOMERULONEFRITIS ASOCIADA A INFECCION |
| GAAJ761224/9 | 45 | 59.0 | FEMENINO | HAS | ESTADIO 2 | 0.85 | 34.00 | 4.00 | 5.10 | 2.40 | 2.10 | 13.8 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/15DIAS | 0 | 0.67 | No resistencia | SE DESCONOCE | 11 | TRDC | 17 AÑOS | 2 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | GLOMERULONEFRITIS ASOCIADA A INFECCION |
| GACC810218/1 | 41 | 82.0 | MASCULINO | HAS | ESTADIO 5 | 4.70 | 94.00 | 3.80 | 7.30 | 5.60 | 1.90 | 10.6 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 80/7DIAS | 1 | 1.90 | Resistencia | SI | 26 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | HIPOPLASIA RENAL |
| GAHR721122/2 | 49 | 78.0 | MASCULINO | HAS + DM | ESTADIO 1 | 0.87 | 37.40 | 3.70 | 7.00 | 4.50 | 1.70 | 15.1 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 30/15DIAS | 0 | 0.38 | No resistencia | SI | 18 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| FOEA551118/9 | 65 | 67.0 | FEMENINO | NINGUNO | ESTADIO 3B | 1.30 | 32.10 | 4.00 | 5.30 | 3.50 | 1.25 | 13.0 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 40/15DIAS | 0 | 0.59 | No resistencia | SE DESCONOCE | 16 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| MAOJ730171/5 | 48 | 69.0 | FEMENINO | NINGUNO | ESTADIO 2 | 1.00 | 33.10 | 4.20 | 9.20 | 7.60 | 0.87 | 12.4 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/15DIAS | 0 | 0.43 | No resistencia | SE DESCONOCE | 7 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| MAMH720913/1 | 49 | 78.0 | MASCULINO | HAS | ESTADIO 2 | 1.09 | 49.80 | 4.50 | 7.90 | 6.11 | 1.01 | 12.8 | NA | INHIB CALCINEURINA + MICOFENOLATO | DARBEPOETINA | 40/15DIAS | 1 | 0.51 | No resistencia | SE DESCONOCE | 5 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| LAEA551215/8 | 35 | 57.0 | FEMENINO | HAS | ESTADIO 3B | 2.05 | 43.00 | 3.90 | 7.80 | 6.00 | 1.48 | 14.5 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 30/15DIAS | 0 | 0.52 | No resistencia | SE DESCONOCE | 17 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| MEJL850831/7 | 18 | 52.0 | MASCULINO | ESTENOSIS DE VEJIGA | ESTADIO 4 | 3.20 | 102.00 | 4.10 | 5.30 | 3.90 | 0.78 | 10.2 | NA | PREDNISONA + MICOFELONATO | DARBEPOETINA | 30/7DIAS | 1 | 1.10 | Resistencia | SE DESCONOCE | 3 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | AGENESIA RENAL |
| SABJ721023/1 | 49 | 47.0 | MASCULINO | NINGUNO | ESTADIO 3B | 1.90 | 83.60 | 4.10 | 6.50 | 4.60 | 1.30 | 10.2 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/7DIAS | 1 | 0.63 | No resistencia | SI | 5 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | DESCONOCE |
| PERS790829/2 | 42 | 78.0 | FEMENINO | NINGUNO | ESTADIO 4 | 2.16 | 65.00 | 4.20 | 6.70 | 4.40 | 1.80 | 12.1 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 40/30DIAS | 0 | 0.25 | No resistencia | SI | 20 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | DESCONOCE |
| QUPR830621/1 | 39 | 90.0 | MASCULINO | HAS + HIPERPARATIROIDISMO | ESTADIO 5 | 9.70 | 159.40 | 4.00 | 12.60 | 8.50 | 2.20 | 8.4 | 1 | PREDNISONA | MIRCERA | 75/15DIAS | 1 | 1.60 | Resistencia | SI | 20 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | HAS |
| SEGJ561119/3 | 50 | 57.0 | FEMENINO | NINGUNO | ESTADIO 1 | 0.74 | 32.10 | 4.40 | 8.90 | 4.50 | 3.20 | 10.8 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/15DIAS | 0 | 0.52 | No resistencia | SE DESCONOCE | 22 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | DESCONOCE |
| PESL740912/ | 47 | 56.0 | FEMENINO | HAS | ESTADIO 3B | 1.90 | 45.30 | 4.00 | 4.40 | 2.60 | 1.04 | 13.1 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/15DIAS | 1 | 0.71 | No resistencia | SE DESCONOCE | 5 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | DESCONOCE |
| GAPM650628/ | 29 | 58.0 | MASCULINO | HAS | ESTADIO 4 | 2.60 | 60.35 | 4.70 | 3.20 | 1.82 | 1.80 | 13.1 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 30/15DIAS | 0 | 0.51 | No resistencia | SE DESCONOCE | 1 | TRDVR | SE DESCONOCE | 2 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | HIPOPLASIA RENAL |
| VACE631030/7 | 27 | 73.5 | MASCULINO | HAS + DISLIPIDEMIA | ESTADIO 4 | 2.90 | 93.90 | 3.90 | 8.10 | 68.90 | 1.38 | 14.2 | NA | PREDNISONA + MICOFELONATO + MTOR | DARBEPOETINA | 30/15DIAS | 1 | 0.41 | No resistencia | SE DESCONOCE | 13 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 1 | AGENESIA RENAL |
| GIHS680418/2 | 53 | 66.0 | FEMENINO | HAS + OSTEOPOROSIS | ESTADIO 4 | 2.80 | 71.60 | 4.50 | 7.57 | 4.33 | 2.40 | 9.6 | NA | MICOFENOLATO + MTOR | DARBEPOETINA | 40/7DIAS | 1 | 1.20 | No resistencia | SI | 14 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | PREECLAMPSIA |
| PIAR530714/9 | 68 | 51.0 | FEMENINO | HAS | ESTADIO 2 | 0.86 | 34.40 | 4.00 | 3.00 | 2.01 | 0.31 | 10.8 | NA | PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | DARBEPOETINA | 40/7DIAS | 1 | 1.50 | No resistencia | SI | 1 | TRDC | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | GEFYS |
