library(funModeling)

## Loading required package: Hmisc

## Loading required package: lattice

## Loading required package: survival

## Loading required package: Formula

## Loading required package: ggplot2

## 
## Attaching package: 'Hmisc'

## The following objects are masked from 'package:base':
## 
##     format.pval, units

## funModeling v.1.9.4 :)
## Examples and tutorials at livebook.datascienceheroes.com
##  / Now in Spanish: librovivodecienciadedatos.ai

library(tidyverse)

## ── Attaching packages
## ───────────────────────────────────────
## tidyverse 1.3.2 ──

## ✔ tibble  3.1.7     ✔ dplyr   1.0.9
## ✔ tidyr   1.2.0     ✔ stringr 1.4.0
## ✔ readr   2.1.2     ✔ forcats 0.5.1
## ✔ purrr   0.3.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter()    masks stats::filter()
## ✖ dplyr::lag()       masks stats::lag()
## ✖ dplyr::src()       masks Hmisc::src()
## ✖ dplyr::summarize() masks Hmisc::summarize()

library(Hmisc)
library(tidyverse)
library(ggpubr)
library(gtable)
library(gt)

## 
## Attaching package: 'gt'
## 
## The following object is masked from 'package:Hmisc':
## 
##     html

library(survival)
library(ggpubr)
library(survminer)

## 
## Attaching package: 'survminer'
## 
## The following object is masked from 'package:survival':
## 
##     myeloma

library(readr)
library(gtsummary)

dbcovid <- read_delim("C:/Users/fidel/OneDrive - CINVESTAV/Proyecto colaboración SSA/base de datos/SISVER/dbcovid.txt", 
                      delim = "|", escape_double = FALSE, trim_ws = TRUE)

## Rows: 429902 Columns: 130
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "|"
## chr (106): ORIGEN, SECTOR, CVEMUNUNI, ENTIDAD, DELEGA, UNIDAD, FECHREG, CLUE...
## dbl  (12): ID_REGISTRO, CVEENTUNI, CVENTINE, CVELOCAL, LATLOCA, LONGLOCA, SE...
## lgl  (12): RESDEFIN2, PAISORI, FINGMEX, PAISTRAN1, PAISTRAN2, PAISTRAN3, PAI...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

covidsin<-dbcovid 

covidsinfilt <-  covidsin %>% filter(RESDEFIN == "SARS-CoV-2" & CLASCOVID19 =="CONF LAB")

covidsinfilt$FECINISI <- strptime(as.character(covidsinfilt$FECINISI), "%d/%m/%Y")

covidsinfilt$FECINISI = as.Date(covidsinfilt$FECINISI)

TOTAL DE CASOS CONFIRMADOS Y POSITIVOS A SARS-CoV-2 de enero 2020 a diciembre 2022

freq(covidsinfilt$RESDEFIN)

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

CURVA EPIDEMIOLOGICA

library(lubridate)

## 
## Attaching package: 'lubridate'

## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union

library(epiR); library(ggplot2); library(scales); library(zoo)

## Warning: package 'epiR' was built under R version 4.2.2

## Package epiR 2.0.53 is loaded

## Type help(epi.about) for summary information

## Type browseVignettes(package = 'epiR') to learn how to use epiR for applied epidemiological analyses

##

## 
## Attaching package: 'scales'

## The following object is masked from 'package:purrr':
## 
##     discard

## The following object is masked from 'package:readr':
## 
##     col_factor

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:Hmisc':
## 
##     subplot

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

epiplot <-ggplot(data = covidsinfilt, aes(x = as.Date(FECINISI))) +
  theme_bw() +
  geom_histogram(binwidth = 7, colour = "black", fill = "#3e78d6", size = 0.1) +
  geom_density(aes(y = ..density.. * (nrow(covidsinfilt) * 10)), colour = "red", size=0.8) +
  scale_x_date( labels = date_format("%d/%m/%Y"), 
     name = "Date") +
  scale_y_continuous(breaks = seq(from = 0, to =1500, by = 100), name = "Number of cases") + theme_classic()+
  theme(axis.text.x = element_text(angle = 90, hjust = 1))

  ggplotly(epiplot)

ANALISIS DE SUPERVIVENCIA

PREPARACIÓN DE LOS DATO: LIMPIEZA, FILTRADO

library(gt)
#crear columna de estatus
covidsinfilt <- covidsinfilt %>% mutate(estatus = case_when(is.na(FECDEF) ~ "Sobrevivió"))

covidsinfilt <- covidsinfilt %>% replace_na(list(estatus = "No sobrevivió")) #con la función "remplace_na"

library(lubridate)

covidsinfilt$FECDEF <- strptime(as.character(covidsinfilt$FECDEF), "%d/%m/%Y")

covidsinfilt$FECDEF = as.Date(covidsinfilt$FECDEF)

str(covidsinfilt$FECDEF)

##  Date[1:51921], format: NA NA NA NA "2020-05-17" NA NA "2020-09-09" NA "2020-05-03" NA NA NA ...

covidsinfilt <- covidsinfilt %>% mutate(deftime = as.double(FECDEF-FECINISI)) 

covidsinfilt %>% select(FECDEF,FECINISI, deftime, estatus)

covidsinfilt <- covidsinfilt %>% mutate(evento = ifelse(is.na(estatus) | estatus == "No sobrevivió", 1, 0)) 

covidsinfilt %>% select(evento, estatus,deftime)

ANALISIS DE FRECUENCIAS OVERALL VARIABLES

covidsinfilt %>% select(RESDEFIN,CLASCOVID19,SEXO,EDAD,ESINDIGE,OCUPACIO,TIPACIEN,EVOLUCI,INTUBADO,DIGCLINE,DIAGPROB,FIEBRE:TXANTIVI,ANTIVIRA,
                                     ANTIPIRETICOS,VACUNADO,TIPO_VAC_COV,estatus) %>% freq()

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##     RESDEFIN frequency percentage cumulative_perc
## 1 SARS-CoV-2     51921        100             100

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   CLASCOVID19 frequency percentage cumulative_perc
## 1    CONF LAB     51921        100             100

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##        SEXO frequency percentage cumulative_perc
## 1  FEMENINO     27082      52.16           52.16
## 2 MASCULINO     24839      47.84          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   ESINDIGE frequency percentage cumulative_perc
## 1       NO     49789      95.89           95.89
## 2     <NA>      1982       3.82           99.71
## 3       SI       150       0.29          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##                                          OCUPACIO frequency percentage
## 1                                       EMPLEADOS     15861      30.55
## 2                                           OTROS      8517      16.40
## 3                                           HOGAR      7207      13.88
## 4                           JUBILADO / PENSIONADO      3418       6.58
## 5                                      ENFERMERAS      2852       5.49
## 6                                     ESTUDIANTES      2615       5.04
## 7                                    DESEMPLEADOS      2489       4.79
## 8                  OTROS TRABAJADORES DE LA SALUD      2294       4.42
## 9                                         MEDICOS      2037       3.92
## 10                                       MAESTROS      1116       2.15
## 11                           OTROS PROFESIONISTAS      1102       2.12
## 12    COMERCIANTES DE MERCADOS FIJOS O AMBULANTES       707       1.36
## 13                                     CAMPESINOS       511       0.98
## 14                                       CHOFERES       383       0.74
## 15                                        OBREROS       316       0.61
## 16                                 LABORATORISTAS       187       0.36
## 17 GERENTES O PROPIETARIOS DE EMPRESAS O NEGOCIOS       186       0.36
## 18                                      DENTISTAS       123       0.24
##    cumulative_perc
## 1            30.55
## 2            46.95
## 3            60.83
## 4            67.41
## 5            72.90
## 6            77.94
## 7            82.73
## 8            87.15
## 9            91.07
## 10           93.22
## 11           95.34
## 12           96.70
## 13           97.68
## 14           98.42
## 15           99.03
## 16           99.39
## 17           99.75
## 18          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##        TIPACIEN frequency percentage cumulative_perc
## 1   AMBULATORIO     36345         70              70
## 2 HOSPITALIZADO     15576         30             100

