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Setting up and using ricu to access the publicly available ICU database AmsterdamUMCdb of Amsterdam UMC.

With release of ricu version 0.2.0, this repository has become obsolete and only serves for illustration purposes on how to set up a new data source with ricu.

In order to use the AmsterdamUMCdb as ricu-external dataset, some configuration is necessary to be set up before loading ricu. A configuration file data-sources.json provides the necessary info on the involved tables and concept-dict.json is required for loading ricu clinical concepts from the new dataset. Finally some dataset-specific implementations of certain S3 generic functions exported from ricu are required (see r/ricu.R) as might be some callback functions used in concept specification (see r/callback.R).

This repository contains configuration files and required functions for setting up AmsterdamUMCdb in two different ways: aumc_ext creates an ricu-external version of AmsterdamUMCdb with ID types and column defaults as implemented in the ricu-internal version of AmsterdamUMCdb, whereas aumc_min provides a minimal version of AmsterdamUMCdb with only a single ID type and no per-table column defaults, thereby significantly simplifying initial setup.

Configuring ricu

Several environment variables can be set for ricu to facilitate the integration of AmsterdamUMCdb as external dataset:

  • RICU_DATA_PATH: (optionally) point this to a directory containing a folder aumc_ext which holds the AmsterdamUMCdb data
  • RICU_CONFIG_PATH: point this to the ./config directory of this project
  • RICU_SRC_LOAD: Comma separated list of data sources to automatically load when attaching ricu (e.g. mimic,mimic_demo,aumc_ext)

For now, we leave RICU_DATA_PATH at default and set the other environment variables accordingly before loading ricu

sources <- c("mimic_demo", "eicu_demo", "aumc", "aumc_ext", "aumc_min")

Sys.setenv(RICU_SRC_LOAD = paste(sources, collapse = ","),
           RICU_CONFIG_PATH = "config")

library(ricu)
#> 
#> ── ricu 0.4.1.9000 ─────────────────────────────────────────────────────────────────────────────────
#> 
#> The following data sources are configured to be attached:
#> (the environment variable `RICU_SRC_LOAD` controls this)
#> 
#> ✔ mimic_demo: 25 of 25 tables available
#> ✔ eicu_demo: 31 of 31 tables available
#> ✔ aumc: 7 of 7 tables available
#> ✔ aumc_ext: 7 of 7 tables available
#> ✔ aumc_min: 7 of 7 tables available
#> 
#> ────────────────────────────────────────────────────────────────────────────────────────────────────

for (file in file.path("r", c("ricu.R", "callback.R"))) {
  source(file)
}

As aumc is already fully supported by ricu, all configuration in this repo has been renamed to set up the AmsterdamUMCdb data as external dataset aumc_ext.

Set-up

In order to download and set up the data as aumc_ext, but using ricu functionality for downloading and importing aumc, run:

ext_dir <- src_data_dir("aumc_ext")

download_src("aumc", ext_dir)
import_src("aumc", ext_dir)

attach_src("aumc_ext")

file.symlink(ext_dir, src_data_dir("aumc_min"))

This mimics manual download and conversion to .fst files (as one might do for setting up a new data source manually) and mimimizes the amount of configuration information during set-up (compare aumc_ext of data-sources.json provided by this repo with aumc of the ricu provided data-sources.json.)

Load data

Upon successful set-up, data can be loaded from aumc_ext as:

aumc_ext$processitems
#> # <src_tbl>:  [256,715 ✖ 6]
#> # ID options: patientid (patient) < admissionid (icustay)
#> # Defaults:   `start` (index), `item` (val)
#> # Time vars:  `start`, `stop`
#>         admissionid itemid item                    start      stop duration
#>               <int>  <int> <chr>                   <dbl>     <dbl>    <int>
#>       1           0   9159 Arterielijn Radialis 20520000 148800000     2138
#>       2           0   9166 Trilumen Jugularis   20520000 148800000     2138
#>       3           0   9174 Swan Ganz Jugularis  20520000 139020000     1975
#>       4           0   9328 Beademen             20520000  69120000      810
#>       5           0   9399 Wonddrain 1          20520000  94320000     1230
#>       …
#> 256,711       23551   9422 Perifeer infuus       3900000 165660000     2696
#> 256,712       23551  12634 Tube                  3900000 165660000     2696
#> 256,713       23551  13009 Parenchymdrain        3960000 165660000     2695
#> 256,714       23552   9422 Perifeer infuus         60000  64980000     1082
#> 256,715       23552   9422 Perifeer infuus         60000  73320000     1221
#> # … with 256,705 more rows

