gtsummary : global pvalue on imputed dataset

Question

I'm trying to perform a logistic regression on imputed data, but I can't get the global p-values. When I try it on the dataset without imputation, it works, but as soon as it's on imputed data, it doesn't work anymore.

Does someone know if there's a way to calculate and display them in gtsummary?

For example, with random variables :

library(tidyverse)
library(gtsummary)
library(mice)

n <- 500

set.seed(123)

data <- data.frame(
  rep_2cl = factor(sample(0:1, n, replace = TRUE)),
  Age = sample(18:62, n, replace = TRUE),
  Diplome = factor(sample(c("1", "2", "3", "4", NA), n, replace = TRUE)),
  Study = factor(sample(c("0", "1", NA), n, replace = TRUE)),
  Alone = factor(sample(c("0", "1", NA), n, replace = TRUE)),
  Special = factor(sample(c("1", "2", "3"), n, replace = TRUE)),
  Contract = factor(sample(c("1", "2", "3", NA), n, replace = TRUE)),
  Durr = factor(sample(c("1", "2", NA), n, replace = TRUE)),
  Vax = factor(sample(c("0", "1", NA), n, replace = TRUE)))

data.i <- mice(data, 
            m = 5, 
            seed = 123, 
            print = FALSE)

# non imputed data
fit <- glm(formula = rep_2cl ~ Age + Diplome + Study + Alone + Special + Contract + Durr + Vax,
           family = binomial,
           data)
tbl_regression(fit, exponentiate = T) |> add_global_p()

# imputed data
fit.i <- with(data.i, 
            glm(formula = rep_2cl ~ Age + Diplome + Study + Alone + Special + Contract + Durr + Vax, 
                family = binomial))
tbl_regression(fit.i, exponentiate = T) |> add_global_p() 

thank you