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##                     EVOLUCI frequency percentage cumulative_perc
## 1     SEGUIMIENTO TERMINADO     36726      70.73           70.73
## 2                 DEFUNCION      7627      14.69           85.42
## 3            ALTA - MEJORIA      6720      12.94           98.36
## 4         ALTA - VOLUNTARIA       329       0.63           98.99
## 5           ALTA - TRASLADO       200       0.39           99.38
## 6           ALTA - CURACION       152       0.29           99.67
## 7  SEGUIMIENTO DOMICILIARIO        78       0.15           99.82
## 8            EN TRATAMIENTO        45       0.09           99.91
## 9              CASO GRAVE -        16       0.03           99.94
## 10            CASO NO GRAVE        16       0.03           99.97
## 11               REFERENCIA        11       0.02           99.99
## 12    CASO GRAVE - TRASLADO         1       0.00          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   INTUBADO frequency percentage cumulative_perc
## 1     <NA>     37155      71.56           71.56
## 2       NO     12772      24.60           96.16
## 3       SI      1994       3.84          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   DIGCLINE frequency percentage cumulative_perc
## 1       NO     40832      78.64           78.64
## 2       SI     11089      21.36          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##                                    DIAGPROB frequency percentage
## 1           ENFERMEDAD TIPO INFLUENZA (ETI)     37331       71.9
## 2 INFECCION RESPIRATORIA AGUDA GRAVE (IRAG)     14590       28.1
##   cumulative_perc
## 1            71.9
## 2           100.0

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##      FIEBRE frequency percentage cumulative_perc
## 1        SI     38433      74.02           74.02
## 2        NO     13467      25.94           99.96
## 3 SE IGNORA        21       0.04          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##         TOS frequency percentage cumulative_perc
## 1        SI     40651      78.29           78.29
## 2        NO     11253      21.67           99.96
## 3 SE IGNORA        17       0.03          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    ODINOGIA frequency percentage cumulative_perc
## 1        NO     29052      55.95           55.95
## 2        SI     22762      43.84           99.79
## 3 SE IGNORA       107       0.21          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##      DISNEA frequency percentage cumulative_perc
## 1        NO     34258      65.98           65.98
## 2        SI     17653      34.00           99.98
## 3 SE IGNORA        10       0.02          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    IRRITABI frequency percentage cumulative_perc
## 1        NO     35195      67.79           67.79
## 2        SI     16688      32.14           99.93
## 3 SE IGNORA        38       0.07          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##     DIARREA frequency percentage cumulative_perc
## 1        NO     42489      81.83           81.83
## 2        SI      9395      18.09           99.92
## 3 SE IGNORA        37       0.07          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    DOTORACI frequency percentage cumulative_perc
## 1        NO     37627      72.47           72.47
## 2        SI     14190      27.33           99.80
## 3 SE IGNORA       104       0.20          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   CALOFRIOS frequency percentage cumulative_perc
## 1        NO     35428      68.23           68.23
## 2        SI     16399      31.58           99.81
## 3 SE IGNORA        94       0.18          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##     CEFALEA frequency percentage cumulative_perc
## 1        SI     40789      78.56           78.56
## 2        NO     11094      21.37           99.93
## 3 SE IGNORA        38       0.07          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    MIALGIAS frequency percentage cumulative_perc
## 1        SI     31037      59.78           59.78
## 2        NO     20777      40.02           99.80
## 3 SE IGNORA       107       0.21          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##      ARTRAL frequency percentage cumulative_perc
## 1        SI     28609      55.10           55.10
## 2        NO     23199      44.68           99.78
## 3 SE IGNORA       113       0.22          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    ATAEDOGE frequency percentage cumulative_perc
## 1        NO     29458      56.74           56.74
## 2        SI     22340      43.03           99.77
## 3 SE IGNORA       123       0.24          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    RINORREA frequency percentage cumulative_perc
## 1        NO     33149      63.85           63.85
## 2        SI     18649      35.92           99.77
## 3 SE IGNORA       123       0.24          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    POLIPNEA frequency percentage cumulative_perc
## 1        NO     46594      89.74           89.74
## 2        SI      5194      10.00           99.74
## 3 SE IGNORA       133       0.26          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##      VOMITO frequency percentage cumulative_perc
## 1        NO     48088      92.62           92.62
## 2        SI      3695       7.12           99.74
## 3 SE IGNORA       138       0.27          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##     DOLABDO frequency percentage cumulative_perc
## 1        NO     46229      89.04           89.04
## 2        SI      5545      10.68           99.72
## 3 SE IGNORA       147       0.28          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##      CONJUN frequency percentage cumulative_perc
## 1        NO     46816      90.17           90.17
## 2        SI      4951       9.54           99.71
## 3 SE IGNORA       154       0.30          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    CIANOSIS frequency percentage cumulative_perc
## 1        NO     50714      97.68           97.68
## 2        SI      1058       2.04           99.72
## 3 SE IGNORA       149       0.29          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    INISUBIS frequency percentage cumulative_perc
## 1        NO     38524      74.20           74.20
## 2        SI     13197      25.42           99.62
## 3 SE IGNORA       200       0.39          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##     ANOSMIA frequency percentage cumulative_perc
## 1        NO     37419      72.07           72.07
## 2        SI      8782      16.91           88.98
## 3 SE IGNORA      5720      11.02          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   DISGEUSIA frequency percentage cumulative_perc
## 1        NO     38385      73.93           73.93
## 2        SI      7721      14.87           88.80
## 3 SE IGNORA      5815      11.20          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   ASINTOMATICO frequency percentage cumulative_perc
## 1           NO     51391      98.98           98.98
## 2           SI       496       0.96           99.94
## 3    SE IGNORA        34       0.07          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    DIABETES frequency percentage cumulative_perc
## 1        NO     44610      85.92           85.92
## 2        SI      7195      13.86           99.78
## 3 SE IGNORA       116       0.22          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##        EPOC frequency percentage cumulative_perc
## 1        NO     51138      98.49           98.49
## 2        SI       704       1.36           99.85
## 3 SE IGNORA        79       0.15          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##        ASMA frequency percentage cumulative_perc
## 1        NO     50696      97.64           97.64
## 2        SI      1139       2.19           99.83
## 3 SE IGNORA        86       0.17          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    INMUSUPR frequency percentage cumulative_perc
## 1        NO     51270      98.75           98.75
## 2        SI       553       1.07           99.82
## 3 SE IGNORA        98       0.19          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    HIPERTEN frequency percentage cumulative_perc
## 1        NO     40685      78.36           78.36
## 2        SI     11129      21.43           99.79
## 3 SE IGNORA       107       0.21          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    VIH.SIDA frequency percentage cumulative_perc
## 1        NO     51658      99.49           99.49
## 2        SI       167       0.32           99.81
## 3 SE IGNORA        96       0.18          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##     OTRACON frequency percentage cumulative_perc
## 1        NO     50306      96.89           96.89
## 2        SI      1489       2.87           99.76
## 3 SE IGNORA       126       0.24          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    ENFCARDI frequency percentage cumulative_perc
## 1        NO     50544      97.35           97.35
## 2        SI      1279       2.46           99.81
## 3 SE IGNORA        98       0.19          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    OBESIDAD frequency percentage cumulative_perc
## 1        NO     43706      84.18           84.18
## 2        SI      8118      15.64           99.82
## 3 SE IGNORA        97       0.19          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    INSRENCR frequency percentage cumulative_perc
## 1        NO     50897      98.03           98.03
## 2        SI       932       1.80           99.83
## 3 SE IGNORA        92       0.18          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    TABAQUIS frequency percentage cumulative_perc
## 1        NO     48985      94.35           94.35
## 2        SI      2827       5.44           99.79
## 3 SE IGNORA       109       0.21          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   RECTRATA frequency percentage cumulative_perc
## 1       NO     47724      91.92           91.92
## 2       SI      3961       7.63           99.55
## 3     <NA>       236       0.45          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   TXCROBIA frequency percentage cumulative_perc
## 1     <NA>     24225      46.66           46.66
## 2       NO     18279      35.21           81.87
## 3       SI      9417      18.14          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   TXANTIVI frequency percentage cumulative_perc
## 1       NO     44617      85.93           85.93
## 2       SI      6020      11.59           97.52
## 3     <NA>      1284       2.47          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##                      ANTIVIRA frequency percentage cumulative_perc
## 1                        <NA>     45896      88.40           88.40
## 2                 OSELTAMIVIR      5828      11.22           99.62
## 3                  AMANTADINA       128       0.25           99.87
## 4                   ZAVAMIVIR        21       0.04           99.91
## 5                  RIMNTADINA         9       0.02           99.93
## 6                AZITROMICINA         5       0.01           99.94
## 7                  RIBAVIRINA         5       0.01           99.95
## 8                 IVERMECTINA         4       0.01           99.96
## 9                  CLOROQUINA         3       0.01           99.97
## 10                 LORATADINA         3       0.01           99.98
## 11                    KALETRA         2       0.00           99.98
## 12                 REMDESIVIR         2       0.00           99.98
## 13                   VIRAZIDE         2       0.00           99.98
## 14                 AMPICILINA         1       0.00           99.98
## 15                 ANTIFLUD D         1       0.00           99.98
## 16               azitromicina         1       0.00           99.98
## 17             CLARITROMICINA         1       0.00           99.98
## 18                 cloroquina         1       0.00           99.98
## 19 cloroquina, azitrominicina         1       0.00           99.98
## 20         INVAZ, FLUCONAZOL,         1       0.00           99.98
## 21                 IVERMECTIN         1       0.00           99.98
## 22               IVERTMENTINA         1       0.00           99.98
## 23              LEVOFLOXACINO         1       0.00           99.98
## 24                 rivabarina         1       0.00           99.98
## 25                VIBRAMICINA         1       0.00           99.98
## 26                         XX         1       0.00          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##   ANTIPIRETICOS frequency percentage cumulative_perc
## 1            SI     28225      54.36           54.36
## 2            NO     23603      45.46           99.82
## 3          <NA>        93       0.18          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##    VACUNADO frequency percentage cumulative_perc
## 1        NO     44097      84.93           84.93
## 2        SI      7700      14.83           99.76
## 3 SE IGNORA        80       0.15           99.91
## 4      <NA>        44       0.08          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##                   TIPO_VAC_COV frequency percentage cumulative_perc
## 1                         <NA>     43344      83.48           83.48
## 2                  AstraZeneca      3329       6.41           89.89
## 3              Pfizer BioNTech      2125       4.09           93.98
## 4                      Sinovac      1992       3.84           97.82
## 5                      CanSino       533       1.03           98.85
## 6                 Se desconoce       243       0.47           99.32
## 7                      Moderna       240       0.46           99.78
## 8  Janssen (Johnson & Johnson)        85       0.16           99.94
## 9                   Sinopharma        26       0.05           99.99
## 10                     Novavax         3       0.01          100.00
## 11                    Gamaleya         1       0.00          100.00