| DITR760117/2 | 46 | 56.0 | FEMENINO | HIPERURICEMIA | ESTADIO 3B | 1.60 | 77.00 | 4.10 | 4.30 | 3.40 | 0.38 | 10.1 | NA | PREDNISONA + MTOR + AZATIOPRINA | DARBEPOETINA | 40/7DIAS | 0 | 1.40 | No resistencia | SI | 12 | TRDVR | SE DESCONOCE | 1 | SE DESCONOCE | SE DESCONOCE | SE DESCONOCE | 0 | ERPAD |
#ACONTINUACIÓN SE MUESTRA LA BASE DE DATO:Reporte de variables en total: Frecuencias y conteos (En total) de las variables que se someterán a análisis estadístico
dbdrort %>% select(EDAD, PESO, SEXO, COMORBIDOS, ERC, CR, U, ALBUMINA, LEUCOS,
NEU, LINF, HB, INFECCION, INMUNOSUPRESORES, AEE,
DOSIS, `IECA/ARA`, `DOSIS KDIGO`, RESISTENCIA,
TRANSFUSIONES, TIEMPO, TIPO, `EDAD DON`, `#`, FRIA, CALIENTE,
`FUNCION RETARDADA`, `Episodios de rechazo`, `Etiologia ERC`) %>% tbl_summary()## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead| Characteristic | N = 521 |
|---|---|
| EDAD | 44 (32, 49) |
| PESO | 62 (56, 70) |
| SEXO | |
| FEMENINO | 34 (65%) |
| MASCULINO | 18 (35%) |
| COMORBIDOS | |
| ESTENOSIS DE VEJIGA | 1 (1.9%) |
| HAS | 14 (27%) |
| HAS + DISLIPIDEMIA | 1 (1.9%) |
| HAS + DM | 4 (7.7%) |
| HAS + DM + VIH | 1 (1.9%) |
| HAS + HIPERPARATIROIDISMO | 1 (1.9%) |
| HAS + HIPERURICEMIA | 1 (1.9%) |
| HAS + HIPOTIROIDISMO | 1 (1.9%) |
| HAS + INSUF CARDIACA | 1 (1.9%) |
| HAS + OSTEOPOROSIS | 2 (3.8%) |
| HIPERURICEMIA | 3 (5.8%) |
| HIPOTIROIDISMO | 1 (1.9%) |
| NINGUNO | 21 (40%) |
| ERC | |
| ESTADIO 1 | 2 (3.8%) |
| ESTADIO 2 | 11 (21%) |
| ESTADIO 3A | 3 (5.8%) |
| ESTADIO 3B | 19 (37%) |
| ESTADIO 4 | 12 (23%) |
| ESTADIO 5 | 5 (9.6%) |
| CR | 1.89 (1.20, 2.80) |
| U | 64 (41, 89) |
| ALBUMINA | 4.10 (3.80, 4.32) |
| LEUCOS | 6.30 (4.88, 8.10) |
| NEU | 4.36 (3.13, 6.08) |
| LINF | 1.43 (1.01, 1.83) |
| HB | 11.50 (10.07, 12.53) |
| INFECCION | 1 (100%) |
| Unknown | 51 |
| INMUNOSUPRESORES | |
| INHIB CALCINEURINA + MICOFENOLATO | 3 (5.8%) |
| MICOFENOLATO + MTOR | 6 (12%) |
| PREDNISONA | 2 (3.8%) |
| PREDNISONA + INHIB CALCINEURINA | 2 (3.8%) |
| PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA | 3 (5.8%) |
| PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | 15 (29%) |
| PREDNISONA + INHIB CALCINEURINA + MTOR | 1 (1.9%) |
| PREDNISONA + MICOFELONATO | 3 (5.8%) |
| PREDNISONA + MICOFELONATO + MTOR | 9 (17%) |
| PREDNISONA + MTOR + AZATIOPRINA | 8 (15%) |
| AEE | |
| DARBEPOETINA | 46 (88%) |
| ERITROPOYETINA | 2 (3.8%) |
| MIRCERA | 4 (7.7%) |
| DOSIS | |
| 30/15 DIAS | 1 (1.9%) |
| 30/15DIAS | 9 (17%) |
| 30/30DIAS | 8 (15%) |
| 30/7DIAS | 4 (7.7%) |
| 40/15DIAS | 7 (13%) |
| 40/30 DIAS | 1 (1.9%) |
| 40/30DIAS | 2 (3.8%) |
| 40/7DIAS | 12 (23%) |
| 4000/30DIAS | 1 (1.9%) |
| 50/15DIAS | 1 (1.9%) |
| 60/7DIAS | 1 (1.9%) |
| 6000/7DIAS | 1 (1.9%) |
| 75/15DIAS | 2 (3.8%) |
| 75/7DIAS | 1 (1.9%) |
| 80/7DIAS | 1 (1.9%) |
| IECA/ARA | 26 (50%) |
| DOSIS KDIGO | 0.71 (0.48, 1.40) |
| RESISTENCIA | |
| No resistencia | 39 (75%) |
| Resistencia | 13 (25%) |
| TRANSFUSIONES | |
| SE DESCONOCE | 31 (60%) |
| SI | 21 (40%) |
| TIEMPO | 11 (5, 16) |
| TIPO | |
| TRDC | 16 (31%) |
| TRDVNR | 3 (5.8%) |
| TRDVR | 33 (63%) |
| EDAD DON | |
| 17 AÑOS | 1 (1.9%) |
| 47 AÑOS | 1 (1.9%) |
| SE DESCONOCE | 50 (96%) |
| # | |
| 1 | 48 (92%) |
| 2 | 4 (7.7%) |
| FRIA | |
| 6.9444444444444434E-2 | 1 (1.9%) |
| SE DESCONOCE | 51 (98%) |
| CALIENTE | |
| 30 | 1 (1.9%) |
| SE DESCONOCE | 51 (98%) |
| FUNCION RETARDADA | |
| SE DESCONOCE | 50 (96%) |
| SI | 2 (3.8%) |
| Episodios de rechazo | 10 (19%) |
| Etiologia ERC | |
| AGENESIA RENAL | 2 (3.8%) |
| AMILOIDOSIS | 1 (1.9%) |
| DESCONOCE | 19 (37%) |
| ERPAD | 2 (3.8%) |
| GEFYS | 3 (5.8%) |
| GLOMERULONEFRITIS ASOCIADA A INFECCION | 2 (3.8%) |
| GLOMERULONEFRITIS NO ESPECIFICADA | 1 (1.9%) |
| GLOMERULONEFRITIS POSTESTREPTOCOCICA | 2 (3.8%) |
| HAS | 4 (7.7%) |
| HAS,DM | 2 (3.8%) |
| HIPOPLASIA RENAL | 10 (19%) |
| LITIASIS REAL | 1 (1.9%) |
| PREECLAMPSIA | 2 (3.8%) |
| VEJIGA NEUROGENICA | 1 (1.9%) |
| 1 Median (IQR); n (%) | |
Análisis de variables demográficas
Distribución edad y sexo
#EDA
#graficas
#DISTRIBUCIÓN EDAD y SEXO TOTAL + PESO en un boxplot
#ANTES HACEMOS DIAGNÓSTICO DE LA DATA:
library(dlookr)
#normalitytest
dbdrort %>% group_by(SEXO) %>% plot_normality(EDAD)
dbdrort %>% group_by(SEXO) %>% normality(EDAD)## # A tibble: 2 × 5
## variable SEXO statistic p_value sample
## <chr> <chr> <dbl> <dbl> <dbl>
## 1 EDAD FEMENINO 0.961 0.253 34
## 2 EDAD MASCULINO 0.920 0.131 18#statistics: median, iqr and p value wilcoxon test
dbdrort %>% select(EDAD,SEXO) %>% tbl_summary(by=SEXO) %>% add_p()## Warning for variable 'EDAD':
## 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 | FEMENINO, N = 341 | MASCULINO, N = 181 | p-value2 |
|---|---|---|---|
| EDAD | 46 (37, 52) | 40 (27, 49) | 0.073 |
| 1 Median (IQR) | |||
| 2 Wilcoxon rank sum test | |||
library(ggpubr)
# Basic histogram plot with mean line and marginal rug
gghistogram(dbdrort, x = "EDAD", bins = 30,
fill = "#0073C2FF", color = "#0073C2FF",
add = "median", rug = TRUE)## Warning: geom_vline(): Ignoring `mapping` because `xintercept` was provided.## Warning: geom_vline(): Ignoring `data` because `xintercept` was provided.
