Dr. Pineda 29_05

TABLA 1

library(readxl)
BASE <- read_excel("Base de datos Hernia oculta pirosis vs nerd (1).xlsx")
library(dplyr)
#names(BASE)
BASE <- BASE |> select(Sexo:`Diagnóstico manometría`)

library(stringr)
BASE$`Diagnostico pH (es el diagnóstico de comparación)` <- str_to_title(BASE$`Diagnostico pH (es el diagnóstico de comparación)`)
BASE$`RESERVA CONTRACTIL` <- str_to_title(BASE$`RESERVA CONTRACTIL`)
BASE$`RESERVA CONTRACTIL` <- case_when(
  BASE$`RESERVA CONTRACTIL`%in% c("adecuado", "adecuada", "Adecuado", "Adecuada") ~ "Adecuado",
  BASE$`RESERVA CONTRACTIL` %in% c("inadecuado", "inadecuada", "Inadecuado", "Inadecuada", "Inadecauda") ~ "Inadecuado",
  TRUE ~ BASE$`RESERVA CONTRACTIL`
)

library(gtsummary)

#cat(names(BASE), sep = ",")
tabla1 <- BASE %>%
  select(Sexo,Edad,`IMC kg/m2`,Diabetes,HTA,`Tiempo de exposición ácida % (PH)`,`N de eventos de reflujo`, `Diagnostico pH (es el diagnóstico de comparación)`,`Impedancia del segmento contractil distal Ohms`,`Integral contractil mmHg/cm`,`DCI mmHg/cm/seg`,`ACLARAMIENTO ESOFAGICO`,`PRESION EII`, `RESERVA CONTRACTIL`, `HERNIA OCULTA`,`Diagnóstico manometría`) %>%
  tbl_summary(
    by = `Diagnostico pH (es el diagnóstico de comparación)`,
    type = list(
      all_continuous()                    ~ "continuous2",
      c(Sexo, Diabetes, HTA, `RESERVA CONTRACTIL`, `HERNIA OCULTA`,`Diagnóstico manometría`)            ~ "categorical"
    ),
    label = list(
      Sexo ~ "Sexo",
      Edad ~ "Edad",
      `IMC kg/m2` ~ "IMC kg/m2",
      Diabetes ~ "Diabetes",
      HTA ~ "HTA",
      `Tiempo de exposición ácida % (PH)` ~ "Tiempo exposición ácida% (PH)",
      `N de eventos de reflujo` ~ "Eventos de reflujo", 
      `Impedancia del segmento contractil distal Ohms` ~"Impedancia segmento contractil distal (OHMS)",
      `Integral contractil mmHg/cm` ~ "Integral contractil (mmHg/cm)",
      `DCI mmHg/cm/seg` ~ "DCI mmHg/CM/SEG",
      `ACLARAMIENTO ESOFAGICO` ~ "Aclaramiento esofágico",
      `PRESION EII` ~ "Presión EEI", 
      `RESERVA CONTRACTIL` ~ "Reserva Contractil", 
      `HERNIA OCULTA` ~ "Hernia Oculta",
      `Diagnóstico manometría` ~ "Diagnóstico manometría"
    ),
    statistic = list(
      all_continuous2()  ~ c(
        "{mean} ({sd})",
        "{median} ({p25}, {p75})",
        "{min} - {max}"
      ),
      all_categorical() ~ "{n} ({p}%)"
    ),
    digits = list(
      all_continuous()  ~ 2,
      all_categorical() ~ 1
    ),
    missing = "ifany",
    missing_text = "Sin dato"
  ) %>%
  add_p(
    test = list(
      all_continuous2()  ~ "kruskal.test",  
      all_categorical() ~ "chisq.test"
    ),
    pvalue_fun = ~ style_pvalue(.x, digits = 3)
  ) %>%
  add_overall() %>%
  modify_header(label ~ "**Variable**") %>%
  bold_labels() %>%
  bold_p(t = 0.05) %>%
  modify_caption("**Tabla 1**")