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

##         estatus frequency percentage cumulative_perc
## 1    Sobrevivió     44294      85.31           85.31
## 2 No sobrevivió      7627      14.69          100.00

## [1] "Variables processed: RESDEFIN, CLASCOVID19, SEXO, ESINDIGE, OCUPACIO, TIPACIEN, EVOLUCI, INTUBADO, DIGCLINE, DIAGPROB, FIEBRE, TOS, ODINOGIA, DISNEA, IRRITABI, DIARREA, DOTORACI, CALOFRIOS, CEFALEA, MIALGIAS, ARTRAL, ATAEDOGE, RINORREA, POLIPNEA, VOMITO, DOLABDO, CONJUN, CIANOSIS, INISUBIS, ANOSMIA, DISGEUSIA, ASINTOMATICO, DIABETES, EPOC, ASMA, INMUSUPR, HIPERTEN, VIH.SIDA, OTRACON, ENFCARDI, OBESIDAD, INSRENCR, TABAQUIS, RECTRATA, TXCROBIA, TXANTIVI, ANTIVIRA, ANTIPIRETICOS, VACUNADO, TIPO_VAC_COV, estatus"

TABLA EDA AGRUPADA EN PACIENTES QUE SOBREVIVIERON Y QUE NO SOBREVIVIERON

tabla1covisin<-covidsinfilt %>% select(RESDEFIN,CLASCOVID19,SEXO,EDAD,ESINDIGE,OCUPACIO,TIPACIEN,EVOLUCI,INTUBADO,DIGCLINE,DIAGPROB,FIEBRE:TXANTIVI,ANTIVIRA,
                                     ANTIPIRETICOS,VACUNADO,TIPO_VAC_COV,estatus) %>% tbl_summary(by=estatus) %>% add_p() %>% add_overall()

## There was an error in 'add_p()/add_difference()' for variable 'RESDEFIN', p-value omitted:
## Error in stats::chisq.test(x = c("SARS-CoV-2", "SARS-CoV-2", "SARS-CoV-2", : 'x' and 'y' must have at least 2 levels

## There was an error in 'add_p()/add_difference()' for variable 'CLASCOVID19', p-value omitted:
## Error in stats::chisq.test(x = c("CONF LAB", "CONF LAB", "CONF LAB", "CONF LAB", : 'x' and 'y' must have at least 2 levels

## There was an error in 'add_p()/add_difference()' for variable 'EVOLUCI', p-value omitted:
## Error in stats::fisher.test(c("SEGUIMIENTO TERMINADO", "SEGUIMIENTO TERMINADO", : FEXACT error 6.  LDKEY=295 is too small for this problem,
##   (ii := key2[itp=545] = 333427243, ldstp=8850)
## Try increasing the size of the workspace and possibly 'mult'

## There was an error in 'add_p()/add_difference()' for variable 'ANTIVIRA', p-value omitted:
## Error in stats::fisher.test(c("OSELTAMIVIR", NA, NA, NA, "OSELTAMIVIR", : FEXACT error 7(location). LDSTP=17460 is too small for this problem,
##   (pastp=9.24648, ipn_0:=ipoin[itp=94]=8061, stp[ipn_0]=15.1783).
## Increase workspace or consider using 'simulate.p.value=TRUE'

