diff --git a/ML/0-data_prep.R b/ML/0-data_prep.R
index 1aaae3b..9b180a6 100644
--- a/ML/0-data_prep.R
+++ b/ML/0-data_prep.R
@@ -43,6 +43,7 @@ test_list_cmp <- c(
   ,50995	#Thyroxine (T4), Free
 )
 
+# 51301 and 51300 looks like test name may have changed
 test_list_bmp <- c(
   51006	#Urea Nitrogen
   ,50893	#Calcium, Total
@@ -54,7 +55,13 @@ test_list_bmp <- c(
   ,50983	#Sodium
   ,50993	#Thyroid Stimulating Hormone
   ,50995	#Thyroxine (T4), Free
-)
+  ,51279  #RBC
+  ,51301	#White Blood Cells
+  ,51300	#WBC Count
+  ,51221	#Hematocrit
+  ,51222	#Hemoglobin
+  ,51265	#Platelet Count
+  )
 
 # TSH Ref Range from File 0.27 - 4.2 uIU/mL
 # Free T4 Ref Range from File 0.93 - 1.7 ng/dL
@@ -80,28 +87,9 @@ patients <- dplyr$tbl(db, "patients") %>%
 #   dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
 #   dplyr$filter(dplyr$across(where(is.numeric), ~!is.na(.x))) %>%
 #   dplyr$collect()
-
-ds_cmp <- dplyr$tbl(db, "labevents") %>%
-  dplyr$filter(itemid %in% test_list_cmp) %>%
-  dplyr$select(-storetime) %>%
-  tidyr$pivot_wider(
-    id_cols = c(subject_id,charttime)
-    ,names_from = itemid
-    ,values_from = valuenum
-  ) %>%
-  dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
-  dplyr$collect()
-
-#this keeps failing if run as part of the above query.  Moving here to keep going
-# keeps only rows that have no more then three NA's
-ds_cmp <- patients %>%
-  dplyr$left_join(ds_cmp, by = c("subject_id" = "subject_id")) %>%
-  dplyr$filter(rowSums(is.na(.)) <= 3)
-
-
-# No longer using this, but saving incase
-# ds_bmp <- dplyr$tbl(db, "labevents") %>%
-#   dplyr$filter(itemid %in% test_list_bmp) %>%
+#No longer using this, but saving incase
+# ds_cmp <- dplyr$tbl(db, "labevents") %>%
+#   dplyr$filter(itemid %in% test_list_cmp) %>%
 #   dplyr$select(-storetime) %>%
 #   tidyr$pivot_wider(
 #     id_cols = c(subject_id,charttime)
@@ -111,21 +99,44 @@ ds_cmp <- patients %>%
 #   dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
 #   dplyr$collect()
 #
-# ds_bmp <- patients %>%
-#   dplyr$left_join(ds_bmp, by = c("subject_id" = "subject_id")) %>%
-#   dplyr$filter(dplyr$if_all(.fns = ~!is.na(.)))
+# #this keeps failing if run as part of the above query.  Moving here to keep going
+# # keeps only rows that have no more then three NA's
+# ds_cmp <- patients %>%
+#   dplyr$left_join(ds_cmp, by = c("subject_id" = "subject_id")) %>%
+#   dplyr$filter(rowSums(is.na(.)) <= 3)
+
+# BMP and CBC Results together
+
+ds_bmp <- dplyr$tbl(db, "labevents") %>%
+  dplyr$filter(itemid %in% test_list_bmp) %>%
+  dplyr$select(-storetime) %>%
+  tidyr$pivot_wider(
+    id_cols = c(subject_id,charttime)
+    ,names_from = itemid
+    ,values_from = valuenum
+  ) %>%
+  dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
+  dplyr$collect()
+
+
+ds_bmp <- ds_bmp %>%
+  dplyr$left_join(patients, by = c("subject_id" = "subject_id")) %>%
+  dplyr$mutate(dplyr$across(`51300`, ~dplyr$if_else(!is.na(.),`51300`,`51301`))) %>%
+  dplyr$select(-`51301`) %>%
+  # dplyr$filter(dplyr$if_all(.fns = ~!is.na(.)))
+  dplyr$filter(rowSums(is.na(.)) <= 2)  #allows for 2 missing test
 
 
 # save data ---------------------------------------------------------------
 
 
-ds_high_tsh <- ds_cmp %>%
+ds_high_tsh <- ds_bmp %>%
   dplyr$filter(`50993` > 4.2) %>%
   readr$write_rds(
     here("ML","data-unshared","ds_high_tsh.RDS")
   )
 
-ds_low_tsh <- ds_cmp %>%
+ds_low_tsh <- ds_bmp %>%
   dplyr$filter(`50993` < 0.27) %>%
   readr$write_rds(
     here("ML","data-unshared","ds_low_tsh.RDS")