load_ts(aumc_ext$processitems, itemid == 9159, id_var = "patientid")
load_ts(aumc_ext$processitems, itemid == 9159, id_var = "admissionid")

gluc <- concept("gluc", unit = "mmol/l",
  item("aumc_ext", "numericitems", "itemid", list(c(9947L, 6833L, 9557L)))
)

load_concepts(gluc, id_type = "patient", verbose = FALSE)
#> # A `ts_tbl`: 587,791 ✖ 3
#> # Id var:     `patientid`
#> # Units:      `gluc` [mmol/l]
#> # Index var:  `measuredat` (1 hours)
#>         patientid measuredat  gluc
#>             <int> <drtn>     <dbl>
#>       1         0 -271 hours  6.40
#>       2         0 -249 hours  7
#>       3         0    5 hours 11.4
#>       4         0    6 hours 10.7
#>       5         0    9 hours  9.60
#>       …
#> 587,787     20325   38 hours  5.30
#> 587,788     20325   39 hours  6.40
#> 587,789     20325   41 hours  5.70
#> 587,790     20325   42 hours  5.40
#> 587,791     20326   13 hours  4.40
#> # … with 587,781 more rows
load_concepts(gluc, id_type = "icustay", verbose = FALSE)
#> # A `ts_tbl`: 771,720 ✖ 3
#> # Id var:     `admissionid`
#> # Units:      `gluc` [mmol/l]
#> # Index var:  `measuredat` (1 hours)
#>         admissionid measuredat  gluc
#>               <int> <drtn>     <dbl>
#>       1           0 -271 hours  6.40
#>       2           0 -249 hours  7
#>       3           0    5 hours 11.4
#>       4           0    6 hours 10.7
#>       5           0    9 hours  9.60
#>       …
#> 771,716       23551   38 hours  5.30
#> 771,717       23551   39 hours  6.40
#> 771,718       23551   41 hours  5.70
#> 771,719       23551   42 hours  5.40
#> 771,720       23552   13 hours  4.40
#> # … with 771,710 more rows

concept_availability(concepts = c("glu", "alb", "weight"))
#>        aumc aumc_ext aumc_min eicu_demo mimic_demo
#> glu    TRUE     TRUE     TRUE      TRUE       TRUE
#> alb    TRUE     TRUE     TRUE      TRUE       TRUE
#> weight TRUE    FALSE    FALSE      TRUE       TRUE

load_concepts(c("glu", "alb"), "aumc_ext", verbose = FALSE)
#> # A `ts_tbl`: 780,378 ✖ 4
#> # Id var:     `admissionid`
#> # Units:      `glu` [mg/dL], `alb` [g/dL]
#> # Index var:  `measuredat` (1 hours)
#>         admissionid measuredat   glu   alb
#>               <int> <drtn>     <dbl> <dbl>
#>       1           0 -271 hours 115.   NA
#>       2           0 -249 hours 126.   NA
#>       3           0    5 hours 205.   NA
#>       4           0    6 hours 193.    2.2
#>       5           0    9 hours 173.   NA
#>       …
#> 780,374       23551   38 hours  95.5   2
#> 780,375       23551   39 hours 115.   NA
#> 780,376       23551   41 hours 103.   NA
#> 780,377       23551   42 hours  97.3  NA
#> 780,378       23552   13 hours  79.3  NA
#> # … with 780,368 more rows
load_concepts(c("alb", "weight"), "aumc_ext", verbose = FALSE)
#> # A `ts_tbl`: 106,139 ✖ 4
#> # Id var:     `admissionid`
#> # Units:      `alb` [g/dL], `weight` [kg]
#> # Index var:  `measuredat` (1 hours)
#>         admissionid measuredat   alb weight
#>               <int> <drtn>     <dbl>  <dbl>
#>       1           0  6 hours     2.2     NA
#>       2           1  0 hours     2.9     NA
#>       3           2  0 hours     2.8     NA
#>       4           3  2 hours     2.8     NA
#>       5           4 41 hours     2.5     NA
#>       …
#> 106,135       23549  9 hours     2.6     NA
#> 106,136       23550  2 hours     2.2     NA
#> 106,137       23551  1 hours     2.6     NA
#> 106,138       23551 14 hours     2.3     NA
#> 106,139       23551 38 hours     2       NA
#> # … with 106,129 more rows

