Closed vmoitra closed 8 months ago
In ricu we have, what we call a dictionary of concepts, covering ~100 variables corresponding to vitals, lab tests, medications, etc. Before setting up the full datasets, for some initial exploration, you could restrict yourself to the demo datasets. But all of this can of course be run, using full data as well. First, we load this dictionary for the demo datasets:
dict <- load_dictionary(c("mimic_demo", "eicu_demo"))
length(dict)
#> [1] 119
head(dict)
#> <concept[6]>
#> abx adh_rate
#> antibiotics <lgl_cncpt[4]> vasopressin rate <num_cncpt[3]>
#> adm age
#> patient admission type <fct_cncpt[2]> patient age <num_cncpt[2]>
#> alb alp
#> albumin <num_cncpt[2]> alkaline phosphatase <num_cncpt[2]>
Concept availability is fairly consistent over datasets, but in some cases, does vary due to availability of corresponding raw data. I only show the top 6 concepts using head()
, but you can easily reproduce this for the full ~100 concept. In order to answer your question pertaining to time-series data, you can query the target type of concepts:
head(concept_availability(dict))
#> eicu_demo mimic_demo
#> abx TRUE TRUE
#> adh_rate TRUE TRUE
#> adm TRUE TRUE
#> age TRUE TRUE
#> alb TRUE TRUE
#> alp TRUE TRUE
head(explain_dictionary(dict, cols = c("name", "target")))
#> name target
#> 1 abx ts_tbl
#> 2 adh_rate ts_tbl
#> 3 adm id_tbl
#> 4 age id_tbl
#> 5 alb ts_tbl
#> 6 alp ts_tbl
Now, whenever the target type is ts_tbl
, the concept represents time-varying data. Other target types are id_tbl
(for static data such as age, admission type, etc.) and win_tbl
for time-stamped interval data, such as for example certain infusions.
To close this, I am attaching the availability of concepts in ricu 0.6.0
:
> concept_availability()
aumc eicu eicu_demo hirid miiv mimic mimic_demo sic
abx TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
adh_rate TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
adm TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
age TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
alb TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
alp TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
alt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
ast TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
basos TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
be TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
bicar TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
bili TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
bili_dir TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
bnd TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
bun TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
ca TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
cai TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
ck TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
ckmb TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
cl TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
cort TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
crea TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
crp TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
dbp TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
death TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
dex TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
dobu_dur TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
dobu_rate TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
dopa_dur TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
dopa_rate TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
egcs TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
eos TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
epi_dur TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
epi_rate TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
esr TRUE FALSE FALSE TRUE TRUE TRUE TRUE FALSE
etco2 TRUE FALSE FALSE TRUE TRUE TRUE TRUE FALSE
ett_gcs TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
fgn TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
fio2 TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
glu TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
hba1c TRUE FALSE FALSE FALSE TRUE TRUE TRUE FALSE
hbco TRUE TRUE TRUE TRUE FALSE FALSE FALSE FALSE
hct TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
height TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
hgb TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
hr TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
inr_pt TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
ins TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
k TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
lact TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
los_hosp FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
los_icu TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
lymph TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
map TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
mch TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
mchc TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
mcv TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
mech_vent TRUE FALSE FALSE TRUE TRUE FALSE FALSE FALSE
methb TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
mg TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
mgcs TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
na TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
neut TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
norepi_dur TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
norepi_rate TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
o2sat TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
pco2 TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
ph TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
phn_rate FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
phos TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
plt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
po2 TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
pt TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
ptt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
rass TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
rbc TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
rdw TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
resp TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
samp TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
sbp TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
sex TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
tco2 FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
temp TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
tgcs FALSE TRUE TRUE FALSE FALSE TRUE TRUE FALSE
tnt TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
tri FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
urine TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
vent_end FALSE TRUE TRUE FALSE FALSE TRUE TRUE FALSE
vent_start FALSE TRUE TRUE FALSE FALSE TRUE TRUE FALSE
vgcs TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
wbc TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
weight TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
I came across your paper on the RICU interface to intensive care data. I am NOT a stastician and most of my work is adminsitrative and as a clinician. I am, however, interested in exploring research in critical care databases. I have an account with physio NET. As a non statistician, if I wanted to figure out what variables had time stamps and what outcomes were available (MMIC, Amsterdam, HRid, Berlin), how can I figure that out? My hope is to develop a data analysis plan before finding a statistician.