# Change outline and fill colors by groups ("SEXO")
# Use a custom palette
fig1histograma<-gghistogram(dbdrort, x = "EDAD", bins = 30,
add = "mean", rug = TRUE,
color = "SEXO", fill = "SEXO",
palette = c("#0073C2FF", "#FC4E07"))
fig1histograma
La edad, de pendiendo de sexo se distribuye cumpliendo el supuesto de normalidad (p > 0.05)
Con base a la dicotomización para la variable anemia
se encontró lo siguiente:
#EDA
#FIGURA RESISTENCIA AEE
RESISTENCIA <- dbdrort %>%
group_by(RESISTENCIA) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
ggplot(RESISTENCIA, aes(x = RESISTENCIA, y = prop, fill= RESISTENCIA)) +
geom_bar(stat = "identity") +
geom_text(aes(label = prop), vjust = -0.3, fontface=2, size= 6) +
theme_pubclean() + ylab("%") + xlab ("RESISTENCIA")+
theme(text = element_text(size = 16, face="bold"), axis.text = element_text(size = 16, face="bold"),
legend.text = element_text(size = 12),)+ scale_fill_brewer(palette="Dark2")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+theme(legend.position = "none")
dbdrort %>% select(RESISTENCIA) %>% tbl_summary()| Characteristic | N = 521 |
|---|---|
| RESISTENCIA | |
| No resistencia | 39 (75%) |
| Resistencia | 13 (25%) |
| 1 n (%) | |
Tabla con todas las variables y RESISTENCIA A AEE
Esta tabla incluye pruebas estadísticas
## 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 'CR':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'U':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'ALBUMINA':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LEUCOS':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'NEU':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'LINF':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'HB':
## 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 'INFECCION', p-value omitted:
## Error in stats::fisher.test(c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, : 'x' and 'y' must have at least 2 levels## Warning for variable 'DOSIS KDIGO':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TIEMPO':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|
| EDAD | 44 (30, 49) | 44 (39, 53) | 0.6 |
| PESO | 62 (57, 70) | 62 (51, 68) | 0.5 |
| SEXO | >0.9 | ||
| FEMENINO | 25 (64%) | 9 (69%) | |
| MASCULINO | 14 (36%) | 4 (31%) | |
| COMORBIDOS | 0.068 | ||
| ESTENOSIS DE VEJIGA | 0 (0%) | 1 (7.7%) | |
| HAS | 10 (26%) | 4 (31%) | |
| HAS + DISLIPIDEMIA | 1 (2.6%) | 0 (0%) | |
| HAS + DM | 3 (7.7%) | 1 (7.7%) | |
| HAS + DM + VIH | 1 (2.6%) | 0 (0%) | |
| HAS + HIPERPARATIROIDISMO | 0 (0%) | 1 (7.7%) | |
| HAS + HIPERURICEMIA | 0 (0%) | 1 (7.7%) | |
| HAS + HIPOTIROIDISMO | 1 (2.6%) | 0 (0%) | |
| HAS + INSUF CARDIACA | 0 (0%) | 1 (7.7%) | |
| HAS + OSTEOPOROSIS | 1 (2.6%) | 1 (7.7%) | |
| HIPERURICEMIA | 2 (5.1%) | 1 (7.7%) | |
| HIPOTIROIDISMO | 1 (2.6%) | 0 (0%) | |
| NINGUNO | 19 (49%) | 2 (15%) | |
| ERC | 0.046 | ||
| ESTADIO 1 | 2 (5.1%) | 0 (0%) | |
| ESTADIO 2 | 10 (26%) | 1 (7.7%) | |
| ESTADIO 3A | 2 (5.1%) | 1 (7.7%) | |
| ESTADIO 3B | 16 (41%) | 3 (23%) | |
| ESTADIO 4 | 8 (21%) | 4 (31%) | |
| ESTADIO 5 | 1 (2.6%) | 4 (31%) | |
| CR | 1.80 (1.07, 2.50) | 3.00 (1.81, 4.70) | 0.011 |
| U | 57 (36, 74) | 87 (72, 118) | <0.001 |
| ALBUMINA | 4.20 (3.90, 4.40) | 3.80 (3.70, 4.10) | 0.026 |
| LEUCOS | 6.30 (4.90, 8.65) | 6.10 (4.90, 6.90) | 0.3 |
| NEU | 4.50 (3.05, 6.11) | 3.90 (3.30, 4.90) | 0.4 |
| LINF | 1.50 (1.18, 1.80) | 0.97 (0.78, 1.90) | 0.14 |
| HB | 12.20 (11.25, 12.75) | 8.80 (7.80, 9.90) | <0.001 |
| INFECCION | 0 (NA%) | 1 (100%) | |
| Unknown | 39 | 12 | |
| INMUNOSUPRESORES | 0.027 | ||
| INHIB CALCINEURINA + MICOFENOLATO | 3 (7.7%) | 0 (0%) | |
| MICOFENOLATO + MTOR | 5 (13%) | 1 (7.7%) | |
| PREDNISONA | 0 (0%) | 2 (15%) | |
| PREDNISONA + INHIB CALCINEURINA | 1 (2.6%) | 1 (7.7%) | |
| PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA | 3 (7.7%) | 0 (0%) | |
| PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | 13 (33%) | 2 (15%) | |
| PREDNISONA + INHIB CALCINEURINA + MTOR | 1 (2.6%) | 0 (0%) | |
| PREDNISONA + MICOFELONATO | 0 (0%) | 3 (23%) | |
| PREDNISONA + MICOFELONATO + MTOR | 7 (18%) | 2 (15%) | |
| PREDNISONA + MTOR + AZATIOPRINA | 6 (15%) | 2 (15%) | |
| AEE | 0.10 | ||
| DARBEPOETINA | 36 (92%) | 10 (77%) | |
| ERITROPOYETINA | 2 (5.1%) | 0 (0%) | |
| MIRCERA | 1 (2.6%) | 3 (23%) | |
| DOSIS | <0.001 | ||
| 30/15 DIAS | 1 (2.6%) | 0 (0%) | |
| 30/15DIAS | 9 (23%) | 0 (0%) | |
| 30/30DIAS | 8 (21%) | 0 (0%) | |
| 30/7DIAS | 3 (7.7%) | 1 (7.7%) | |
| 40/15DIAS | 7 (18%) | 0 (0%) | |
| 40/30 DIAS | 1 (2.6%) | 0 (0%) | |
| 40/30DIAS | 2 (5.1%) | 0 (0%) | |
| 40/7DIAS | 4 (10%) | 8 (62%) | |
| 4000/30DIAS | 1 (2.6%) | 0 (0%) | |
| 50/15DIAS | 0 (0%) | 1 (7.7%) | |
| 60/7DIAS | 1 (2.6%) | 0 (0%) | |
| 6000/7DIAS | 1 (2.6%) | 0 (0%) | |
| 75/15DIAS | 1 (2.6%) | 1 (7.7%) | |
| 75/7DIAS | 0 (0%) | 1 (7.7%) | |
| 80/7DIAS | 0 (0%) | 1 (7.7%) | |
| IECA/ARA | 15 (38%) | 11 (85%) | 0.004 |
| DOSIS KDIGO | 0.53 (0.40, 0.89) | 1.40 (1.20, 1.60) | <0.001 |
| TRANSFUSIONES | <0.001 | ||
| SE DESCONOCE | 29 (74%) | 2 (15%) | |