## There was an error in 'add_p()/add_difference()' for variable 'TIPO_VAC_COV', p-value omitted:
## Error in stats::fisher.test(c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, : FEXACT error 7(location). LDSTP=17040 is too small for this problem,
##   (pastp=65.5472, ipn_0:=ipoin[itp=388]=1331, stp[ipn_0]=91.525).
## Increase workspace or consider using 'simulate.p.value=TRUE'

tabla1covisin

Characteristic	Overall, N = 51,921¹	No sobrevivió, N = 7,627¹	Sobrevivió, N = 44,294¹	p-value²
RESDEFIN
SARS-CoV-2	51,921 (100%)	7,627 (100%)	44,294 (100%)
CLASCOVID19
CONF LAB	51,921 (100%)	7,627 (100%)	44,294 (100%)
SEXO				<0.001
FEMENINO	27,082 (52%)	3,171 (42%)	23,911 (54%)
MASCULINO	24,839 (48%)	4,456 (58%)	20,383 (46%)
EDAD	43 (31, 58)	67 (56, 76)	40 (29, 52)	<0.001
ESINDIGE				0.10
NO	49,789 (100%)	7,232 (100%)	42,557 (100%)
SI	150 (0.3%)	29 (0.4%)	121 (0.3%)
Unknown	1,982	366	1,616
OCUPACIO				<0.001
CAMPESINOS	511 (1.0%)	177 (2.3%)	334 (0.8%)
CHOFERES	383 (0.7%)	74 (1.0%)	309 (0.7%)
COMERCIANTES DE MERCADOS FIJOS O AMBULANTES	707 (1.4%)	128 (1.7%)	579 (1.3%)
DENTISTAS	123 (0.2%)	3 (<0.1%)	120 (0.3%)
DESEMPLEADOS	2,489 (4.8%)	860 (11%)	1,629 (3.7%)
EMPLEADOS	15,861 (31%)	1,003 (13%)	14,858 (34%)
ENFERMERAS	2,852 (5.5%)	16 (0.2%)	2,836 (6.4%)
ESTUDIANTES	2,615 (5.0%)	37 (0.5%)	2,578 (5.8%)
GERENTES O PROPIETARIOS DE EMPRESAS O NEGOCIOS	186 (0.4%)	37 (0.5%)	149 (0.3%)
HOGAR	7,207 (14%)	2,274 (30%)	4,933 (11%)
JUBILADO / PENSIONADO	3,418 (6.6%)	1,769 (23%)	1,649 (3.7%)
LABORATORISTAS	187 (0.4%)	2 (<0.1%)	185 (0.4%)
MAESTROS	1,116 (2.1%)	97 (1.3%)	1,019 (2.3%)
MEDICOS	2,037 (3.9%)	59 (0.8%)	1,978 (4.5%)
OBREROS	316 (0.6%)	66 (0.9%)	250 (0.6%)
OTROS	8,517 (16%)	946 (12%)	7,571 (17%)
OTROS PROFESIONISTAS	1,102 (2.1%)	58 (0.8%)	1,044 (2.4%)
OTROS TRABAJADORES DE LA SALUD	2,294 (4.4%)	21 (0.3%)	2,273 (5.1%)
TIPACIEN				<0.001
AMBULATORIO	36,345 (70%)	51 (0.7%)	36,294 (82%)
HOSPITALIZADO	15,576 (30%)	7,576 (99%)	8,000 (18%)
EVOLUCI
ALTA - CURACION	152 (0.3%)	0 (0%)	152 (0.3%)
ALTA - MEJORIA	6,720 (13%)	0 (0%)	6,720 (15%)
ALTA - TRASLADO	200 (0.4%)	0 (0%)	200 (0.5%)
ALTA - VOLUNTARIA	329 (0.6%)	0 (0%)	329 (0.7%)
CASO GRAVE -	16 (<0.1%)	0 (0%)	16 (<0.1%)
CASO GRAVE - TRASLADO	1 (<0.1%)	0 (0%)	1 (<0.1%)
CASO NO GRAVE	16 (<0.1%)	0 (0%)	16 (<0.1%)
DEFUNCION	7,627 (15%)	7,627 (100%)	0 (0%)
EN TRATAMIENTO	45 (<0.1%)	0 (0%)	45 (0.1%)
REFERENCIA	11 (<0.1%)	0 (0%)	11 (<0.1%)
SEGUIMIENTO DOMICILIARIO	78 (0.2%)	0 (0%)	78 (0.2%)
SEGUIMIENTO TERMINADO	36,726 (71%)	0 (0%)	36,726 (83%)
INTUBADO				<0.001
NO	12,772 (86%)	5,670 (77%)	7,102 (96%)
SI	1,994 (14%)	1,662 (23%)	332 (4.5%)
Unknown	37,155	295	36,860
DIGCLINE				<0.001
NO	40,832 (79%)	1,974 (26%)	38,858 (88%)
SI	11,089 (21%)	5,653 (74%)	5,436 (12%)
DIAGPROB				<0.001
ENFERMEDAD TIPO INFLUENZA (ETI)	37,331 (72%)	69 (0.9%)	37,262 (84%)
INFECCION RESPIRATORIA AGUDA GRAVE (IRAG)	14,590 (28%)	7,558 (99%)	7,032 (16%)
FIEBRE				0.2
NO	13,467 (26%)	1,934 (25%)	11,533 (26%)
SE IGNORA	21 (<0.1%)	5 (<0.1%)	16 (<0.1%)
SI	38,433 (74%)	5,688 (75%)	32,745 (74%)
TOS				0.5
NO	11,253 (22%)	1,643 (22%)	9,610 (22%)
SE IGNORA	17 (<0.1%)	4 (<0.1%)	13 (<0.1%)
SI	40,651 (78%)	5,980 (78%)	34,671 (78%)
ODINOGIA				<0.001
NO	29,052 (56%)	5,395 (71%)	23,657 (53%)
SE IGNORA	107 (0.2%)	18 (0.2%)	89 (0.2%)
SI	22,762 (44%)	2,214 (29%)	20,548 (46%)
DISNEA				<0.001
NO	34,258 (66%)	646 (8.5%)	33,612 (76%)
SE IGNORA	10 (<0.1%)	0 (0%)	10 (<0.1%)
SI	17,653 (34%)	6,981 (92%)	10,672 (24%)
IRRITABI				<0.001
NO	35,195 (68%)	5,393 (71%)	29,802 (67%)
SE IGNORA	38 (<0.1%)	8 (0.1%)	30 (<0.1%)
SI	16,688 (32%)	2,226 (29%)	14,462 (33%)
DIARREA				<0.001
NO	42,489 (82%)	6,031 (79%)	36,458 (82%)
SE IGNORA	37 (<0.1%)	11 (0.1%)	26 (<0.1%)
SI	9,395 (18%)	1,585 (21%)	7,810 (18%)
DOTORACI				<0.001
NO	37,627 (72%)	4,232 (55%)	33,395 (75%)
SE IGNORA	104 (0.2%)	12 (0.2%)	92 (0.2%)
SI	14,190 (27%)	3,383 (44%)	10,807 (24%)
CALOFRIOS				<0.001
NO	35,428 (68%)	5,450 (71%)	29,978 (68%)
SE IGNORA	94 (0.2%)	12 (0.2%)	82 (0.2%)
SI	16,399 (32%)	2,165 (28%)	14,234 (32%)
CEFALEA				<0.001
NO	11,094 (21%)	2,755 (36%)	8,339 (19%)
SE IGNORA	38 (<0.1%)	9 (0.1%)	29 (<0.1%)
SI	40,789 (79%)	4,863 (64%)	35,926 (81%)
MIALGIAS				0.012
NO	20,777 (40%)	2,943 (39%)	17,834 (40%)
SE IGNORA	107 (0.2%)	12 (0.2%)	95 (0.2%)
SI	31,037 (60%)	4,672 (61%)	26,365 (60%)
ARTRAL				<0.001
NO	23,199 (45%)	3,198 (42%)	20,001 (45%)
SE IGNORA	113 (0.2%)	14 (0.2%)	99 (0.2%)
SI	28,609 (55%)	4,415 (58%)	24,194 (55%)
ATAEDOGE				<0.001
NO	29,458 (57%)	2,824 (37%)	26,634 (60%)
SE IGNORA	123 (0.2%)	15 (0.2%)	108 (0.2%)
SI	22,340 (43%)	4,788 (63%)	17,552 (40%)
RINORREA				<0.001
NO	33,149 (64%)	5,826 (76%)	27,323 (62%)
SE IGNORA	123 (0.2%)	18 (0.2%)	105 (0.2%)
SI	18,649 (36%)	1,783 (23%)	16,866 (38%)
POLIPNEA				<0.001
NO	46,594 (90%)	5,437 (71%)	41,157 (93%)
SE IGNORA	133 (0.3%)	14 (0.2%)	119 (0.3%)
SI	5,194 (10%)	2,176 (29%)	3,018 (6.8%)
VOMITO				<0.001