tabla1

**Tabla 1**
Variable	Overall N = 94¹	Nerd N = 43¹	Pirosis Funcional N = 51¹
Sexo
Femenino	59.0 (64.1%)	27.0 (62.8%)	32.0 (65.3%)
Masculino	33.0 (35.9%)	16.0 (37.2%)	17.0 (34.7%)
Sin dato	2	0	2
Edad
Mean (SD)	56.08 (14.40)	55.67 (15.02)	56.42 (13.99)
Median (Q1, Q3)	57.00 (45.00, 68.00)	57.00 (43.00, 69.00)	55.50 (45.00, 67.00)
Min - Max	26.00 - 82.00	26.00 - 81.00	32.00 - 82.00
Sin dato	1	0	1
IMC kg/m2
Mean (SD)	24.41 (3.41)	23.57 (3.38)	25.11 (3.32)
Median (Q1, Q3)	24.48 (21.50, 25.88)	23.40 (20.40, 25.30)	24.86 (22.76, 27.24)
Min - Max	18.38 - 32.79	19.30 - 30.80	18.38 - 32.79
Diabetes
0	67.0 (71.3%)	20.0 (46.5%)	47.0 (92.2%)
1	27.0 (28.7%)	23.0 (53.5%)	4.0 (7.8%)
HTA
0	73.0 (77.7%)	29.0 (67.4%)	44.0 (86.3%)
1	21.0 (22.3%)	14.0 (32.6%)	7.0 (13.7%)
Tiempo exposición ácida% (PH)
Mean (SD)	495.16 (4,756.76)	1,080.80 (7,032.42)	1.38 (1.19)
Median (Q1, Q3)	3.20 (1.20, 7.30)	7.50 (6.50, 9.10)	1.20 (0.40, 2.10)
Min - Max	0.00 - 46,123.00	6.00 - 46,123.00	0.00 - 5.40
Eventos de reflujo
Mean (SD)	48.60 (33.96)	64.02 (39.74)	35.59 (21.00)
Median (Q1, Q3)	39.00 (23.00, 65.00)	58.00 (37.00, 87.00)	31.00 (20.00, 51.00)
Min - Max	1.00 - 185.00	15.00 - 185.00	1.00 - 82.00
Impedancia segmento contractil distal (OHMS)
Mean (SD)	2,198.41 (588.20)	1,622.21 (295.16)	2,684.24 (209.91)
Median (Q1, Q3)	2,398.50 (1,534.00, 2,734.00)	1,532.00 (1,467.00, 1,615.00)	2,678.00 (2,546.00, 2,789.00)
Min - Max	1,230.00 - 3,200.00	1,230.00 - 2,578.00	2,156.00 - 3,200.00
Integral contractil (mmHg/cm)
Mean (SD)	34.64 (7.83)	32.61 (9.27)	36.35 (5.95)
Median (Q1, Q3)	33.45 (29.70, 37.90)	30.20 (27.30, 35.60)	35.20 (32.40, 41.10)
Min - Max	20.50 - 67.80	20.50 - 67.80	24.80 - 48.70
DCI mmHg/CM/SEG
Mean (SD)	1,666.80 (1,435.33)	1,129.58 (869.53)	2,119.75 (1,655.10)
Median (Q1, Q3)	1,338.50 (668.00, 1,998.00)	983.00 (516.00, 1,651.00)	1,654.00 (948.00, 2,864.00)
Min - Max	0.00 - 7,004.00	0.00 - 3,555.00	150.00 - 7,004.00
Aclaramiento esofágico
Mean (SD)	67.23 (35.12)	60.70 (38.13)	72.75 (31.69)
Median (Q1, Q3)	80.00 (40.00, 100.00)	70.00 (30.00, 100.00)	80.00 (60.00, 100.00)
Min - Max	0.00 - 100.00	0.00 - 100.00	0.00 - 100.00
Presión EEI
Mean (SD)	22.33 (11.36)	20.57 (11.16)	23.81 (11.42)
Median (Q1, Q3)	20.35 (14.70, 29.90)	18.90 (11.40, 29.90)	20.70 (17.10, 31.00)
Min - Max	1.30 - 61.70	2.10 - 42.80	1.30 - 61.70
Reserva Contractil
Adecuado	53.0 (56.4%)	25.0 (58.1%)	28.0 (54.9%)
Inadecuado	41.0 (43.6%)	18.0 (41.9%)	23.0 (45.1%)
Hernia Oculta
no	74.0 (78.7%)	38.0 (88.4%)	36.0 (70.6%)
si	20.0 (21.3%)	5.0 (11.6%)	15.0 (29.4%)
Diagnóstico manometría
Contractilidad ausente	3.0 (3.2%)	3.0 (7.0%)	0.0 (0.0%)
Hipercontractil	2.0 (2.1%)	0.0 (0.0%)	2.0 (3.9%)
MEI	12.0 (12.8%)	6.0 (14.0%)	6.0 (11.8%)
No conclusivo para MEI	1.0 (1.1%)	1.0 (2.3%)	0.0 (0.0%)
No conclusivo para OTS	3.0 (3.2%)	2.0 (4.7%)	1.0 (2.0%)
Normal	72.0 (76.6%)	31.0 (72.1%)	41.0 (80.4%)
OTS	1.0 (1.1%)	0.0 (0.0%)	1.0 (2.0%)
¹ n (%)