| SI | 10 (26%) | 11 (85%) | |
| TIEMPO | 11 (5, 15) | 12 (5, 20) | 0.6 |
| TIPO | >0.9 | ||
| TRDC | 12 (31%) | 4 (31%) | |
| TRDVNR | 2 (5.1%) | 1 (7.7%) | |
| TRDVR | 25 (64%) | 8 (62%) | |
| EDAD DON | >0.9 | ||
| 17 AÑOS | 1 (2.6%) | 0 (0%) | |
| 47 AÑOS | 1 (2.6%) | 0 (0%) | |
| SE DESCONOCE | 37 (95%) | 13 (100%) | |
| # | 0.6 | ||
| 1 | 35 (90%) | 13 (100%) | |
| 2 | 4 (10%) | 0 (0%) | |
| FRIA | 0.3 | ||
| 6.9444444444444434E-2 | 0 (0%) | 1 (7.7%) | |
| SE DESCONOCE | 39 (100%) | 12 (92%) | |
| CALIENTE | 0.3 | ||
| 30 | 0 (0%) | 1 (7.7%) | |
| SE DESCONOCE | 39 (100%) | 12 (92%) | |
| FUNCION RETARDADA | 0.059 | ||
| SE DESCONOCE | 39 (100%) | 11 (85%) | |
| SI | 0 (0%) | 2 (15%) | |
| Episodios de rechazo | 7 (18%) | 3 (23%) | 0.7 |
| Etiologia ERC | 0.11 | ||
| AGENESIA RENAL | 1 (2.6%) | 1 (7.7%) | |
| AMILOIDOSIS | 1 (2.6%) | 0 (0%) | |
| DESCONOCE | 18 (46%) | 1 (7.7%) | |
| ERPAD | 1 (2.6%) | 1 (7.7%) | |
| GEFYS | 2 (5.1%) | 1 (7.7%) | |
| GLOMERULONEFRITIS ASOCIADA A INFECCION | 1 (2.6%) | 1 (7.7%) | |
| GLOMERULONEFRITIS NO ESPECIFICADA | 1 (2.6%) | 0 (0%) | |
| GLOMERULONEFRITIS POSTESTREPTOCOCICA | 1 (2.6%) | 1 (7.7%) | |
| HAS | 2 (5.1%) | 2 (15%) | |
| HAS,DM | 2 (5.1%) | 0 (0%) | |
| HIPOPLASIA RENAL | 7 (18%) | 3 (23%) | |
| LITIASIS REAL | 1 (2.6%) | 0 (0%) | |
| PREECLAMPSIA | 1 (2.6%) | 1 (7.7%) | |
| VEJIGA NEUROGENICA | 0 (0%) | 1 (7.7%) | |
| 1 Median (IQR); n (%) | |||
| 2 Wilcoxon rank sum test; Fisher's exact test; Pearson's Chi-squared test | |||
Total de transplantados con anemia y uso de AEE
Objetivo 1
dbRESISAEE <- dbdrort %>%
group_by(RESISTENCIA,AEE) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))## `summarise()` has grouped output by 'RESISTENCIA'. You can override using the
## `.groups` argument.dbRESISAEE## # A tibble: 5 × 4
## # Groups: RESISTENCIA [2]
## RESISTENCIA AEE counts prop
## <chr> <chr> <int> <dbl>
## 1 No resistencia DARBEPOETINA 36 92.3
## 2 No resistencia ERITROPOYETINA 2 5.1
## 3 No resistencia MIRCERA 1 2.6
## 4 Resistencia DARBEPOETINA 10 76.9
## 5 Resistencia MIRCERA 3 23.1dbdrort %>% select(RESISTENCIA, AEE) %>% tbl_summary(by=RESISTENCIA) %>% add_p()## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|
| AEE | 0.10 | ||
| DARBEPOETINA | 36 (92%) | 10 (77%) | |
| ERITROPOYETINA | 2 (5.1%) | 0 (0%) | |
| MIRCERA | 1 (2.6%) | 3 (23%) | |
| 1 n (%) | |||
| 2 Fisher's exact test | |||
#Representación gráfica
library(dplyr)
library(ggpubr)
theme_set(theme_pubclean())
dbRESIAEE <- dbRESISAEE %>%
arrange(AEE, desc(RESISTENCIA)) %>%
mutate(lab_ypos = cumsum(counts) - 0.5 * counts)
head(dbRESIAEE, 4)## # A tibble: 4 × 5
## # Groups: RESISTENCIA [2]
## RESISTENCIA AEE counts prop lab_ypos
## <chr> <chr> <int> <dbl> <dbl>
## 1 Resistencia DARBEPOETINA 10 76.9 5
## 2 No resistencia DARBEPOETINA 36 92.3 18
## 3 No resistencia ERITROPOYETINA 2 5.1 37
## 4 Resistencia MIRCERA 3 23.1 11.5# Create stacked bar graphs with labels
ggplot(dbRESIAEE, aes(x = AEE, y = counts)) +
geom_bar(aes(color = RESISTENCIA, fill = RESISTENCIA), stat = "identity")+
scale_color_manual(values = c("#0073C2FF", "#EFC000FF"))+
scale_fill_manual(values = c("#0073C2FF", "#EFC000FF")) 
Objetivo 2: Describir las características bioquímicas en RTR con anemia y resistencia a AEE
#prevalencia de resistencia a AEE en los pacientes con anemia
prevresistencia<-dbdrort %>% select(AEE,CR,U,
ALBUMINA, LEUCOS, NEU,
LINF, HB, RESISTENCIA)
RESISTENCIA <- prevresistencia %>%
group_by(RESISTENCIA) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
ggplot(RESISTENCIA, aes(x = RESISTENCIA, y = prop, fill= RESISTENCIA)) +
geom_bar(stat = "identity") +
geom_text(aes(label = prop), vjust = -0.3, fontface=2, size= 6) +
theme_pubclean() + ylab("%") + xlab ("RESISTENCIA A AEE")+
theme(text = element_text(size = 16, face="bold"), axis.text = element_text(size = 16, face="bold"),
legend.text = element_text(size = 12),)+ scale_fill_brewer(palette="Dark2")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+theme(legend.position = "none")
#PREVALENCIA RESISTENCIA Y ANEMIA
prevresistenciaanemia<-dbdrort %>% select(RESISTENCIA)
prevresistenciaanemia %>% tbl_summary()## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead| Characteristic | N = 521 |
|---|---|
| RESISTENCIA | |
| No resistencia | 39 (75%) |
| Resistencia | 13 (25%) |
| 1 n (%) | |
dbanemiaRESISTENCIA <- prevresistenciaanemia %>%
group_by(RESISTENCIA) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
dbanemiaRESISTENCIA## # A tibble: 2 × 3
## RESISTENCIA counts prop
## <chr> <int> <dbl>
## 1 No resistencia 39 75
## 2 Resistencia 13 25#Representación gráfica
library(dplyr)
library(ggpubr)
theme_set(theme_pubclean())
dbanemiaRESIS <- dbanemiaRESISTENCIA %>%
arrange(RESISTENCIA) %>%
mutate(lab_ypos = cumsum(counts) - 0.5 * counts)
head(dbanemiaRESISTENCIA, 4)## # A tibble: 2 × 3
## RESISTENCIA counts prop
## <chr> <int> <dbl>
## 1 No resistencia 39 75
## 2 Resistencia 13 25# Create stacked bar graphs with labels
ggplot(dbanemiaRESIS, aes(x = RESISTENCIA, y = counts)) +
