If possible provide minimum reproducible example. I would suggest you to explore R tidyModels. Probably function broom::tidy() could solve your problem. See the example below where I used model created by lm() function and later get model details using broom::tidy()

library(tidyverse)
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)


lm.D9 %>% broom::tidy()
#> # A tibble: 2 x 5
#>   term        estimate std.error statistic  p.value
#>   <chr>          <dbl>     <dbl>     <dbl>    <dbl>
#> 1 (Intercept)    5.03      0.220     22.9  9.55e-15
#> 2 groupTrt      -0.371     0.311     -1.19 2.49e- 1

^{Created on 2020-03-25 by the reprex package (v0.3.0)}