#' Get an individual standard table for AHSQC
#'
#' Retrieves the code for the standard AHSQC table specified and returns it in either
#' a separate file or through a text string.
#' @param tbl NULL or integer 1-9 to identify which table to return.
#' @param data a data table
#' @param print a boolean. If TRUE, the code for specified table will be returned
#' in a tet string. If FALSE, the code for specified table will be written to a
#' separate .R file in the working directory with \code{tbl}n\code{.R} nomenclature.
#' @param overwrite a boolean. If a .R file already exists for the table specified and set to TRUE, the file will be overwritten with original code.
#' @param pval a boolean. Set to TRUE if pvalues are desired for table.
#' @details If \code{overwrite} = FALSE and a .R file exists for the specified table, the function will throw an error.
#'
#'If \code{print} = TRUE, the \code{overwrite} argument will be ignored.
#'
#' @keywords AHSQC
#' @export
#' @examples
#' # Not run:
#' # d0 <- ahs_get_data()
#' # d1 <- d0[["analyticview]]
#' # get_table(tbl = 1, d1, print = TRUE) ## will print code as text
#' # get_table(tbl = 9, d1, print = FALSE) ## will write tbl9.R
#' # get_table(tbl = 9, d1, print = FALSE, overwrite = TRUE) ## will overwrite tbl9.R
get_standard_table <- function(tbl = NULL
, data
, print = FALSE
, overwrite = FALSE
, pval = FALSE){
if(is.character(data)) stop("data should be a data table, not a character string")
if(is.null(tbl)) return(message("tbl is NULL"))
dt <- deparse(substitute(data))
table_list <- list(
"tbl1 <- list() %>%
n_unique(patientid, xlab = \"N\") %>%
cat_entry(e_procedure_category
, pvalue = FALSE
, xlab = \"Procedure category\"
) %>%
cat_entry(recurrent %>% factor(levels = c(\"Primary\", \"Recurrent\"))
, pvalue = FALSE
, xlab = \"Primary or recurrent hernia\") %>%
cat_entry(
prior_repairs
, xlab = \"Number of prior repairs\"
, dt = data %>% filter(recurrent == \"Recurrent\")
, pvalue = FALSE
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Cohort volume and prior repairs\")"
, "tbl2 <- list() %>%
n_unique(id_surgeon
, xlab = \"Surgeons contributing data\") %>%
n_unique(id_site
, xlab = \"Sites contributing data\") %>%
cat_entry(
e_surg_affiliation
, xlab = \"Primary surgeon affiliation\"
, pvalue = FALSE
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Surgeon and site volume\")"
, "tbl3 <- list() %>%
cont_entry(val_age_new
, xlab = \"Age (years; capped at 90)\"
, pvalue = FALSE) %>%
binary_entry(female
, pvalue = FALSE
, xlab = \"Female\") %>%
cat_entry(e_race
, pvalue = FALSE
, xlab = \"Race\") %>%
cont_entry(val_calc_bmi2
, xlab = \"BMI (kg/m<sup>2</sup>; capped at 15, 60)\"
, pvalue = FALSE) %>%
cat_entry(bmi_cat %>% factor(levels = c(\"< 30\", \">= 30\"))
, xlab = \"BMI categories\"
, pvalue = FALSE) %>%
cat_entry(e_asaclass
, xlab = \"ASA class\"
, pvalue = FALSE) %>%
cat_entry(wound_class
, xlab = \"Wound class distribution\"
, pvalue = FALSE) %>%
cat_entry(vhwg
, xlab = \"Hernia Grade (VHWG)\"
, pvalue = FALSE) %>%
cont_entry(val_hern_width
, xlab = \"Hernia width (cm)\"
, pvalue = FALSE) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Demographics\")"
, "tbl4 <- list() %>%
binary_entry(any_comorbidities %>% factor(levels = c(0,1))
, xlab = \"Prevalence of comorbidities\"
, pvalue = FALSE
) %>%
empty_entry(fill = c(\"Comorbidities\",\"N\")) %>%
binary_entry(
flg_cmb_steroids %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Immunosuppressant\"
, fmt = count_fmt
) %>%
binary_entry(
smoking_one_year %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Smoking (within 1 year)\"
, fmt = count_fmt
) %>%
binary_entry(
nicotine_one_year %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Nicotine use (within 1 year)\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_hypertension %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Hypertension\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_diabetes %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Diabetes mellitus\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_dyspnea %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Dyspnea\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_copd %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@COPD\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_abdominal_wall_ssi_hx %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@History of abdominal wall surgical site infection\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_component_separation_hx %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@History of component separation\"
, fmt = count_fmt
) %>%
binary_entry(
flg_cmb_open_abdomen_hx %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@History of open abdomen\"
, fmt = count_fmt
) %>%
binary_entry(
current_steroids %>% factor(levels = c(0,1))
, xlab = \"@@Current steroid use\"
, fmt = count_fmt
) %>%
cat_entry(e_prior_mesh_excision %>% factor(levels = c(\"Complete\", \"Partial\", \"None\"))
, xlab = \"Prior mesh excision\"
, pvalue = FALSE
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Comorbidities\")"
, "tbl5 <- list() %>%
cat_entry(operative_time
, pvalue_fmt = garbage_pvalue
, pvalue = FALSE
, xlab = \"Operative time\") %>%
binary_entry(planned_concomitant_procedure %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Planned concomitant procedure\"
, pvalue = FALSE) %>%
binary_entry(flg_concomitant_proc %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Any concomitant procedure\"
, pvalue = FALSE) %>%
empty_entry(
fill = c(
\"Concomitant procedures<sup>cata</sup>\",
\"N\")
) %>%
binary_entry(
