# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Data Analysis for R # # # # SOURCE # # https://github.com/msberends/AMR # # # # LICENCE # # (c) 2018-2021 Berends MS, Luz CF et al. # # Developed at the University of Groningen, the Netherlands, in # # collaboration with non-profit organisations Certe Medical # # Diagnostics & Advice, and University Medical Center Groningen. # # # # This R package is free software; you can freely use and distribute # # it for both personal and commercial purposes under the terms of the # # GNU General Public License version 2.0 (GNU GPL-2), as published by # # the Free Software Foundation. # # We created this package for both routine data analysis and academic # # research and it was publicly released in the hope that it will be # # useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # # # # Visit our website for the full manual and a complete tutorial about # # how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # ==================================================================== # # all four methods expect_equal(sum(first_isolate(x = example_isolates, method = "isolate-based", info = TRUE), na.rm = TRUE), 1984) expect_equal(sum(first_isolate(x = example_isolates, method = "patient-based", info = TRUE), na.rm = TRUE), 1265) expect_equal(sum(first_isolate(x = example_isolates, method = "episode-based", info = TRUE), na.rm = TRUE), 1300) expect_equal(sum(first_isolate(x = example_isolates, method = "phenotype-based", info = TRUE), na.rm = TRUE), 1379) # Phenotype-based, using key antimicrobials expect_equal(sum(first_isolate(x = example_isolates, method = "phenotype-based", type = "keyantimicrobials", antifungal = NULL, info = TRUE), na.rm = TRUE), 1395) expect_equal(sum(first_isolate(x = example_isolates, method = "phenotype-based", type = "keyantimicrobials", antifungal = NULL, info = TRUE, ignore_I = FALSE), na.rm = TRUE), 1418) # first non-ICU isolates expect_equal( sum( first_isolate(example_isolates, col_mo = "mo", col_date = "date", col_patient_id = "patient_id", col_icu = "ward_icu", info = TRUE, icu_exclude = TRUE), na.rm = TRUE), 941) # set 1500 random observations to be of specimen type 'Urine' random_rows <- sample(x = 1:2000, size = 1500, replace = FALSE) x <- example_isolates x$specimen <- "Other" x[random_rows, "specimen"] <- "Urine" expect_true( sum(first_isolate(x = x, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", col_specimen = "specimen", filter_specimen = "Urine", info = TRUE), na.rm = TRUE) < 1501) # same, but now exclude ICU expect_true( sum(first_isolate(x = x, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", col_specimen = "specimen", filter_specimen = "Urine", col_icu = "ward_icu", icu_exclude = TRUE, info = TRUE), na.rm = TRUE) < 1501) # "No isolates found" test_iso <- example_isolates test_iso$specimen <- "test" expect_message(first_isolate(test_iso, "date", "patient_id", col_mo = "mo", col_specimen = "specimen", filter_specimen = "something_unexisting", info = TRUE)) # printing of exclusion message expect_message(first_isolate(example_isolates, col_date = "date", col_mo = "mo", col_patient_id = "patient_id", col_testcode = "gender", testcodes_exclude = "M", info = TRUE)) # errors expect_error(first_isolate("date", "patient_id", col_mo = "mo")) expect_error(first_isolate(example_isolates, col_date = "non-existing col", col_mo = "mo")) if (AMR:::pkg_is_available("dplyr")) { # if mo is not an mo class, result should be the same expect_identical(example_isolates %>% mutate(mo = as.character(mo)) %>% first_isolate(col_date = "date", col_mo = "mo", col_patient_id = "patient_id", info = FALSE, require_cur_data = TRUE), example_isolates %>% first_isolate(col_date = "date", col_mo = "mo", col_patient_id = "patient_id", info = FALSE, require_cur_data = TRUE)) # support for WHONET expect_message(example_isolates %>% select(-patient_id) %>% mutate(`First name` = "test", `Last name` = "test", Sex = "Female") %>% first_isolate(info = TRUE)) # groups x <- example_isolates %>% group_by(ward_icu) %>% mutate(first = first_isolate(require_cur_data = TRUE)) y <- example_isolates %>% group_by(ward_icu) %>% mutate(first = first_isolate(., require_cur_data = TRUE)) expect_identical(x, y) } # missing dates should be no problem df <- example_isolates df[1:100, "date"] <- NA expect_equal( sum( first_isolate(x = df, col_date = "date", col_patient_id = "patient_id", col_mo = "mo", info = TRUE), na.rm = TRUE), 1382) # unknown MOs test_unknown <- example_isolates test_unknown$mo <- ifelse(test_unknown$mo == "B_ESCHR_COLI", "UNKNOWN", test_unknown$mo) expect_equal(sum(first_isolate(test_unknown, include_unknown = FALSE)), 1108) expect_equal(sum(first_isolate(test_unknown, include_unknown = TRUE)), 1591) test_unknown$mo <- ifelse(test_unknown$mo == "UNKNOWN", NA, test_unknown$mo) expect_equal(sum(first_isolate(test_unknown)), 1108) # empty rsi results expect_equal(sum(first_isolate(example_isolates, include_untested_rsi = FALSE)), 1366) # shortcuts expect_identical(filter_first_isolate(example_isolates), subset(example_isolates, first_isolate(example_isolates))) # notice that all mo's are distinct, so all are TRUE expect_true(all(first_isolate(AMR:::pm_distinct(example_isolates, mo, .keep_all = TRUE), info = TRUE) == TRUE)) # only one isolate, so return fast expect_true(first_isolate(data.frame(mo = "Escherichia coli", date = Sys.Date(), patient = "patient"), info = TRUE))