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reference/get_episode.md
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@@ -178,29 +178,27 @@ x
df <- example_isolates[sample(seq_len(2000), size = 100), ]
get_episode(df$date, episode_days = 60) # indices
#> [1] 20 43 19 12 43 41 12 28 30 15 41 18 34 6 15 9 29 8 45 16 43 10 14 9 42
#> [26] 48 8 28 24 4 31 45 20 43 47 4 30 2 15 22 15 19 32 27 4 11 12 3 2 28
#> [51] 35 2 42 27 7 3 17 45 46 11 13 37 25 36 37 17 47 1 32 21 20 35 41 31 32
#> [76] 24 21 33 48 25 40 42 39 6 23 5 11 35 13 33 16 38 18 49 44 2 48 26 9 3
#> [1] 28 47 7 7 6 17 9 4 37 11 43 43 14 38 26 38 12 39 49 18 15 27 5 22 25
#> [26] 36 11 18 22 41 42 38 33 35 18 45 11 30 40 31 46 19 24 18 17 16 43 46 1 23
#> [51] 2 18 34 45 21 3 45 12 48 30 10 13 29 40 48 30 2 20 9 19 14 36 19 32 36
#> [76] 10 44 20 4 4 36 8 48 43 46 9 32 6 8 29 13 6 45 9 12 38 45 44 35 5
is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
#> [1] TRUE TRUE TRUE TRUE FALSE TRUE FALSE TRUE TRUE TRUE FALSE TRUE
#> [13] TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE FALSE TRUE TRUE FALSE
#> [25] TRUE TRUE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE TRUE FALSE
#> [37] FALSE TRUE FALSE TRUE FALSE FALSE TRUE TRUE FALSE TRUE FALSE TRUE
#> [49] FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE TRUE FALSE
#> [61] TRUE TRUE TRUE TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE
#> [73] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE TRUE FALSE
#> [85] TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE FALSE
#> [97] FALSE TRUE FALSE FALSE
#> [1] TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
#> [13] TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [25] TRUE TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE FALSE TRUE
#> [37] FALSE TRUE TRUE TRUE TRUE TRUE TRUE FALSE FALSE TRUE FALSE FALSE
#> [49] TRUE TRUE TRUE FALSE TRUE FALSE TRUE TRUE FALSE FALSE TRUE FALSE
#> [61] TRUE TRUE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
#> [73] FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
#> [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [97] FALSE FALSE FALSE FALSE
# filter on results from the third 60-day episode only, using base R
df[which(get_episode(df$date, 60) == 3), ]
#> # A tibble: 3 × 46
#> date patient age gender ward mo PEN OXA FLC AMX
#> <date> <chr> <dbl> <chr> <chr> <mo> <sir> <sir> <sir> <sir>
#> 1 2002-10-20 F35553 51 M ICU B_STPHY_AURS S NA S NA
#> 2 2002-09-24 CF9318 29 M ICU B_CMPYL_JEJN NA NA NA NA
#> 3 2002-08-31 149442 80 F ICU B_STPHY_AURS R NA S R
#> # A tibble: 1 × 46
#> date patient age gender ward mo PEN OXA FLC AMX
#> <date> <chr> <dbl> <chr> <chr> <mo> <sir> <sir> <sir> <sir>
#> 1 2002-06-07 710157 76 M Outpatie… B_STPHY_CONS S NA S NA
#> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>,
#> # CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>,
#> # TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>,
@@ -234,19 +232,19 @@ if (require("dplyr")) {
arrange(patient, condition, date)
}
#> # A tibble: 100 × 4
#> # Groups: patient, condition [97]
#> # Groups: patient, condition [95]
#> patient date condition new_episode
#> <chr> <date> <chr> <lgl>
#> 1 018637 2005-09-28 C TRUE
#> 2 022060 2004-05-04 C TRUE
#> 3 032343 2003-06-09 B TRUE