array_other_procedures_system_hernia %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Hernia\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_foregutendocrine %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Foregut/Endocrine\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_hepatobiliarypancreatic %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Hepatobiliary/Pancreatic\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_small_intestine %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Small intestine\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_colorectal %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Colorectal\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_obstetricgynecologic %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Obstetric/Gynecologic\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_urologic %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Urologic\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_vascular %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Vascular\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(
array_other_procedures_system_soft_tissueplastics %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Soft tissue/plastics\"
, dt = data %>% dplyr:::filter(flg_concomitant_proc == \"Yes\")
, fmt = count_fmt
, pvalue = FALSE
) %>%
binary_entry(flg_fascial_closure %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Fascial closure\"
, pvalue = FALSE
) %>%
binary_entry(flg_myofascial_release %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Myofascial release\"
, pvalue = FALSE
) %>%
binary_entry(flg_mesh_used %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Mesh used\"
, pvalue = FALSE) %>%
cat_entry(e_mesh_type4_1 %>% factor(levels = c(\"Permanent Synthetic\", \"Resorbable Synthetic\", \"Biological tissue-derived\", \"Other/Unknown\"))
, xlab = \"Mesh type (4)\"
, pvalue = FALSE
, dt = data %>% dplyr::filter(flg_mesh_used == \"Yes\")
) %>%
cat_entry(e_mesh_location %>% factor(levels = c(\"Inlay\", \"Onlay\", \"Sublay\"))
, xlab = \"Mesh location\"
, pvalue = FALSE
, dt = data %>% dplyr::filter(flg_mesh_used == \"Yes\")
) %>%
binary_entry(
flg_fixation %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Mesh fixation (among repairs using mesh)\"
, dt = data %>% dplyr:::filter(flg_mesh_used == \"Yes\")
, pvalue = FALSE
) %>%
empty_entry(fill = c(\"Mesh fixation type<sup>cata</sup>\",\"N\")) %>%
binary_entry(
e_fixation_type_adhesives %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Adhesives\"
, dt = data %>% dplyr:::filter(flg_fixation == \"Yes\")
, fmt = count_fmt
) %>%
binary_entry(
e_fixation_type_staples %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Staples\"
, dt = data %>% dplyr:::filter(flg_fixation == \"Yes\")
, fmt = count_fmt
) %>%
binary_entry(
e_fixation_type_sutures %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Sutures\"
, dt = data %>% dplyr:::filter(flg_fixation == \"Yes\")
, fmt = count_fmt
) %>%
binary_entry(
e_fixation_type_tacks %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Tacks\"
, dt = data %>% dplyr:::filter(flg_fixation == \"Yes\")
, fmt = count_fmt
) %>%
cont_entry(
val_util_los
, xlab = \"Length of stay (days)\"
, pvalue = FALSE
) %>%
binary_entry(convert_to_open %>% factor(levels = c(0,1))
, xlab = \"Conversion to open\"
, pvalue_fmt = garbage_pvalue
, pvalue = FALSE) %>%
rbindlist
tbl5 <- tbl5 %>% as.data.frame %>%
`attr<-`(\"title\",\"Operative characteristics\")"
, "tbl6 <- list() %>%
binary_entry(
flg_intraop_complication %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Any intra-op complications\"
, pvalue = FALSE
) %>%
empty_entry(
fill = c(
\"Specific complications<sup>cata</sup>\",
\"N (%)\")
) %>%
binary_entry(
array_intraop_complication_type_hemorrhage_requiring_transfusion %>%
factor(levels=c(\"No\",\"Yes\"))
, xlab = \"@@Hemorrhage requiring transfusion\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_peritoneal_access_injury %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Peritoneal access injury\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_bowel_injury %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Bowel injury\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_bladder_injury %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Bladder injury\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_liver_injury %>%
factor(levels=c(\"No\",\"Yes\"))
, xlab = \"@@Liver injury\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_gastric_injury %>%
factor(levels=c(\"No\",\"Yes\"))
, xlab = \"@@Gastric injury\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_major_vascular_injury_requiring_operative_intervention
%>% factor(levels=c(\"No\",\"Yes\"))
, xlab = \"@@Major vascular injury requiring intervention\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_intraop_complication_type_other %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Other\"
, dt = data %>% dplyr:::filter(flg_intraop_complication == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Intra-operative complications\")"
, "tbl7 <- list() %>%
binary_entry(
flg_cmp_postop_any %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Subjects reporting any complication\"
, pvalue_fmt = garbage_pvalue
, pvalue = FALSE
) %>%
empty_entry(
fill = c(\"Specific non-wound/other complication\",\"N\")
) %>%
binary_entry(