and from aumc_min as

aumc_min$processitems
#> # <src_tbl>: [256,715 ✖ 6]
#>         admissionid itemid item                    start      stop duration
#>               <int>  <int> <chr>                   <dbl>     <dbl>    <int>
#>       1           0   9159 Arterielijn Radialis 20520000 148800000     2138
#>       2           0   9166 Trilumen Jugularis   20520000 148800000     2138
#>       3           0   9174 Swan Ganz Jugularis  20520000 139020000     1975
#>       4           0   9328 Beademen             20520000  69120000      810
#>       5           0   9399 Wonddrain 1          20520000  94320000     1230
#>       …
#> 256,711       23551   9422 Perifeer infuus       3900000 165660000     2696
#> 256,712       23551  12634 Tube                  3900000 165660000     2696
#> 256,713       23551  13009 Parenchymdrain        3960000 165660000     2695
#> 256,714       23552   9422 Perifeer infuus         60000  64980000     1082
#> 256,715       23552   9422 Perifeer infuus         60000  73320000     1221
#> # … with 256,705 more rows

load_ts(aumc_min$processitems, itemid == 9159, id_var = "admissionid",
        index_var = "start", time_vars = c("start", "stop"))

gluc <- concept("gluc", unit = "mmol/l",
  item("aumc_min", "numericitems", "itemid", list(c(9947L, 6833L, 9557L)),
       index_var = "measuredat", val_var = "value", unit_var = "unit",
       time_vars = list(c("measuredat", "registeredat", "updatedat")))
)

load_concepts(gluc, id_type = "icustay", verbose = FALSE)
#> # A `ts_tbl`: 771,720 ✖ 3
#> # Id var:     `admissionid`
#> # Units:      `gluc` [mmol/l]
#> # Index var:  `index_var` (1 hours)
#>         admissionid index_var   gluc
#>               <int> <drtn>     <dbl>
#>       1           0 -271 hours  6.40
#>       2           0 -249 hours  7
#>       3           0    5 hours 11.4
#>       4           0    6 hours 10.7
#>       5           0    9 hours  9.60
#>       …
#> 771,716       23551   38 hours  5.30
#> 771,717       23551   39 hours  6.40
#> 771,718       23551   41 hours  5.70
#> 771,719       23551   42 hours  5.40
#> 771,720       23552   13 hours  4.40
#> # … with 771,710 more rows
load_concepts(c("glu", "alb"), "aumc_min", verbose = FALSE)
#> # A `ts_tbl`: 780,378 ✖ 4
#> # Id var:     `admissionid`
#> # Units:      `glu` [mg/dL], `alb` [g/dL]
#> # Index var:  `index_var` (1 hours)
#>         admissionid index_var    glu   alb
#>               <int> <drtn>     <dbl> <dbl>
#>       1           0 -271 hours 115.   NA
#>       2           0 -249 hours 126.   NA
#>       3           0    5 hours 205.   NA
#>       4           0    6 hours 193.    2.2
#>       5           0    9 hours 173.   NA
#>       …
#> 780,374       23551   38 hours  95.5   2
#> 780,375       23551   39 hours 115.   NA
#> 780,376       23551   41 hours 103.   NA
#> 780,377       23551   42 hours  97.3  NA
#> 780,378       23552   13 hours  79.3  NA
#> # … with 780,368 more rows

Note that for aumc_min, data can only be queried using the icustay ID type and calls to load_ts() and related functions, as well as instantiation of data items is required to be more verbose, as corresponding default values are not available from configuration info. Similarly, aumc_min items in concept-dict.json also repeatedly require this information.

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AUMCdb data for the R package ricu

cran.r-project.org/package=ricu

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