NO	48,088 (93%)	6,881 (90%)	41,207 (93%)
SE IGNORA	138 (0.3%)	19 (0.2%)	119 (0.3%)
SI	3,695 (7.1%)	727 (9.5%)	2,968 (6.7%)
DOLABDO				<0.001
NO	46,229 (89%)	6,558 (86%)	39,671 (90%)
SE IGNORA	147 (0.3%)	20 (0.3%)	127 (0.3%)
SI	5,545 (11%)	1,049 (14%)	4,496 (10%)
CONJUN				<0.001
NO	46,816 (90%)	7,133 (94%)	39,683 (90%)
SE IGNORA	154 (0.3%)	22 (0.3%)	132 (0.3%)
SI	4,951 (9.5%)	472 (6.2%)	4,479 (10%)
CIANOSIS				<0.001
NO	50,714 (98%)	7,124 (93%)	43,590 (98%)
SE IGNORA	149 (0.3%)	21 (0.3%)	128 (0.3%)
SI	1,058 (2.0%)	482 (6.3%)	576 (1.3%)
INISUBIS				<0.001
NO	38,524 (74%)	5,200 (68%)	33,324 (75%)
SE IGNORA	200 (0.4%)	40 (0.5%)	160 (0.4%)
SI	13,197 (25%)	2,387 (31%)	10,810 (24%)
ANOSMIA				<0.001
NO	37,419 (72%)	5,552 (73%)	31,867 (72%)
SE IGNORA	5,720 (11%)	1,195 (16%)	4,525 (10%)
SI	8,782 (17%)	880 (12%)	7,902 (18%)
DISGEUSIA				<0.001
NO	38,385 (74%)	5,636 (74%)	32,749 (74%)
SE IGNORA	5,815 (11%)	1,196 (16%)	4,619 (10%)
SI	7,721 (15%)	795 (10%)	6,926 (16%)
ASINTOMATICO				<0.001
NO	51,391 (99%)	7,620 (100%)	43,771 (99%)
SE IGNORA	34 (<0.1%)	1 (<0.1%)	33 (<0.1%)
SI	496 (1.0%)	6 (<0.1%)	490 (1.1%)
DIABETES				<0.001
NO	44,610 (86%)	4,896 (64%)	39,714 (90%)
SE IGNORA	116 (0.2%)	46 (0.6%)	70 (0.2%)
SI	7,195 (14%)	2,685 (35%)	4,510 (10%)
EPOC				<0.001
NO	51,138 (98%)	7,314 (96%)	43,824 (99%)
SE IGNORA	79 (0.2%)	30 (0.4%)	49 (0.1%)
SI	704 (1.4%)	283 (3.7%)	421 (1.0%)
ASMA				<0.001
NO	50,696 (98%)	7,419 (97%)	43,277 (98%)
SE IGNORA	86 (0.2%)	32 (0.4%)	54 (0.1%)
SI	1,139 (2.2%)	176 (2.3%)	963 (2.2%)
INMUSUPR				<0.001
NO	51,270 (99%)	7,400 (97%)	43,870 (99%)
SE IGNORA	98 (0.2%)	38 (0.5%)	60 (0.1%)
SI	553 (1.1%)	189 (2.5%)	364 (0.8%)
HIPERTEN				<0.001
NO	40,685 (78%)	3,581 (47%)	37,104 (84%)
SE IGNORA	107 (0.2%)	43 (0.6%)	64 (0.1%)
SI	11,129 (21%)	4,003 (52%)	7,126 (16%)
VIH/SIDA				<0.001
NO	51,658 (99%)	7,549 (99%)	44,109 (100%)
SE IGNORA	96 (0.2%)	34 (0.4%)	62 (0.1%)
SI	167 (0.3%)	44 (0.6%)	123 (0.3%)
OTRACON				<0.001
NO	50,306 (97%)	7,169 (94%)	43,137 (97%)
SE IGNORA	126 (0.2%)	41 (0.5%)	85 (0.2%)
SI	1,489 (2.9%)	417 (5.5%)	1,072 (2.4%)
ENFCARDI				<0.001
NO	50,544 (97%)	7,063 (93%)	43,481 (98%)
SE IGNORA	98 (0.2%)	37 (0.5%)	61 (0.1%)
SI	1,279 (2.5%)	527 (6.9%)	752 (1.7%)
OBESIDAD				<0.001
NO	43,706 (84%)	5,793 (76%)	37,913 (86%)
SE IGNORA	97 (0.2%)	38 (0.5%)	59 (0.1%)
SI	8,118 (16%)	1,796 (24%)	6,322 (14%)
INSRENCR				<0.001
NO	50,897 (98%)	7,135 (94%)	43,762 (99%)
SE IGNORA	92 (0.2%)	35 (0.5%)	57 (0.1%)
SI	932 (1.8%)	457 (6.0%)	475 (1.1%)
TABAQUIS				<0.001
NO	48,985 (94%)	6,936 (91%)	42,049 (95%)
SE IGNORA	109 (0.2%)	43 (0.6%)	66 (0.1%)
SI	2,827 (5.4%)	648 (8.5%)	2,179 (4.9%)
RECTRATA				<0.001
NO	47,724 (92%)	6,730 (89%)	40,994 (93%)
SI	3,961 (7.7%)	815 (11%)	3,146 (7.1%)
Unknown	236	82	154
TXCROBIA				<0.001
NO	18,279 (66%)	1,152 (34%)	17,127 (70%)
SI	9,417 (34%)	2,209 (66%)	7,208 (30%)
Unknown	24,225	4,266	19,959
TXANTIVI				<0.001
NO	44,617 (88%)	5,716 (77%)	38,901 (90%)
SI	6,020 (12%)	1,661 (23%)	4,359 (10%)
Unknown	1,284	250	1,034
ANTIVIRA
AMANTADINA	128 (2.1%)	5 (0.3%)	123 (2.8%)
AMPICILINA	1 (<0.1%)	0 (0%)	1 (<0.1%)
ANTIFLUD D	1 (<0.1%)	1 (<0.1%)	0 (0%)
azitromicina	1 (<0.1%)	0 (0%)	1 (<0.1%)
AZITROMICINA	5 (<0.1%)	0 (0%)	5 (0.1%)
CLARITROMICINA	1 (<0.1%)	0 (0%)	1 (<0.1%)
cloroquina	1 (<0.1%)	0 (0%)	1 (<0.1%)
CLOROQUINA	3 (<0.1%)	0 (0%)	3 (<0.1%)
cloroquina, azitrominicina	1 (<0.1%)	0 (0%)	1 (<0.1%)
INVAZ, FLUCONAZOL,	1 (<0.1%)	1 (<0.1%)	0 (0%)
IVERMECTIN	1 (<0.1%)	0 (0%)	1 (<0.1%)
IVERMECTINA	4 (<0.1%)	2 (0.1%)	2 (<0.1%)
IVERTMENTINA	1 (<0.1%)	0 (0%)	1 (<0.1%)
KALETRA	2 (<0.1%)	0 (0%)	2 (<0.1%)
LEVOFLOXACINO	1 (<0.1%)	0 (0%)	1 (<0.1%)
LORATADINA	3 (<0.1%)	0 (0%)	3 (<0.1%)
OSELTAMIVIR	5,828 (97%)	1,643 (99%)	4,185 (96%)
REMDESIVIR	2 (<0.1%)	1 (<0.1%)	1 (<0.1%)
RIBAVIRINA	5 (<0.1%)	3 (0.2%)	2 (<0.1%)
RIMNTADINA	9 (0.1%)	2 (0.1%)	7 (0.2%)
rivabarina	1 (<0.1%)	0 (0%)	1 (<0.1%)
VIBRAMICINA	1 (<0.1%)	0 (0%)	1 (<0.1%)
VIRAZIDE	2 (<0.1%)	0 (0%)	2 (<0.1%)
XX	1 (<0.1%)	0 (0%)	1 (<0.1%)
ZAVAMIVIR	21 (0.3%)	4 (0.2%)	17 (0.4%)
Unknown	45,896	5,965	39,931
ANTIPIRETICOS				<0.001
NO	23,603 (46%)	3,147 (41%)	20,456 (46%)
SI	28,225 (54%)	4,444 (59%)	23,781 (54%)
Unknown	93	36	57
VACUNADO				<0.001
NO	44,097 (85%)	7,003 (92%)	37,094 (84%)
SE IGNORA	80 (0.2%)	23 (0.3%)	57 (0.1%)
SI	7,700 (15%)	590 (7.7%)	7,110 (16%)
Unknown	44	11	33
TIPO_VAC_COV
AstraZeneca	3,329 (39%)	264 (44%)	3,065 (38%)
CanSino	533 (6.2%)	46 (7.7%)	487 (6.1%)
Gamaleya	1 (<0.1%)	1 (0.2%)	0 (0%)
Janssen (Johnson & Johnson)	85 (1.0%)	2 (0.3%)	83 (1.0%)
Moderna	240 (2.8%)	1 (0.2%)	239 (3.0%)
Novavax	3 (<0.1%)	0 (0%)	3 (<0.1%)
Pfizer BioNTech	2,125 (25%)	127 (21%)	1,998 (25%)
Se desconoce	243 (2.8%)	60 (10%)	183 (2.3%)
Sinopharma	26 (0.3%)	4 (0.7%)	22 (0.3%)
Sinovac	1,992 (23%)	93 (16%)	1,899 (24%)
Unknown	43,344	7,029	36,315
¹ n (%); Median (IQR)
² Pearson's Chi-squared test; Wilcoxon rank sum test; Fisher's exact test