flg_pe %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Pulmonary embolism\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_stroke %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Stroke\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_dvt %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@DVT\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_sepsis %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Sepsis\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_septic_shock %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Septic shock\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_mi %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@MI\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_cardiac_arrest %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Cardiac arrest\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_uti %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@UTI\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_renal_insuff %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Renal insufficiency\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_renal_failure %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Acute renal failure\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_pneumonia %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Pneumonia\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_endotracheal %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Respiratory failure requiring intubation\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_ventilator %>% factor(levels = c(0,1))
, xlab = \"@@Ventilator > 48 hrs\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_coma %>% factor(levels = c(0,1))
, xlab = \"@@Coma > 24 hrs\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_nerve_injury %>% factor(levels = c(0,1))
, xlab = \"@@Peripheral nerve injury\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_bleeding_transfusion %>% factor(levels = c(0,1))
, xlab = \"@@Post-op bleeding transfusion\"
, pvalue = FALSE
, fmt = count_fmt
, pvalue_fmt = garbage_pvalue
) %>%
binary_entry(
flg_graft_prosthesis_flap_fail %>% factor(levels = c(0,1))
, xlab = \"@@Graft/prosthesis/flap failure\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_pain %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Pain requiring intervention\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_other_comp %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Other\"
, pvalue = FALSE
, fmt = count_fmt
) %>%
cat_entry(
death_30_days %>% factor(levels = c(\"Actively following\", \"Follow up ended\", \"Death after 30 days\", \"Death (no date reported)\", \"Death within 30 days\"))
, pvalue = FALSE
, xlab = \"Death 30 days\"
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Post-operative complications, mortality, follow-up\")"
, "tbl8 <- list() %>%
binary_entry(
flg_cmp_postop_ssi %>% factor(levels = c(\"No\", \"Yes\"))
# , pvalue_fmt = garbage_pvalue
, pvalue = FALSE
, xlab = \"Surgical site infection (SSI)\"
) %>%
empty_entry(
fill = c(\"Infection type\", \"N\")
) %>%
binary_entry(
array_ssi_comp_type_superficial_surgical_site_infection %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Superficial SSI\"
, dt = data %>% dplyr:::filter(flg_cmp_postop_ssi == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_comp_type_deep_incisional_surgical_site_infection %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Deep incisional SSI\"
, dt = data %>% dplyr:::filter(flg_cmp_postop_ssi == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_comp_type_organ_space_surgical_site_infection %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Organ space SSI\"
, dt = data %>% dplyr:::filter(flg_cmp_postop_ssi == \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
ssi_treatment %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Surgical site infection requiring treatment\"
, dt = data
#, pvalue = FALSE
#, fmt = count_fmt
# , pvalue_fmt = garbage_pvalue
) %>%
binary_entry(
ssi_pi %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Surgical site infection requiring procedural intervention\"
, dt = data
#, pvalue = FALSE
#, fmt = count_fmt
# , pvalue_fmt = garbage_pvalue
) %>%
empty_entry(
fill = c(\"Treatments administered for SSI<sup>cata</sup>\",\"N\")) %>%
binary_entry(
array_ssi_treatments_oral_antibiotics %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Oral antibiotics\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_iv_antibiotics %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@IV antibiotics\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_wound_opening %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound opening\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_wound_debridement %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound debridement\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_suture_excision %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Suture excision\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_percutaneous_drainage %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Percutaneous drainage\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_partial_mesh_removal %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Partial mesh removal\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_ssi_treatments_complete_mesh_removal %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Complete mesh removal\"
, dt = data %>% dplyr:::filter(ssi_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_sso_comps %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Surgical site occurrences exclusive of SSI (SSO-EI)\"
# , pvalue_fmt = garbage_pvalue
, pvalue = FALSE
) %>%
empty_entry(
fill = c(\"SSO-EI complication type<sup>cata</sup>\", \"N\")
) %>%
binary_entry(