geom_bar(aes(color = RESISTENCIA, fill = RESISTENCIA), stat = "identity")+
scale_color_manual(values = c("#0073C2FF", "#EFC000FF"))+
scale_fill_manual(values = c("#0073C2FF", "#EFC000FF"))
#Filtrar anemia y resistentes a AEE (son 13 pacientes)
dbdrort %>% select(AEE,CR,U,
ALBUMINA, LEUCOS, NEU,
LINF, HB, RESISTENCIA) %>% tbl_summary(by= RESISTENCIA)| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 |
|---|---|---|
| AEE | ||
| DARBEPOETINA | 36 (92%) | 10 (77%) |
| ERITROPOYETINA | 2 (5.1%) | 0 (0%) |
| MIRCERA | 1 (2.6%) | 3 (23%) |
| CR | 1.80 (1.07, 2.50) | 3.00 (1.81, 4.70) |
| U | 57 (36, 74) | 87 (72, 118) |
| ALBUMINA | 4.20 (3.90, 4.40) | 3.80 (3.70, 4.10) |
| LEUCOS | 6.30 (4.90, 8.65) | 6.10 (4.90, 6.90) |
| NEU | 4.50 (3.05, 6.11) | 3.90 (3.30, 4.90) |
| LINF | 1.50 (1.18, 1.80) | 0.97 (0.78, 1.90) |
| HB | 12.20 (11.25, 12.75) | 8.80 (7.80, 9.90) |
| 1 n (%); Median (IQR) | ||
#hacer graficos de boxplot con su respectiva significancia estadistica
library(ggpubr)
#CR
CRbp <- dbdrort %>% select(CR, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
CRplot <- ggboxplot(CRbp, x = "RESISTENCIA", y = "CR",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#U
Ubp <-dbdrort %>% select(U, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
Uplot <- ggboxplot(Ubp, x = "RESISTENCIA", y = "U",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#ALBUMINA
ALBbp<-dbdrort %>% select(ALBUMINA, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
ALBplot <- ggboxplot(ALBbp, x = "RESISTENCIA", y = "ALBUMINA",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#LEUCOS
LEUbp<-dbdrort %>% select(LEUCOS, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
LEUplot <- ggboxplot(LEUbp, x = "RESISTENCIA", y = "LEUCOS",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#NEU
NEUbp<-dbdrort %>% select(NEU, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
NEUplot <- ggboxplot(NEUbp, x = "RESISTENCIA", y = "NEU",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#LINF
LINFbp <- dbdrort %>% select(LINF, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
LINFplot <- ggboxplot(LINFbp, x = "RESISTENCIA", y = "LINF",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#HB
HBbp <- dbdrort %>% select(HB, RESISTENCIA) %>% mutate(RESISTENCIA = factor(RESISTENCIA, levels=c("No resistencia", "Resistencia")))
HBplot <- ggboxplot(HBbp, x = "RESISTENCIA", y = "HB",
color = "RESISTENCIA", palette = "Paired",
add = "jitter")+ stat_compare_means()+ theme(legend.position = "none")+ xlab("")
#HACER UN SOLO GRAFICO CON COWPLOT
library(cowplot)##
## Attaching package: 'cowplot'## The following object is masked from 'package:ggpubr':
##
## get_legendBIOQbp<-plot_grid(CRplot, Uplot, ALBplot, LEUplot,NEUplot,LINFplot, HBplot,
labels = c('A', 'B','C','D','E', "F", "G"),
label_size = 12, nrow=4, ncol=2)
BIOQbp
Objetivo 3:Describir las principales características demográficas en RTR con anemia y resistencia a AEE
demodb<-dbdrort %>% select(EDAD, PESO, SEXO, COMORBIDOS, INMUNOSUPRESORES, AEE,
DOSIS, `IECA/ARA`, `DOSIS KDIGO`, RESISTENCIA,
TRANSFUSIONES, TIEMPO, TIPO, `EDAD DON`, `#`, FRIA, CALIENTE,
`FUNCION RETARDADA`, `Episodios de rechazo`, `Etiologia ERC`) %>% tbl_summary(by= RESISTENCIA)
demodb %>% add_p()## 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 'DOSIS KDIGO':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TIEMPO':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|
| EDAD | 44 (30, 49) | 44 (39, 53) | 0.6 |
| PESO | 62 (57, 70) | 62 (51, 68) | 0.5 |
| SEXO | >0.9 | ||
| FEMENINO | 25 (64%) | 9 (69%) | |
| MASCULINO | 14 (36%) | 4 (31%) | |
| COMORBIDOS | 0.068 | ||
| ESTENOSIS DE VEJIGA | 0 (0%) | 1 (7.7%) | |
| HAS | 10 (26%) | 4 (31%) | |
| HAS + DISLIPIDEMIA | 1 (2.6%) | 0 (0%) | |
| HAS + DM | 3 (7.7%) | 1 (7.7%) | |
| HAS + DM + VIH | 1 (2.6%) | 0 (0%) | |
| HAS + HIPERPARATIROIDISMO | 0 (0%) | 1 (7.7%) | |
| HAS + HIPERURICEMIA | 0 (0%) | 1 (7.7%) | |
| HAS + HIPOTIROIDISMO | 1 (2.6%) | 0 (0%) | |
| HAS + INSUF CARDIACA | 0 (0%) | 1 (7.7%) | |
| HAS + OSTEOPOROSIS | 1 (2.6%) | 1 (7.7%) | |
| HIPERURICEMIA | 2 (5.1%) | 1 (7.7%) | |
| HIPOTIROIDISMO | 1 (2.6%) | 0 (0%) | |
| NINGUNO | 19 (49%) | 2 (15%) | |
| INMUNOSUPRESORES | 0.027 | ||
| INHIB CALCINEURINA + MICOFENOLATO | 3 (7.7%) | 0 (0%) | |
| MICOFENOLATO + MTOR | 5 (13%) | 1 (7.7%) | |
| PREDNISONA | 0 (0%) | 2 (15%) | |
| PREDNISONA + INHIB CALCINEURINA | 1 (2.6%) | 1 (7.7%) | |
| PREDNISONA + INHIB CALCINEURINA + AZATIOPRINA | 3 (7.7%) | 0 (0%) | |
| PREDNISONA + INHIB CALCINEURINA + MICOFELONATO | 13 (33%) | 2 (15%) | |
| PREDNISONA + INHIB CALCINEURINA + MTOR | 1 (2.6%) | 0 (0%) | |
| PREDNISONA + MICOFELONATO | 0 (0%) | 3 (23%) | |
| PREDNISONA + MICOFELONATO + MTOR | 7 (18%) | 2 (15%) | |
| PREDNISONA + MTOR + AZATIOPRINA | 6 (15%) | 2 (15%) | |
| AEE | 0.10 | ||
| DARBEPOETINA | 36 (92%) | 10 (77%) | |
| ERITROPOYETINA | 2 (5.1%) | 0 (0%) | |
| MIRCERA | 1 (2.6%) | 3 (23%) | |
| DOSIS | <0.001 | ||
| 30/15 DIAS | 1 (2.6%) | 0 (0%) | |
| 30/15DIAS | 9 (23%) | 0 (0%) | |