#Podemos definir que probabilidad existion a no sobrevivir si los pacientes se encontraban con diferentes condiciones

Utilizando gtsummary

Clinica

library(gtsummary)

clinicm <- coxph(Surv(deftime, evento) ~ SEXO+EDAD+TOS+ODINOGIA+DISNEA+IRRITABI+DIARREA+DOTORACI+CALOFRIOS+CEFALEA+ARTRAL+RINORREA+POLIPNEA+CONJUN+CIANOSIS+INISUBIS+ANOSMIA+DISGEUSIA, data = covidsinfilt)

cm_table <- tbl_regression(clinicm, exponentiate = TRUE) 

cm_table

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
SEXO
FEMENINO	—	—
MASCULINO	1.02	0.97, 1.07	0.4
EDAD	1.01	1.01, 1.01	<0.001
TOS
NO	—	—
SE IGNORA	0.04	0.01, 0.21	<0.001
SI	0.96	0.91, 1.01	0.14
ODINOGIA
NO	—	—
SE IGNORA	0.99	0.43, 2.28	>0.9
SI	0.99	0.94, 1.04	0.7
DISNEA
NO	—	—
SI	1.00	0.92, 1.08	>0.9
IRRITABI
NO	—	—
SE IGNORA	0.52	0.16, 1.71	0.3
SI	1.03	0.98, 1.09	0.3
DIARREA
NO	—	—
SE IGNORA	1.83	0.41, 8.20	0.4
SI	0.97	0.92, 1.03	0.3
DOTORACI
NO	—	—
SE IGNORA	0.74	0.30, 1.87	0.5
SI	1.06	1.01, 1.11	0.020
CALOFRIOS
NO	—	—
SE IGNORA	2.85	0.68, 12.0	0.2
SI	0.99	0.94, 1.05	0.9
CEFALEA
NO	—	—
SE IGNORA	3.70	0.92, 14.8	0.065
SI	0.94	0.90, 0.99	0.019
ARTRAL
NO	—	—
SE IGNORA	0.86	0.39, 1.90	0.7
SI	0.97	0.92, 1.02	0.2
RINORREA
NO	—	—
SE IGNORA	2.37	0.59, 9.51	0.2
SI	0.92	0.87, 0.97	0.003
POLIPNEA
NO	—	—
SE IGNORA	0.72	0.36, 1.42	0.3
SI	1.05	1.00, 1.11	0.053
CONJUN
NO	—	—
SE IGNORA	0.46	0.17, 1.22	0.12
SI	0.97	0.88, 1.07	0.6
CIANOSIS
NO	—	—
SE IGNORA	1.29	0.43, 3.93	0.6
SI	1.08	0.98, 1.19	0.11
INISUBIS
NO	—	—
SE IGNORA	1.07	0.77, 1.47	0.7
SI	1.02	0.97, 1.08	0.3
ANOSMIA
NO	—	—
SE IGNORA	1.14	0.79, 1.64	0.5
SI	0.87	0.79, 0.96	0.005
DISGEUSIA
NO	—	—
SE IGNORA	0.96	0.67, 1.38	0.8
SI	0.92	0.83, 1.02	0.10
¹ HR = Hazard Ratio, CI = Confidence Interval

comorbilidades

#sinfiltro
coxph(Surv(deftime, evento) ~DIABETES+EPOC+ASMA+INMUSUPR+HIPERTEN+ENFCARDI+OBESIDAD+INSRENCR+TABAQUIS+RECTRATA+TXCROBIA+TIPACIEN+VACUNADO, data = covidsinfilt)

