filter rows by condition and add n rows before/after selected row

Question

I have a grouped data and I want to select a rows that fulfill a certain condition (works with code provided below), but I also want to add n number of rows before or after that. The code below give me two rows per group and I now for example want to add one row that is before the first row and one row that is after the second row. I could not find a code or function "like add one row", so is there anyway that I can include this in the following code?

daf1 <- df %>% 
  setDT(df) %>% 
  dplyr::mutate(row_id = row_number()) %>% 
  dplyr::group_by(PATIENT.ID) %>% 
  dplyr::mutate(first_yes = cumsum(Caffeinefactor == "yes"), 
         last_no = (Caffeinefactor == "no") * row_number(), 
         last_no = ifelse(first_yes == 0, last_no, 0)) %>% 
  dplyr:: filter((first_yes == 1 & Caffeine >0) | last_no == max(last_no)) %>%
  dplyr::select(-first_yes, -last_no)

DF = structure(list(PATIENT.ID = c(210625L, 210625L, 210625L, 210625L, 
210625L, 210625L, 210625L, 210625L, 210625L, 210625L, 210625L, 
210625L, 210625L, 210625L, 210625L, 210625L, 210625L, 220909L, 
220909L, 220909L, 220909L, 220909L, 220909L, 220909L, 220909L, 
220909L, 220909L, 221179L, 221179L, 221179L, 221179L, 221179L, 
221179L, 221179L, 221179L, 221179L, 221179L, 221179L, 221179L, 
221179L, 221179L, 301705L, 301705L, 301705L, 301705L, 301705L, 
301705L, 301705L, 301705L, 301705L, 301705L, 301705L, 301705L, 
301705L, 301705L, 301705L, 303926L, 303926L, 303926L, 303926L
), PATIENT.TREATMENT.NUMBER = c(1L, 2L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 1L, 2L, 3L, 4L, 
5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 13L, 17L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 12L, 13L, 14L, 15L, 16L, 1L, 2L, 3L, 4L), Caffeinefactor = c("no", 
"no", "no", "no", "yes", "yes", "yes", "no", "yes", "yes", "yes", 
"yes", "yes", "no", "no", "yes", "yes", "yes", "no", "yes", 
"yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", 
"no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", 
"yes", "no", "no", "no", "no", "no", "no", "yes", "no", "yes", 
"yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no"
)), row.names = c(NA, -60L), class = c("data.table", "data.frame"
), .internal.selfref = <pointer: 0x7fe7f7002ee0>)

What the output looks like now:

PATIENT.ID	Caffeinefactor header
210625L	no
210625L	yes
220909L	no
220909L	yes
301705L	no
301705L	yes

The output should look like this if one row is added before and after:

PATIENT.ID	Caffeinefactor header
210625L	no
210625L	no
210625L	yes
210625L	yes
220909L	no
220909L	yes
220909L	yes
301705L	no
301705L	no
301705L	yes
301705L	yes

EDIT:

The original dataset has more that 90 columns and I also need to keep the values in these column. I do not want to duplicate the rows that the shown code selected.

To get to the out I have I changed my Data before with the following code:

groups <- Data2 %>%
  setDT(Data2) %>%
  dplyr::group_by(PATIENT.ID)

groups_we_want_removed <- Data2 %>%
  setDT(Data2) %>%
  dplyr::group_by(PATIENT.ID) %>%
  dplyr::mutate(rownum = dplyr::row_number()) %>%
  dplyr::filter((rownum == 1 & Caffeinefactor == "yes"))

remove_people_with_only_no_caffeinefactor <- Data2 %>%
  setDT(Data2) %>%
  dplyr::group_by(PATIENT.ID) %>%
  dplyr::filter(Caffeinefactor == "yes")

desired_result <- groups %>%
  filter(!PATIENT.ID %in% groups_we_want_removed$PATIENT.ID) %>%
  filter(PATIENT.ID %in% remove_people_with_only_no_caffeinefactor$PATIENT.ID)

EDIT 2:

I know how I can theoretically select it. With this code it:

desired_result[which(desired_result$Caffeinefactor == "yes") + c(-1:1), ]

However, I need this code to be implemented after I matched for the two rows that I want, like in int he first code