| 30/30DIAS | 8 (21%) | 0 (0%) | |
| 30/7DIAS | 3 (7.7%) | 1 (7.7%) | |
| 40/15DIAS | 7 (18%) | 0 (0%) | |
| 40/30 DIAS | 1 (2.6%) | 0 (0%) | |
| 40/30DIAS | 2 (5.1%) | 0 (0%) | |
| 40/7DIAS | 4 (10%) | 8 (62%) | |
| 4000/30DIAS | 1 (2.6%) | 0 (0%) | |
| 50/15DIAS | 0 (0%) | 1 (7.7%) | |
| 60/7DIAS | 1 (2.6%) | 0 (0%) | |
| 6000/7DIAS | 1 (2.6%) | 0 (0%) | |
| 75/15DIAS | 1 (2.6%) | 1 (7.7%) | |
| 75/7DIAS | 0 (0%) | 1 (7.7%) | |
| 80/7DIAS | 0 (0%) | 1 (7.7%) | |
| IECA/ARA | 15 (38%) | 11 (85%) | 0.004 |
| DOSIS KDIGO | 0.53 (0.40, 0.89) | 1.40 (1.20, 1.60) | <0.001 |
| TRANSFUSIONES | <0.001 | ||
| SE DESCONOCE | 29 (74%) | 2 (15%) | |
| SI | 10 (26%) | 11 (85%) | |
| TIEMPO | 11 (5, 15) | 12 (5, 20) | 0.6 |
| TIPO | >0.9 | ||
| TRDC | 12 (31%) | 4 (31%) | |
| TRDVNR | 2 (5.1%) | 1 (7.7%) | |
| TRDVR | 25 (64%) | 8 (62%) | |
| EDAD DON | >0.9 | ||
| 17 AÑOS | 1 (2.6%) | 0 (0%) | |
| 47 AÑOS | 1 (2.6%) | 0 (0%) | |
| SE DESCONOCE | 37 (95%) | 13 (100%) | |
| # | 0.6 | ||
| 1 | 35 (90%) | 13 (100%) | |
| 2 | 4 (10%) | 0 (0%) | |
| FRIA | 0.3 | ||
| 6.9444444444444434E-2 | 0 (0%) | 1 (7.7%) | |
| SE DESCONOCE | 39 (100%) | 12 (92%) | |
| CALIENTE | 0.3 | ||
| 30 | 0 (0%) | 1 (7.7%) | |
| SE DESCONOCE | 39 (100%) | 12 (92%) | |
| FUNCION RETARDADA | 0.059 | ||
| SE DESCONOCE | 39 (100%) | 11 (85%) | |
| SI | 0 (0%) | 2 (15%) | |
| Episodios de rechazo | 7 (18%) | 3 (23%) | 0.7 |
| Etiologia ERC | 0.11 | ||
| AGENESIA RENAL | 1 (2.6%) | 1 (7.7%) | |
| AMILOIDOSIS | 1 (2.6%) | 0 (0%) | |
| DESCONOCE | 18 (46%) | 1 (7.7%) | |
| ERPAD | 1 (2.6%) | 1 (7.7%) | |
| GEFYS | 2 (5.1%) | 1 (7.7%) | |
| GLOMERULONEFRITIS ASOCIADA A INFECCION | 1 (2.6%) | 1 (7.7%) | |
| GLOMERULONEFRITIS NO ESPECIFICADA | 1 (2.6%) | 0 (0%) | |
| GLOMERULONEFRITIS POSTESTREPTOCOCICA | 1 (2.6%) | 1 (7.7%) | |
| HAS | 2 (5.1%) | 2 (15%) | |
| HAS,DM | 2 (5.1%) | 0 (0%) | |
| HIPOPLASIA RENAL | 7 (18%) | 3 (23%) | |
| LITIASIS REAL | 1 (2.6%) | 0 (0%) | |
| PREECLAMPSIA | 1 (2.6%) | 1 (7.7%) | |
| VEJIGA NEUROGENICA | 0 (0%) | 1 (7.7%) | |
| 1 Median (IQR); n (%) | |||
| 2 Wilcoxon rank sum test; Fisher's exact test; Pearson's Chi-squared test | |||
#Histogramas edad y sexo anemia y resistencia a AEE
demoagesexdb<-dbdrort %>% select(EDAD, SEXO, RESISTENCIA,
) %>% tbl_summary(by= RESISTENCIA)
demoagesexdb %>% add_p()## Warning for variable 'EDAD':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|
| EDAD | 44 (30, 49) | 44 (39, 53) | 0.6 |
| SEXO | >0.9 | ||
| FEMENINO | 25 (64%) | 9 (69%) | |
| MASCULINO | 14 (36%) | 4 (31%) | |
| 1 Median (IQR); n (%) | |||
| 2 Wilcoxon rank sum test; Fisher's exact test | |||
demodb<-dbdrort %>% select(EDAD, SEXO, RESISTENCIA) %>% filter(RESISTENCIA!="No resistencia")
# Basic histogram plot with mean line and marginal rug
gghistogram(demodb, x = "EDAD", bins = 30,
fill = "#0073C2FF", color = "#0073C2FF",
add = "median", rug = TRUE)
# Change outline and fill colors by groups ("SEXO")
# Use a custom palette
fig1histogramaANEMIAYRESISTENCIA<-gghistogram(demodb, x = "EDAD", bins = 30,
add = "mean", rug = TRUE,
color = "SEXO", fill = "SEXO",
palette = c("#0073C2FF", "#FC4E07"))
fig1histogramaANEMIAYRESISTENCIA
demodb<-dbdrort %>% select(SEXO, EDAD, RESISTENCIA) %>% tbl_summary(by=RESISTENCIA) %>% add_p()## Warning for variable 'EDAD':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with tiesdemodb| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|
| SEXO | >0.9 | ||
| FEMENINO | 25 (64%) | 9 (69%) | |
| MASCULINO | 14 (36%) | 4 (31%) | |
| EDAD | 44 (30, 49) | 44 (39, 53) | 0.6 |
| 1 n (%); Median (IQR) | |||
| 2 Fisher's exact test; Wilcoxon rank sum test | |||
#Plot comorbilidades
comorbdb<-dbdrort %>% select(COMORBIDOS, RESISTENCIA) %>% filter(RESISTENCIA!="No resistencia")
comorb <- comorbdb %>%
group_by(COMORBIDOS) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
ggplot(comorb, aes(x = COMORBIDOS, y = prop, fill= COMORBIDOS)) +
geom_bar(stat = "identity") +
geom_text(aes(label = prop), vjust = -0.3, fontface=2, size= 6) +
theme_pubclean() + ylab("%") + xlab ("Comorbilidades")+
theme(text = element_text(size = 16, face="bold"), axis.text = element_text(size = 16, face="bold"),
legend.text = element_text(size = 12),)+ scale_fill_brewer(palette="Paired")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+theme(legend.position = "none")
dbdrort%>% select(COMORBIDOS, RESISTENCIA) %>%
tbl_summary(by=RESISTENCIA) %>% add_p() %>% add_overall()| Characteristic | Overall, N = 521 | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|---|
| COMORBIDOS | 0.068 | |||
| ESTENOSIS DE VEJIGA | 1 (1.9%) | 0 (0%) | 1 (7.7%) | |
| HAS | 14 (27%) | 10 (26%) | 4 (31%) | |
| HAS + DISLIPIDEMIA | 1 (1.9%) | 1 (2.6%) | 0 (0%) | |
| HAS + DM | 4 (7.7%) | 3 (7.7%) | 1 (7.7%) | |
| HAS + DM + VIH | 1 (1.9%) | 1 (2.6%) | 0 (0%) | |
| HAS + HIPERPARATIROIDISMO | 1 (1.9%) | 0 (0%) | 1 (7.7%) | |
| HAS + HIPERURICEMIA | 1 (1.9%) | 0 (0%) | 1 (7.7%) | |
| HAS + HIPOTIROIDISMO | 1 (1.9%) | 1 (2.6%) | 0 (0%) | |
| HAS + INSUF CARDIACA | 1 (1.9%) | 0 (0%) | 1 (7.7%) | |
