Merge branch 'dev/aki-df' into dev/anemia

DESCRIPTION

@@ -30,7 +30,8 @@ Imports:
     ellipsis,
     rlang,
     units,
-    lubridate
+    lubridate,
+    magrittr
 Suggests:
     testthat,
     covr

NAMESPACE

@@ -4,4 +4,7 @@ S3method(aki,default)
 S3method(aki,numeric)
 S3method(aki,ts)
 S3method(aki,units)
+export("%>%")
 export(aki)
+importFrom(magrittr,"%>%")
+importFrom(rlang,.data)

R/aki.R

@@ -6,6 +6,47 @@
   }
 }
 
+#' @importFrom rlang .data
+#' @importFrom magrittr %>%
+.generate_cr_ch <- function(data,
+  SCr, dttm, pt_id)
+{
+  cr_ts = data %>%
+    dplyr::ungroup() %>%
+    {if (TRUE) dplyr::group_by(.data, dplyr::across(dplyr::all_of(pt_id))) else .data} %>%
+    dplyr::select(dplyr::all_of(c(pt_id, dttm, SCr))) %>%
+    unique(.data)  # To remove any duplicate DTTM entries
+
+  # if (nrow(cr_ts) < 2) {
+  #   return(data.frame(
+  #     DateTime_Pathology_Result = as_datetime(NA_real_),
+  #     del_t_ch  = as.duration(NA_real_),
+  #     del_t_aki = as.duration(NA_real_),
+  #     del_cr    = NA_real_,
+  #     cr      = NA_real_
+  #   ))
+  # }
+  # Consider filtering out ones post AKI here?
+
+  # combns <- combn(nrow(cr_ts), 2)
+  # Ti_1 = cr_ts[combns[1,],]
+  # Ti   = cr_ts[combns[2,],]
+  #
+  # if(AKI_ICU == 0 | is.na(AKI_ICU)) {
+  #   del_t_aki = rep(as.duration(NA_real_), nrow(Ti))
+  # } else {
+  #   del_t_aki = as.duration(DateTime_AKI_Dx - Ti$Pathology_Result_DTTM)
+  # }
+  #
+  # return(data.frame(
+  #   DateTime_Pathology_Result = Ti$Pathology_Result_DTTM,
+  #   del_t_ch  = as.duration(Ti$Pathology_Result_DTTM - Ti_1$Pathology_Result_DTTM),
+  #   del_t_aki = del_t_aki,
+  #   del_cr    = Ti$Creatinine_level - Ti_1$Creatinine_level,
+  #   cr      = Ti$Creatinine_level
+  # ))
+}
+
 #' Codify AKI from Serum Creatinine and/or Urine Output
 #'
 #' Using KDIGO Clinical Practice Guideline for Acute Kidney Injury
@@ -80,5 +121,6 @@ aki.ts <- function(SCr, UO, units = "umol/l", ...) {
 #' @rdname aki
 #' @export
 aki.default <- function(data, SCr, bCr, units = list("SCr" = "umol/l"), na.rm = FALSE, ...) {
+  predictor <- rlang::as_name(rlang::enquo(SCr))
   factor(data, levels = .aki_stages)
 }

R/utils-pipe.R

@@ -0,0 +1,11 @@
+#' Pipe operator
+#'
+#' See \code{magrittr::\link[magrittr:pipe]{\%>\%}} for details.
+#'
+#' @name %>%
+#' @rdname pipe
+#' @keywords internal
+#' @export
+#' @importFrom magrittr %>%
+#' @usage lhs \%>\% rhs
+NULL

tests/testthat/test-aki.R

@@ -71,8 +71,8 @@ test_that("aki() for vector of SCr in mg/dl with baseline", {
 })
 
 data <- data.frame(
-  pt_id = c(rep("pt1", 11), rep("pt2", 13)),
-  dttm = c(
+  pt_id_ = c(rep("pt1", 11), rep("pt2", 13)),
+  dttm_ = c(
     seq(
       lubridate::as_datetime("2020-10-18 09:00:00", tz = "Australia/Melbourne"),
       lubridate::as_datetime("2020-10-20 09:00:00", tz = "Australia/Melbourne"),
@@ -84,11 +84,11 @@ data <- data.frame(
       length.out = 13
     )
   ),
-  SCr = c(
+  SCr_ = c(
     units::set_units(seq(2.0, 4.5, by = 0.25), "mg/dl"),
     units::set_units(seq(3.0, 4.2, by = 0.10), "mg/dl")
   ),
-  bCr = c(
+  bCr_ = c(
     rep(units::set_units(1.8, "mg/dl"), 11),
     rep(units::set_units(3.0, "mg/dl"), 13)
   )