#> 4 080086 2010-08-08 C TRUE
#> 5 126334 2009-11-26 A TRUE
#> 6 149442 2002-08-31 C TRUE
#> 7 14D826 2006-09-14 A TRUE
#> 8 16F0F7 2010-01-17 C TRUE
#> 9 179451 2007-09-15 B TRUE
#> 10 189795 2008-10-19 B TRUE
#> 1 005088 2017-09-28 B TRUE
#> 2 010257 2004-04-03 C TRUE
#> 3 080086 2007-10-26 A TRUE
#> 4 083080 2012-04-16 B TRUE
#> 5 0E2483 2008-07-22 B TRUE
#> 6 141061 2014-10-22 B TRUE
#> 7 16DC39 2015-11-19 A TRUE
#> 8 204562 2010-07-03 B TRUE
#> 9 22B987 2009-10-19 C TRUE
#> 10 257844 2011-05-22 C TRUE
#> # ℹ 90 more rows
if (require("dplyr")) {
@@ -260,19 +258,19 @@ if (require("dplyr")) {
arrange(patient, ward, date)
}
#> # A tibble: 100 × 5
#> # Groups: ward, patient [94]
#> # Groups: ward, patient [91]
#> ward date patient new_index new_logical
#> <chr> <date> <chr> <int> <lgl>
#> 1 Clinical 2005-09-28 018637 1 TRUE
#> 2 ICU 2004-05-04 022060 1 TRUE
#> 3 Clinical 2003-06-09 032343 1 TRUE
#> 4 Clinical 2010-08-08 080086 1 TRUE
#> 5 Outpatient 2009-11-26 126334 1 TRUE
#> 6 ICU 2002-08-31 149442 1 TRUE
#> 7 Clinical 2006-09-14 14D826 1 TRUE
#> 8 Clinical 2010-01-17 16F0F7 1 TRUE
#> 9 ICU 2007-09-15 179451 1 TRUE
#> 10 Clinical 2008-10-19 189795 1 TRUE
#> 1 Clinical 2017-09-28 005088 1 TRUE
#> 2 Clinical 2004-04-03 010257 1 TRUE
#> 3 Clinical 2007-10-26 080086 1 TRUE
#> 4 Clinical 2012-04-16 083080 1 TRUE
#> 5 Clinical 2008-07-22 0E2483 1 TRUE
#> 6 Clinical 2014-10-22 141061 1 TRUE
#> 7 ICU 2015-11-19 16DC39 1 TRUE
#> 8 Outpatient 2010-07-03 204562 1 TRUE
#> 9 Clinical 2009-10-19 22B987 1 TRUE
#> 10 Clinical 2011-05-22 257844 1 TRUE
#> # ℹ 90 more rows
if (require("dplyr")) {
@@ -288,9 +286,9 @@ if (require("dplyr")) {
#> # A tibble: 3 × 5
#> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30
#> <chr> <int> <int> <int> <int>
#> 1 Clinical 55 14 33 43
#> 2 ICU 33 11 23 27
#> 3 Outpatient 6 5 5 5
#> 1 Clinical 60 13 39 49
#> 2 ICU 26 11 23 24
#> 3 Outpatient 5 5 5 5
# grouping on patients and microorganisms leads to the same
# results as first_isolate() when using 'episode-based':
@@ -308,7 +306,7 @@ if (require("dplyr")) {
identical(x, y)
}
#> [1] TRUE
#> [1] FALSE
# but is_new_episode() has a lot more flexibility than first_isolate(),
# since you can now group on anything that seems relevant:
@@ -319,19 +317,19 @@ if (require("dplyr")) {
select(group_vars(.), flag_episode)
}
#> # A tibble: 100 × 4
#> # Groups: patient, mo, ward [97]
#> # Groups: patient, mo, ward [94]
#> patient mo ward flag_episode
#> <chr> <mo> <chr> <lgl>
#> 1 189795 B_AERCC_URNQ Clinical TRUE
#> 2 5C1947 B_ESCHR_COLI Clinical TRUE
#> 3 D22254 B_ESCHR_COLI Clinical TRUE
#> 4 018637 B_ESCHR_COLI Clinical TRUE
#> 5 483195 B_ESCHR_COLI ICU TRUE
#> 6 324415 B_PROTS_MRBL ICU TRUE
#> 7 671180 B_ESCHR_COLI Clinical TRUE
#> 8 59B5BD B_ESCHR_COLI Clinical TRUE
#> 9 443847 B_STPHY_CONS Clinical TRUE
#> 10 690B42 B_ESCHR_COLI ICU TRUE
#> 1 D91230 B_STPHY_EPDR Clinical TRUE
#> 2 F5F794 B_STPHY_AURS ICU TRUE
#> 3 419655 B_STPHY_EPDR Clinical TRUE
#> 4 010257 B_ESCHR_COLI Clinical TRUE
#> 5 E60130 B_KLBSL_OXYT Clinical TRUE
#> 6 693505 B_STPHY_AURS ICU TRUE
#> 7 E1C9D4 B_STPHY_CONS Clinical TRUE
#> 8 762305 B_PROTS_MRBL Clinical TRUE
#> 9 545388 B_STPHY_HMNS Clinical TRUE
#> 10 E02001 B_ESCHR_COLI Clinical TRUE
#> # ℹ 90 more rows
# }
```