| HAS + OSTEOPOROSIS | 2 (3.8%) | 1 (2.6%) | 1 (7.7%) | |
| HIPERURICEMIA | 3 (5.8%) | 2 (5.1%) | 1 (7.7%) | |
| HIPOTIROIDISMO | 1 (1.9%) | 1 (2.6%) | 0 (0%) | |
| NINGUNO | 21 (40%) | 19 (49%) | 2 (15%) | |
| 1 n (%) | ||||
| 2 Fisher's exact test | ||||
#INMUNOSUPRESORES
inmunodb<-dbdrort %>% select(INMUNOSUPRESORES, RESISTENCIA) %>% filter(RESISTENCIA!="No resistencia")
inmuno <- inmunodb %>%
group_by(INMUNOSUPRESORES) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
plotimm<-ggplot(inmuno, aes(x = INMUNOSUPRESORES, y = prop, fill= INMUNOSUPRESORES)) +
geom_bar(stat = "identity") +
geom_text(aes(label = prop), vjust = -0.3, fontface=2, size= 6) +
theme_pubclean() + ylab("%") + xlab ("Inmunosupresores")+
theme(text = element_text(size = 16, face="bold"), axis.text = element_text(size = 16, face="bold"),
legend.text = element_text(size = 12),)+ scale_fill_brewer(palette="Paired")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+theme(legend.position = "none")
plotimm
#AEE en general
AEEdb<-dbdrort %>% select(AEE, RESISTENCIA)
AEEdb %>% tbl_summary()| Characteristic | N = 521 |
|---|---|
| AEE | |
| DARBEPOETINA | 46 (88%) |
| ERITROPOYETINA | 2 (3.8%) |
| MIRCERA | 4 (7.7%) |
| RESISTENCIA | |
| No resistencia | 39 (75%) |
| Resistencia | 13 (25%) |
| 1 n (%) | |
AEE <-AEEdb %>%
group_by(AEE) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
ggplot(AEE, aes(x = AEE, y = prop, fill= AEE)) +
geom_bar(stat = "identity") +
geom_text(aes(label = prop), vjust = -0.3, fontface=2, size= 6) +
theme_pubclean() + ylab("%") + xlab ("AEE")+
theme(text = element_text(size = 16, face="bold"), axis.text = element_text(size = 16, face="bold"),
legend.text = element_text(size = 12),)+ scale_fill_brewer(palette="Paired")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+theme(legend.position = "none")
AEEdb %>% tbl_summary(by= RESISTENCIA) %>% add_p() %>% add_overall()| Characteristic | Overall, N = 521 | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|---|
| AEE | 0.10 | |||
| DARBEPOETINA | 46 (88%) | 36 (92%) | 10 (77%) | |
| ERITROPOYETINA | 2 (3.8%) | 2 (5.1%) | 0 (0%) | |
| MIRCERA | 4 (7.7%) | 1 (2.6%) | 3 (23%) | |
| 1 n (%) | ||||
| 2 Fisher's exact test | ||||
#AEE en anemia
AEEdb<-dbdrort %>% select(AEE, RESISTENCIA) %>% filter(RESISTENCIA!="No resistencia")
AEE <-AEEdb %>%
group_by(AEE) %>%
summarise(counts = n()) %>%
mutate(prop = round(counts*100/sum(counts), 1))
ggplot(AEE, aes(x = AEE, y = prop, fill= AEE)) +
geom_bar(stat = "identity") +
geom_text(aes(label = prop), vjust = -0.3, fontface=2, size= 6) +
theme_pubclean() + ylab("%") + xlab ("AEE")+
theme(text = element_text(size = 16, face="bold"), axis.text = element_text(size = 16, face="bold"),
legend.text = element_text(size = 12),)+ scale_fill_brewer(palette="Paired")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+theme(legend.position = "none")
demodb<-dbdrort %>% select(
DOSIS, `IECA/ARA`, `DOSIS KDIGO`, RESISTENCIA,
TRANSFUSIONES, TIEMPO, TIPO, `EDAD DON`, `#`, FRIA, CALIENTE,
`FUNCION RETARDADA`, `Episodios de rechazo`, `Etiologia ERC`) %>% tbl_summary(by= RESISTENCIA)
demodb %>% add_p()## Warning for variable 'DOSIS KDIGO':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties## Warning for variable 'TIEMPO':
## simpleWarning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot compute exact p-value with ties| Characteristic | No resistencia, N = 391 | Resistencia, N = 131 | p-value2 |
|---|---|---|---|
| DOSIS | <0.001 | ||
| 30/15 DIAS | 1 (2.6%) | 0 (0%) | |
| 30/15DIAS | 9 (23%) | 0 (0%) | |
| 30/30DIAS | 8 (21%) | 0 (0%) | |
| 30/7DIAS | 3 (7.7%) | 1 (7.7%) | |
| 40/15DIAS | 7 (18%) | 0 (0%) | |
| 40/30 DIAS | 1 (2.6%) | 0 (0%) | |
| 40/30DIAS | 2 (5.1%) | 0 (0%) | |
| 40/7DIAS | 4 (10%) | 8 (62%) | |
| 4000/30DIAS | 1 (2.6%) | 0 (0%) | |
| 50/15DIAS | 0 (0%) | 1 (7.7%) | |
| 60/7DIAS | 1 (2.6%) | 0 (0%) | |
| 6000/7DIAS | 1 (2.6%) | 0 (0%) | |
| 75/15DIAS | 1 (2.6%) | 1 (7.7%) | |
| 75/7DIAS | 0 (0%) | 1 (7.7%) | |
| 80/7DIAS | 0 (0%) | 1 (7.7%) | |
| IECA/ARA | 15 (38%) | 11 (85%) | 0.004 |
| DOSIS KDIGO | 0.53 (0.40, 0.89) | 1.40 (1.20, 1.60) | <0.001 |
| TRANSFUSIONES | <0.001 | ||
| SE DESCONOCE | 29 (74%) | 2 (15%) | |
| SI | 10 (26%) | 11 (85%) | |
| TIEMPO | 11 (5, 15) | 12 (5, 20) | 0.6 |
| TIPO | >0.9 | ||
| TRDC | 12 (31%) | 4 (31%) | |
| TRDVNR | 2 (5.1%) | 1 (7.7%) | |
| TRDVR | 25 (64%) | 8 (62%) | |
| EDAD DON | >0.9 | ||
| 17 AÑOS | 1 (2.6%) | 0 (0%) | |
| 47 AÑOS | 1 (2.6%) | 0 (0%) | |
| SE DESCONOCE | 37 (95%) | 13 (100%) | |
| # | 0.6 | ||
| 1 | 35 (90%) | 13 (100%) | |
| 2 | 4 (10%) | 0 (0%) | |
| FRIA | 0.3 | ||
| 6.9444444444444434E-2 | 0 (0%) | 1 (7.7%) | |
| SE DESCONOCE | 39 (100%) | 12 (92%) | |
| CALIENTE | 0.3 | ||
| 30 | 0 (0%) | 1 (7.7%) | |
| SE DESCONOCE | 39 (100%) | 12 (92%) | |
| FUNCION RETARDADA | 0.059 | ||
| SE DESCONOCE | 39 (100%) | 11 (85%) | |
| SI | 0 (0%) | 2 (15%) | |
| Episodios de rechazo | 7 (18%) | 3 (23%) | 0.7 |
| Etiologia ERC | 0.11 | ||
| AGENESIA RENAL | 1 (2.6%) | 1 (7.7%) | |
| AMILOIDOSIS | 1 (2.6%) | 0 (0%) | |