## Call:
## coxph(formula = Surv(deftime, evento) ~ DIABETES + EPOC + ASMA + 
##     INMUSUPR + HIPERTEN + ENFCARDI + OBESIDAD + INSRENCR + TABAQUIS + 
##     RECTRATA + TXCROBIA + TIPACIEN + VACUNADO, data = covidsinfilt)
## 
##                            coef exp(coef)  se(coef)      z        p
## DIABETESSE IGNORA      1.146387  3.146804  0.364145  3.148  0.00164
## DIABETESSI             0.095667  1.100393  0.038645  2.476  0.01330
## EPOCSE IGNORA         -1.035340  0.355106  1.033234 -1.002  0.31633
## EPOCSI                 0.241843  1.273594  0.106991  2.260  0.02380
## ASMASE IGNORA         -2.599773  0.074290  1.464112 -1.776  0.07579
## ASMASI                 0.064475  1.066599  0.117929  0.547  0.58457
## INMUSUPRSE IGNORA      0.371861  1.450431  0.610118  0.609  0.54220
## INMUSUPRSI            -0.049718  0.951498  0.115539 -0.430  0.66697
## HIPERTENSE IGNORA      0.389513  1.476262  0.418170  0.931  0.35161
## HIPERTENSI             0.076544  1.079550  0.037282  2.053  0.04006
## ENFCARDISE IGNORA      0.662666  1.939958  0.465427  1.424  0.15451
## ENFCARDISI             0.083379  1.086954  0.072130  1.156  0.24770
## OBESIDADSE IGNORA      0.640214  1.896887  0.415831  1.540  0.12366
## OBESIDADSI            -0.012988  0.987096  0.040758 -0.319  0.74998
## INSRENCRSE IGNORA      1.015707  2.761316  0.579607  1.752  0.07970
## INSRENCRSI             0.356799  1.428749  0.087146  4.094 4.23e-05
## TABAQUISSE IGNORA     -0.117538  0.889107  0.334301 -0.352  0.72514
## TABAQUISSI            -0.087471  0.916245  0.062014 -1.410  0.15839
## RECTRATASI             0.045472  1.046521  0.050894  0.893  0.37161
## TXCROBIASI            -0.087650  0.916081  0.037941 -2.310  0.02088
## TIPACIENHOSPITALIZADO  0.508555  1.662887  0.310109  1.640  0.10102
## VACUNADOSI            -0.002949  0.997055  0.054811 -0.054  0.95709
## 
## Likelihood ratio test=86.7  on 22 df, p=1.24e-09
## n= 3294, number of events= 3294 
##    (48627 observations deleted due to missingness)

comorbcm <- coxph(Surv(deftime, evento) ~DIABETES+EPOC+ASMA+INMUSUPR+HIPERTEN+ENFCARDI+OBESIDAD+INSRENCR+TABAQUIS+RECTRATA+TXCROBIA+TIPACIEN+VACUNADO, data = covidsinfilt)

cm_table <- tbl_regression(comorbcm, exponentiate = TRUE) 

cm_table

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
DIABETES
NO	—	—
SE IGNORA	3.15	1.54, 6.42	0.002
SI	1.10	1.02, 1.19	0.013
EPOC
NO	—	—
SE IGNORA	0.36	0.05, 2.69	0.3
SI	1.27	1.03, 1.57	0.024
ASMA
NO	—	—
SE IGNORA	0.07	0.00, 1.31	0.076
SI	1.07	0.85, 1.34	0.6
INMUSUPR
NO	—	—
SE IGNORA	1.45	0.44, 4.80	0.5
SI	0.95	0.76, 1.19	0.7
HIPERTEN
NO	—	—
SE IGNORA	1.48	0.65, 3.35	0.4
SI	1.08	1.00, 1.16	0.040
ENFCARDI
NO	—	—
SE IGNORA	1.94	0.78, 4.83	0.2
SI	1.09	0.94, 1.25	0.2
OBESIDAD
NO	—	—
SE IGNORA	1.90	0.84, 4.29	0.12
SI	0.99	0.91, 1.07	0.7
INSRENCR
NO	—	—
SE IGNORA	2.76	0.89, 8.60	0.080
SI	1.43	1.20, 1.69	<0.001
TABAQUIS
NO	—	—
SE IGNORA	0.89	0.46, 1.71	0.7
SI	0.92	0.81, 1.03	0.2
RECTRATA
NO	—	—
SI	1.05	0.95, 1.16	0.4
TXCROBIA
NO	—	—
SI	0.92	0.85, 0.99	0.021
TIPACIEN
AMBULATORIO	—	—
HOSPITALIZADO	1.66	0.91, 3.05	0.10
VACUNADO
NO	—	—
SI	1.00	0.90, 1.11	>0.9
¹ HR = Hazard Ratio, CI = Confidence Interval

KM curves and survival analysis

Sexo

library(ggthemes)

sexo<-survfit(Surv(deftime, evento) ~SEXO, data = covidsinfilt)


sexkmplot<-ggsurvplot(sexo, 
  xlab = "Days",
  ylab = "Survival Probability", xlim = c(0, 120),conf.int=T, risk.table = T,
  pval= TRUE, pval.coord = c(100, 0.25),fontsize = 5, break.time.by = 20, legend.title = "Sex", legend.labs = c("Female", "Male"))

sexkmplot

sexhr <- coxph(Surv(deftime, evento) ~SEXO, data = covidsinfilt)

sexhr_table <- tbl_regression(sexhr, exponentiate = TRUE) 

sexhr_table

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
SEXO
FEMENINO	—	—
MASCULINO	1.03	0.98, 1.08	0.2
¹ HR = Hazard Ratio, CI = Confidence Interval

AGE

#stratificar edad

covidsinfilt<-covidsinfilt %>% 
  mutate(
    # para crear las categorias requeridas
    age_group = dplyr::case_when(
      EDAD <= 18            ~ "<18",
      EDAD >= 18 & EDAD <= 40 ~ "18-40",
      EDAD >= 40 & EDAD <= 60 ~ "40-60",
      EDAD >= 60 & EDAD <= 80 ~ "60-80",
      EDAD > 80             ~ ">80"
    ),
    # Convertimos a factor
    age_group = factor(
      age_group,
      level = c("<18","60-80","18-40", "40-60",">80")))


covidsinfilt %>% select(age_group,EDAD,estatus) %>%  tbl_summary(by=estatus) %>% add_p() %>%  add_overall()

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	Overall, N = 51,921¹	No sobrevivió, N = 7,627¹	Sobrevivió, N = 44,294¹	p-value²
age_group				<0.001
<18	2,028 (3.9%)	23 (0.3%)	2,005 (4.5%)
60-80	9,100 (18%)	3,841 (50%)	5,259 (12%)
18-40	21,377 (41%)	457 (6.0%)	20,920 (47%)
40-60	17,461 (34%)	2,157 (28%)	15,304 (35%)
>80	1,955 (3.8%)	1,149 (15%)	806 (1.8%)
EDAD	43 (31, 58)	67 (56, 76)	40 (29, 52)	<0.001
¹ n (%); Median (IQR)
² Pearson's Chi-squared test; Wilcoxon rank sum test

agegr <- survfit(Surv(deftime, evento) ~age_group, data = covidsinfilt)

tbl_survfit(
  covidsinfilt, y = Surv(deftime, evento),
  include = c(age_group),
  probs = 0.5,
  label_header = "**Median Survival**"
  ) %>% 
  add_p()