library(flextable)
tabla1 %>%
  as_flex_table() %>%
  save_as_docx(path = "tabla1.1.docx")

library(tableone)
library(openxlsx)
library(tibble)
library(reactable)

myVars <- c("Sexo", "Edad", "IMC kg/m2", "Diabetes", "HTA",
            "Tiempo de exposición ácida % (PH)",
            "N de eventos de reflujo",
            "Impedancia del segmento contractil distal Ohms",
            "Integral contractil mmHg/cm",
            "DCI mmHg/cm/seg",
            "ACLARAMIENTO ESOFAGICO",
            "PRESION EII",
            "RESERVA CONTRACTIL",
            "HERNIA OCULTA",
            "Diagnóstico manometría")

catVars <- c("Sexo", "Diabetes", "HTA",
             "RESERVA CONTRACTIL",
             "HERNIA OCULTA",
             "Diagnóstico manometría")

tab <- CreateTableOne(
  vars    = myVars,
  strata  = "Diagnostico pH (es el diagnóstico de comparación)",
  factorVars = catVars,
  data    = BASE,
  includeNA  = FALSE,
  addOverall = TRUE,
  testNonNormal = TRUE
)

tableone <- as.data.frame(print(tab, 
                               showAllLevels = TRUE, 
                               printToggle   = FALSE, 
                               noSpaces      = TRUE))

# Renombrar filas para que se vean bonito
nombres_bonitos <- c(
  "Sexo",
  "Edad (años)",
  "IMC (kg/m²)",
  "Diabetes",
  "HTA",
  "Tiempo exposición ácida % (pH)",
  "N° eventos de reflujo",
  "Impedancia segmento contractil distal (Ω)",
  "Integral contractil (mmHg/cm)",
  "DCI (mmHg/cm/seg)",
  "Aclaramiento esofágico",
  "Presión EEI",
  "Reserva contractil",
  "Hernia oculta",
  "Diagnóstico manometría"
)

# Solo renombra las filas que corresponden a variables principales
# (tableone agrega filas extra por niveles de factores)
limpiar_nombres <- function(nombres) {
  nombres %>%
    gsub("\\(X.*?\\)", "", .) %>%
    gsub("X", "", .)           %>%
    gsub("\\.{1,}", " ", .)    %>%
    gsub("\\s+", " ", .)       %>%
    trimws(.)
}

rownames(tableone) <- limpiar_nombres(rownames(tableone))

# Exportar a Excel
write.xlsx(tableone, "tabla1.xlsx", rowNames = TRUE, colNames = TRUE)

# Tabla reactable
tabla_reactable <- tableone %>%
  rownames_to_column("Variable") %>%
  reactable(
    pagination       = FALSE,
    defaultPageSize  = nrow(tableone),
    columns = list(
      Variable = colDef(
        style     = list(backgroundColor = "#2C3E50", color = "white", fontWeight = "bold"),
        width     = 250,
        align     = "left"
      )
    ),
    theme = reactableTheme(
      headerStyle = list(
        backgroundColor = "#34495E",
        color           = "white",
        fontWeight      = "bold",
        fontSize        = "13px"
      ),
      cellStyle   = list(fontSize = "11px"),
      stripedColor = "#F8F9FA"
    ),
    striped    = TRUE,
    highlight  = TRUE,
    bordered   = TRUE,
    compact    = TRUE,
    wrap       = FALSE,
    resizable  = TRUE
  )

tabla_reactable

library(flextable)

tableone %>%
  rownames_to_column("Variable") %>%
  flextable() %>%
  bold(part = "header") %>%
  bold(j = 1) %>%
  bg(part = "header", bg = "#2C3E50") %>%
  color(part = "header", color = "white") %>%
  bg(i = seq(2, nrow(tableone), 2), bg = "#F8F9FA") %>%  # filas alternas
  autofit() %>%
  set_caption("Tabla 1. Características de la muestra según diagnóstico pH") %>%
  save_as_docx(path = "tabla1.docx")

Dr. Pineda 29_05_2026

NMR

2026-05-29

TABLA 1