138 lines
3.7 KiB
R
138 lines
3.7 KiB
R
rm(list = ls(all.names = TRUE)) # Clear the memory of variables from previous run.
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cat("\014") # Clear the console
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# load packages -----------------------------------------------------------
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box::use(
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magrittr[`%>%`]
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,RSQLite
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,DBI[dbConnect,dbDisconnect]
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,here[here]
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,dplyr
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,dbplyr
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,tidyr
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,readr
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)
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# globals -----------------------------------------------------------------
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db <- dbConnect(
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RSQLite$SQLite()
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,here("ML","data-unshared","mimicDB.sqlite")
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)
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#item list shows two different numbers for a few tests, second set of items do not have
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# any results that are on the same samples as TSH and Free T4
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test_list_cmp <- c(
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50862 #Albumin
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,50863 #Alkaline Phosphatase
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,50861 #Alanine Aminotransferase (ALT)
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,50878 #Asparate Aminotransferase (AST)
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,51006 #Urea Nitrogen
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,50893 #Calcium, Total
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,50882 #Bicarbonate
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,50902 #Chloride
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,50912 #Creatinine
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,50931 #Glucose
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,50971 #Potassium
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,50983 #Sodium
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,50885 #Bilirubin, Total
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,50976 #Protein, Total
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,50993 #Thyroid Stimulating Hormone
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,50995 #Thyroxine (T4), Free
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)
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test_list_bmp <- c(
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51006 #Urea Nitrogen
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,50893 #Calcium, Total
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,50882 #Bicarbonate
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,50902 #Chloride
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,50912 #Creatinine
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,50931 #Glucose
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,50971 #Potassium
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,50983 #Sodium
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,50993 #Thyroid Stimulating Hormone
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,50995 #Thyroxine (T4), Free
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)
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# TSH Ref Range from File 0.27 - 4.2 uIU/mL
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# Free T4 Ref Range from File 0.93 - 1.7 ng/dL
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# load data ---------------------------------------------------------------
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# load patients first to add to lab values
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patients <- dplyr$tbl(db, "patients") %>%
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dplyr$select(-anchor_year, -anchor_year_group, -dod) %>%
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dplyr$collect()
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# most likely will not use this as there are not as many complete rows. However
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# gathering it just in case.
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# first is using specimen id, usable data set is using chart time as it appears
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# LIS uses different id's for groups of tests
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#
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# ds_cmp <- dplyr$tbl(db, "labevents") %>%
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# dplyr$filter(itemid %in% test_list_cmp) %>%
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# dplyr$select(-charttime,-storetime) %>%
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# tidyr$pivot_wider(
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# id_cols = c(subject_id,specimen_id)
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# ,names_from = itemid
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# ,values_from = valuenum
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# ) %>%
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# dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
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# dplyr$filter(dplyr$across(where(is.numeric), ~!is.na(.x))) %>%
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# dplyr$collect()
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ds_cmp <- dplyr$tbl(db, "labevents") %>%
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dplyr$filter(itemid %in% test_list_cmp) %>%
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dplyr$select(-storetime) %>%
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tidyr$pivot_wider(
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id_cols = c(subject_id,charttime)
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,names_from = itemid
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,values_from = valuenum
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) %>%
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dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
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dplyr$collect()
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#this keeps failing if run as part of the above query. Moving here to keep going
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# keeps only rows that have values for all columns
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ds_cmp <- patients %>%
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dplyr$left_join(ds_cmp, by = c("subject_id" = "subject_id")) %>%
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dplyr$filter(dplyr$if_all(.fns = ~!is.na(.)))
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ds_bmp <- dplyr$tbl(db, "labevents") %>%
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dplyr$filter(itemid %in% test_list_bmp) %>%
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dplyr$select(-storetime) %>%
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tidyr$pivot_wider(
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id_cols = c(subject_id,charttime)
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,names_from = itemid
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,values_from = valuenum
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) %>%
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dplyr$filter(!is.na(`50993`) & !is.na(`50995`)) %>%
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dplyr$collect()
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ds_bmp <- patients %>%
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dplyr$left_join(ds_bmp, by = c("subject_id" = "subject_id")) %>%
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dplyr$filter(dplyr$if_all(.fns = ~!is.na(.)))
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# save data ---------------------------------------------------------------
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ds_high_tsh <- ds_bmp %>%
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dplyr$filter(`50993` > 4.2) %>%
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readr$write_rds(
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here("ML","data-unshared","ds_high_tsh.RDS")
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)
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ds_low_tsh <- ds_bmp %>%
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dplyr$filter(`50993` < 0.27) %>%
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readr$write_rds(
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here("ML","data-unshared","ds_low_tsh.RDS")
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)
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S
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# close database ----------------------------------------------------------
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dbDisconnect(db)
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