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	Median Survival	p-value¹
age_group		<0.001
<18	8.0 (5.0, 18)
60-80	14 (14, 15)
18-40	15 (15, 17)
40-60	15 (15, 16)
>80	12 (11, 12)
¹ Log-rank test

agegrkmplot<-ggsurvplot(agegr, 
  xlab = "Days",
  ylab = "Survival Probability", xlim = c(0, 120),conf.int=T, risk.table = T,
  pval= TRUE, pval.coord = c(100, 0.25),fontsize = 5, break.time.by = 20, legend.title = "Age Group")

agegrkmplot

agestrat<-covidsinfilt %>% filter(age_group == "<18" | age_group == "60-80") 

agestrata<- survfit(Surv(deftime, evento) ~ age_group, data = agestrat)

ggsurvplot(agestrata, 
  xlab = "Days",
  ylab = "Survival Probability", xlim = c(0, 120), conf.int=T, risk.table = T,
  pval= TRUE, pval.coord = c(100, 0.25),fontsize = 5, break.time.by = 20, legend.title = "Age Group")

agerh <- coxph(Surv(deftime, evento) ~age_group, data = agestrat)

tbl_regression(agerh, exponentiate = TRUE)

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
age_group
<18	—	—
60-80	0.63	0.42, 0.95	0.028
18-40
40-60
>80
¹ HR = Hazard Ratio, CI = Confidence Interval

TIPO DE PACIENTE

#TIPO DE PACIENTE
 
tippax <- survfit(Surv(deftime, evento) ~ TIPACIEN, data = covidsinfilt)

tbl_survfit(
  covidsinfilt, y = Surv(deftime, evento),
  include = c(TIPACIEN),
  probs = 0.5,
  label_header = "**Median Survival**"
  ) %>% add_p()

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	Median Survival	p-value¹
TIPACIEN		0.001
AMBULATORIO	16 (12, 22)
HOSPITALIZADO	14 (14, 15)
¹ Log-rank test

tippaxkmplot<-ggsurvplot(tippax, 
  xlab = "Days",
  ylab = "Survival Probability", xlim = c(0, 120),conf.int=T, risk.table = T,
  pval= TRUE, pval.coord = c(100, 0.25),fontsize = 5, break.time.by = 20, legend.title = "Patient:",
  legend.labs = c("Outpatient", "Hospitalized"))

tippaxkmplot

tippaxcox <- coxph(Surv(deftime, evento) ~TIPACIEN, data = agestrat)

tbl_regression(tippaxcox, exponentiate = TRUE)

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
TIPACIEN
AMBULATORIO	—	—
HOSPITALIZADO	1.28	0.84, 1.95	0.2
¹ HR = Hazard Ratio, CI = Confidence Interval

Intubated

#INTUBADO

intub <- survfit(Surv(deftime, evento) ~INTUBADO, data = covidsinfilt)

tbl_survfit(
  covidsinfilt, y = Surv(deftime, evento),
  include = c(INTUBADO),
  probs = 0.5,
  label_header = "**Median Survival**"
  ) %>% 
  add_p()

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	Median Survival	p-value¹
INTUBADO		<0.001
NO	14 (14, 14)
SI	16 (15, 16)
¹ Log-rank test

intubkmplot<-ggsurvplot(intub, 
  xlab = "Days",
  ylab = "Survival Probability", xlim = c(0, 120),conf.int=T, risk.table = T,
  pval= TRUE, pval.coord = c(100, 0.25),fontsize = 5, break.time.by = 20, legend.title = "Intubated:",
  legend.labs = c("Not", "Yes"))

intubkmplot

intubcox <- coxph(Surv(deftime, evento) ~INTUBADO, data = agestrat)

tbl_regression(intubcox, exponentiate = TRUE)

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
INTUBADO
NO	—	—
SI	0.88	0.81, 0.95	<0.001
¹ HR = Hazard Ratio, CI = Confidence Interval

DIAGNOSTICO PROBABLE (SEVERIDAD)

#DIAGPROB


sev <- survfit(Surv(deftime, evento) ~DIAGPROB, data = covidsinfilt)

tbl_survfit(
  covidsinfilt, y = Surv(deftime, evento),
  include = c(DIAGPROB),
  probs = 0.5,
  label_header = "**Median Survival**"
  ) %>% 
  add_p()

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	Median Survival	p-value¹
DIAGPROB		0.008
ENFERMEDAD TIPO INFLUENZA (ETI)	14 (12, 19)
INFECCION RESPIRATORIA AGUDA GRAVE (IRAG)	14 (14, 15)
¹ Log-rank test

sevkmplot<-ggsurvplot(sev, 
  xlab = "Days",
  ylab = "Survival Probability", xlim = c(0, 120),conf.int=T, risk.table = T,
  pval= TRUE, pval.coord = c(100, 0.25),fontsize = 5, break.time.by = 20, legend.title = "Severity",
  legend.labs = c("ETI", "SARI"))

sevkmplot

clasicox <- coxph(Surv(deftime, evento) ~DIAGPROB, data = agestrat)

tbl_regression(clasicox, exponentiate = TRUE)

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
DIAGPROB
ENFERMEDAD TIPO INFLUENZA (ETI)	—	—
INFECCION RESPIRATORIA AGUDA GRAVE (IRAG)	1.26	0.89, 1.77	0.2
¹ HR = Hazard Ratio, CI = Confidence Interval

COX-REGRESSION ANALISIS WITH CLINIC AND MORTALITY COVID-19

library(survminer)
library(survival)

covidsincox <-covidsinfilt %>% filter(if_all(c(SEXO, TIPACIEN, INTUBADO, DIAGPROB), ~ .x != "SE IGNORA"))

DEMO <- coxph(Surv(deftime, evento) ~ SEXO +  INTUBADO + DIAGPROB , data = covidsincox)

cm_table <- tbl_regression(DEMO, exponentiate = TRUE) 

cm_table

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead

Characteristic	HR¹	95% CI¹	p-value
SEXO
FEMENINO	—	—
MASCULINO	1.03	0.99, 1.08	0.15
INTUBADO
NO	—	—
SI	0.89	0.84, 0.94	<0.001
DIAGPROB
ENFERMEDAD TIPO INFLUENZA (ETI)	—	—
INFECCION RESPIRATORIA AGUDA GRAVE (IRAG)	0.88	0.55, 1.40	0.6
¹ HR = Hazard Ratio, CI = Confidence Interval

library(forestmodel)


print(forest_model(coxph(Surv(deftime, evento) ~ SEXO +  INTUBADO + DIAGPROB , data = covidsincox)))

## Warning in recalculate_width_panels(panel_positions, mapped_text =
## mapped_text, : Unable to resize forest panel to be smaller than its heading;
## consider a smaller text size

Análisis COVID-Sinaloa

MDatos

2022-12-21

TOTAL DE CASOS CONFIRMADOS Y POSITIVOS A SARS-CoV-2 de enero 2020 a diciembre 2022

CURVA EPIDEMIOLOGICA

ANALISIS DE SUPERVIVENCIA

PREPARACIÓN DE LOS DATO: LIMPIEZA, FILTRADO

ANALISIS DE FRECUENCIAS OVERALL VARIABLES

TABLA EDA AGRUPADA EN PACIENTES QUE SOBREVIVIERON Y QUE NO SOBREVIVIERON

Utilizando gtsummary

Clinica

comorbilidades

KM curves and survival analysis

Sexo

AGE

TIPO DE PACIENTE

Intubated

DIAGNOSTICO PROBABLE (SEVERIDAD)

COX-REGRESSION ANALISIS WITH CLINIC AND MORTALITY COVID-19