array_sso_comp_type_chronic_sinus_drainage %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Chronic sinus drainage\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_contaminated_biologic_mesh %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Contaminated biologic mesh\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_contaminated_synthetic_mesh %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Contaminated synthetic mesh\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_enterocutaneous_fistula %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Enterocutaneous fistula\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_exposed_biologic_mesh %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Exposed biologic mesh\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_exposed_synthetic_mesh %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Exposed synthetic mesh\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_fascial_disruption %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Fascial disruption\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_hematoma %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Hematoma\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_infected_biologic_mesh %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Infected biologic mesh\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_infected_hematoma %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Infected hematoma\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_infected_seroma %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Infected seroma\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_infected_synthetic_mesh %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Infected synthetic mesh\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_localized_stab_wound_infection %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Localized stab wound infection\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_mucocutaneous_anastomosis_disruption %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Mucocutaneous anastomosis disruption\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_nonhealing_incisional_wound %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Nonhealing incisional wound\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_seroma %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Seroma\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_skin_or_soft_tissue_ischemia %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Skin/soft tissue ischemia\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_skin_or_soft_tissue_necrosis %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Skin/soft tissue necrosis\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_stitch_abscess %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Stitch abscess\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_wound_cellulitis %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound cellulitis\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_wound_purulent_drainage %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound purulent drainage\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_wound_serous_drainage %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound serous drainage\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_comp_type_unspecified_surgical_site_occurrence %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Unspecified\"
, dt = data %>% dplyr:::filter(flg_sso_comps == 'Yes')
# , pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
sso_treatment %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"SSO-EI requiring treatment\"
, dt = data
, pvalue = FALSE
# #, fmt = count_fmt
# , pvalue_fmt = garbage_pvalue
) %>%
binary_entry(
sso_pi %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"SSO-EI requiring procedural intervention\"
, dt = data
, pvalue = FALSE
#, fmt = count_fmt
# , pvalue_fmt = garbage_pvalue
) %>%
empty_entry(
fill = c(\"Treatments administered for SSO-EI<sup>cata</sup>\",\"N\")) %>%
binary_entry(
array_sso_treatments_oral_antibiotics %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Oral antibiotics\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_iv_antibiotics %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@IV antibiotics\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_wound_opening %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound opening\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_wound_debridement %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound debridement\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_suture_excision %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Suture excision\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_percutaneous_drainage %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Percutaneous drainage\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_partial_mesh_removal %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Partial mesh removal\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_sso_treatments_complete_mesh_removal %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Complete mesh removal\"
, dt = data %>% dplyr:::filter(sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_cmp_postop_sso_ssi %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Surgical site infection or occurrence (SSI/O)\"
# , pvalue_fmt = garbage_pvalue
, pvalue = FALSE
) %>%
binary_entry(
ssi_sso_treatment %>% factor(levels = c(\"No\",\"Yes\"))
, xlab = \"SSI/O requiring treatment\"
, pvalue = FALSE
, dt = data
# #, fmt = count_fmt
# , pvalue_fmt = garbage_pvalue
) %>%
binary_entry(
ssi_sso_pi %>% factor(levels = c(\"No\",\"Yes\"))
, xlab = \"SSI/O requiring procedural intervention\"
, pvalue = FALSE
, dt = data
#, fmt = count_fmt
# , pvalue_fmt = garbage_pvalue
) %>%
empty_entry(
fill = c(\"Treatments administered for SSI/O<sup>cata</sup>\",\"N\")) %>%
binary_entry(
(1*(array_sso_treatments_oral_antibiotics %in% \"Yes\" |
array_ssi_treatments_oral_antibiotics %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Oral antibiotics\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_iv_antibiotics %in% \"Yes\" |