| DESCONOCE | 18 (46%) | 1 (7.7%) | |
| ERPAD | 1 (2.6%) | 1 (7.7%) | |
| GEFYS | 2 (5.1%) | 1 (7.7%) | |
| GLOMERULONEFRITIS ASOCIADA A INFECCION | 1 (2.6%) | 1 (7.7%) | |
| GLOMERULONEFRITIS NO ESPECIFICADA | 1 (2.6%) | 0 (0%) | |
| GLOMERULONEFRITIS POSTESTREPTOCOCICA | 1 (2.6%) | 1 (7.7%) | |
| HAS | 2 (5.1%) | 2 (15%) | |
| HAS,DM | 2 (5.1%) | 0 (0%) | |
| HIPOPLASIA RENAL | 7 (18%) | 3 (23%) | |
| LITIASIS REAL | 1 (2.6%) | 0 (0%) | |
| PREECLAMPSIA | 1 (2.6%) | 1 (7.7%) | |
| VEJIGA NEUROGENICA | 0 (0%) | 1 (7.7%) | |
| 1 n (%); Median (IQR) | |||
| 2 Fisher's exact test; Pearson's Chi-squared test; Wilcoxon rank sum test | |||
Regresión lógistica
library(finalfit)
library(broom)
dborresi<-dbdrort %>% select(EDAD,SEXO,AEE, RESISTENCIA, CR, U, LEUCOS, NEU,LINF,INFECCION,INMUNOSUPRESORES,`IECA/ARA`, `DOSIS KDIGO`, TRANSFUSIONES,DOSIS)
#dicotomizar variable
dborresi<-dborresi %>% mutate(resior = ifelse(RESISTENCIA == "Resistencia",
'1', '0'))
#dborresi
dborresi$resior = as.numeric(dborresi$resior)
#explanatory <- c("IECA/ARA", "DOSIS KDIGO", "TRANSFUSIONES")
#dependent <- "resior"
#tablelr <- dborresi %>% finalfit(dependent, explanatory, dependent_label_prefix = "")
#tablelr
#dborresi %>%
# or_plot(dependent, explanatory,
# breaks = c(0.5,0,0.5),
# table_text_size = 5)
#modelo
model <- glm(resior ~ AEE+EDAD+SEXO+CR+U, family = "binomial", data = dborresi)
summary(model)##
## Call:
## glm(formula = resior ~ AEE + EDAD + SEXO + CR + U, family = "binomial",
## data = dborresi)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.30479 -0.63750 -0.34809 0.02218 2.06446
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -6.78663 2.67147 -2.540 0.0111 *
## AEEERITROPOYETINA -17.09153 2784.44006 -0.006 0.9951
## AEEMIRCERA 0.56912 2.25782 0.252 0.8010
## EDAD 0.06247 0.04216 1.481 0.1385
## SEXOMASCULINO -0.57031 1.03422 -0.551 0.5813
## CR 0.39873 0.47285 0.843 0.3991
## U 0.02894 0.02039 1.419 0.1559
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 58.483 on 51 degrees of freedom
## Residual deviance: 39.540 on 45 degrees of freedom
## AIC: 53.54
##
## Number of Fisher Scoring iterations: 16mv_reg <- glm(resior ~ `IECA/ARA`+`DOSIS KDIGO`+TRANSFUSIONES, family = "binomial", data = dborresi)
summary(mv_reg)##
## Call:
## glm(formula = resior ~ `IECA/ARA` + `DOSIS KDIGO` + TRANSFUSIONES,
## family = "binomial", data = dborresi)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6094 -0.5483 -0.1957 0.1576 2.0096
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.92206 1.07107 -3.662 0.00025 ***
## `IECA/ARA` 2.12199 0.94370 2.249 0.02454 *
## `DOSIS KDIGO` -0.04791 0.05818 -0.823 0.41026
## TRANSFUSIONESSI 2.80532 0.92061 3.047 0.00231 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 58.483 on 51 degrees of freedom
## Residual deviance: 36.571 on 48 degrees of freedom
## AIC: 44.571
##
## Number of Fisher Scoring iterations: 6library(stringr)
library(dplyr)
library(gtsummary)
library(purrr)
## define variables of interest
explanatory_vars <- c("`IECA/ARA`","`DOSIS KDIGO`","TRANSFUSIONES")
explanatory_vars %>% str_c("resior ~ ", .)## [1] "resior ~ `IECA/ARA`" "resior ~ `DOSIS KDIGO`" "resior ~ TRANSFUSIONES"## run a regression with all variables of interest
mv_reg <- explanatory_vars %>% ## begin with vector of explanatory column names
str_c(collapse = "+") %>% ## combine all names of the variables of interest separated by a plus
str_c("resior ~ ", .) %>% ## combine the names of variables of interest with outcome in formula style
glm(family = "binomial", ## define type of glm as logistic,
data = dborresi) ## define your dataset
mv_reg##
## Call: glm(formula = ., family = "binomial", data = dborresi)
##
## Coefficients:
## (Intercept) `IECA/ARA` `DOSIS KDIGO` TRANSFUSIONESSI
## -3.92206 2.12199 -0.04791 2.80532
##
## Degrees of Freedom: 51 Total (i.e. Null); 48 Residual
## Null Deviance: 58.48
## Residual Deviance: 36.57 AIC: 44.57## choose a model using forward selection based on AIC
## you can also do "backward" or "both" by adjusting the direction
final_mv_reg <- mv_reg %>%
step(direction = "forward", trace = FALSE)
final_mv_reg##
## Call: glm(formula = resior ~ `IECA/ARA` + `DOSIS KDIGO` + TRANSFUSIONES,
## family = "binomial", data = dborresi)
##
## Coefficients:
## (Intercept) `IECA/ARA` `DOSIS KDIGO` TRANSFUSIONESSI
## -3.92206 2.12199 -0.04791 2.80532
##
## Degrees of Freedom: 51 Total (i.e. Null); 48 Residual
## Null Deviance: 58.48
## Residual Deviance: 36.57 AIC: 44.57mv_tab_base <- final_mv_reg %>%
broom::tidy(exponentiate = TRUE, conf.int = TRUE) %>% ## get a tidy dataframe of estimates
mutate(across(where(is.numeric), round, digits = 2)) ## round
## show results table of final regression
mv_tab <- tbl_regression(final_mv_reg, exponentiate = TRUE)
mv_tab| Characteristic | OR1 | 95% CI1 | p-value |
|---|---|---|---|
| IECA/ARA | 8.35 | 1.52, 70.4 | 0.025 |
| DOSIS KDIGO | 0.95 | 0.4 | |
| TRANSFUSIONES | |||
| SE DESCONOCE | — | — | |
| SI | 16.5 | 3.21, 135 | 0.002 |
| 1 OR = Odds Ratio, CI = Confidence Interval | |||