array_ssi_treatments_iv_antibiotics %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@IV antibiotics\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_wound_opening %in% \"Yes\" |
array_ssi_treatments_wound_opening %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Wound opening\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_wound_debridement %in% \"Yes\" |
array_ssi_treatments_wound_debridement %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Wound debridement\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_suture_excision %in% \"Yes\" |
array_ssi_treatments_suture_excision %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Suture excision\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_percutaneous_drainage %in% \"Yes\" |
array_ssi_treatments_percutaneous_drainage %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Percutaneous drainage\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_partial_mesh_removal %in% \"Yes\" |
array_ssi_treatments_partial_mesh_removal %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Partial mesh removal\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
(1*(array_sso_treatments_complete_mesh_removal %in% \"Yes\" |
array_ssi_treatments_complete_mesh_removal %in% \"Yes\")) %>% factor(levels = c(0:1))
, xlab = \"@@Complete mesh removal\"
, dt = data %>% dplyr:::filter(ssi_sso_treatment %in% \"Yes\")
#, pvalue = FALSE
, fmt = count_fmt
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"SSI/SSO outcomes\")"
, "tbl9 <- list() %>%
empty_entry(fill = c(\"Subject re-encounters<sup>cata</sup>\",\"N (%)\")) %>%
binary_entry(
e_between_visit_clinic %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Clinic\"
, pvalue_fmt = garbage_pvalue
) %>%
binary_entry(
e_between_visit_emergency_room %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Emergency room\"
, pvalue_fmt = garbage_pvalue
) %>%
binary_entry(
flg_readmission %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Re-admission within 30 days\"
, pvalue_fmt = garbage_pvalue
) %>%
empty_entry(fill = c(\"Reported reasons for re-admission<sup>cata</sup>\",\"N\")) %>%
binary_entry(
array_readmission_reason_pain %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Pain\"
, dt = data %>% dplyr:::filter(flg_readmission == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_readmission_reason_prosthetic_related_complication %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Prosthetic related complication\"
, dt = data %>% dplyr:::filter(flg_readmission == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_readmission_reason_wound_complication %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Wound complication\"
, dt = data %>% dplyr:::filter(flg_readmission == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_readmission_reason_bleeding_complication %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Bleeding complication\"
, dt = data %>% dplyr:::filter(flg_readmission == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_readmission_reason_thrombotic_complication_noncardiac %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Thrombotic complication (non-cardiac)\"
, dt = data %>% dplyr:::filter(flg_readmission == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_readmission_reason_gastrointestinal_complication %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Gastrointestinal complication\"
, dt = data %>% dplyr:::filter(flg_readmission == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_reoperation %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"Reoperation\"
, pvalue_fmt = garbage_pvalue
) %>%
empty_entry(
fill = c(\"Reoperation type<sup>cata</sup>\", \"N\")) %>%
binary_entry(
array_reop_type_unrecognized_bowel_injury %>% factor(levels = c(0,1))
, xlab = \"@@Unrecognized bowel injury\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_reop_type_major_wound_complication %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Major wound complication\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_reop_type_postoperative_bleeding %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Postoperative bleeding\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_reop_type_early_recurrence %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Early recurrence\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_reop_type_bowel_obstruction %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Bowel obstruction\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_reop_type_mesh_excision %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Mesh excision\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
array_reop_type_unrelated_intraabdominal_pathology %>% factor(levels = c(\"No\", \"Yes\"))
, xlab = \"@@Unrelated intraabdominal pathology\"
, dt = data %>% dplyr:::filter(flg_reoperation == \"Yes\")
, pvalue = FALSE
, fmt = count_fmt
) %>%
binary_entry(
flg_recurrence %>% factor(levels = c(\"No\", \"Yes\"))
, pvalue_fmt = garbage_pvalue
, pvalue = FALSE
, xlab = \"Hernia recurrence\"
) %>%
rbindlist %>%
as.data.frame %>%
`attr<-`(\"title\",\"Post-operative through 30 day outcomes\")"
)
#table_list <- lapply(table_list, gsub, pattern = "= dt", replacement = paste0("= ", dt)) ## not sure why this was here..
table_list <- lapply(table_list, gsub, pattern = "pvalue = FALSE", replacement = paste0("pvalue = ", pval," "))
if(print == FALSE){
assign(paste0("tbl",tbl), as.character(table_list[tbl]))
if((paste0("tbl",tbl,".R") %in% list.files()) & overwrite == FALSE){
stop(paste0("tbl",tbl,".R already exists in your list of files. To overwrite this file, specify overwrite = TRUE."))
}else{
write(get(paste0("tbl",tbl)), file = paste0("tbl",tbl,".R"))
}
}
if(print == TRUE){
return(as.character(table_list[tbl]))
}
}
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