Update plots.

Author: elinrow

Reporting/Report/Report.qmd

@@ -31,6 +31,8 @@ result <- purrr::map(csv_files, \(x){
   omopgenerics::bind() |>
   omopgenerics::newSummarisedResult()
 
+result$additional_level <- gsub("&&&\\s+&&&", "&&& NULL &&&", result$additional_level)
+
 resultList <- resultList |>
   purrr::map(\(x) {
     omopgenerics::settings(result) |>
@@ -115,9 +117,10 @@ outcome_counts <- data[["incidence"]] |>
     estimate_value = as.numeric(estimate_value)
   )
 
-ggplot2::ggplot(outcome_counts, ggplot2::aes(x = outcome_cohort_name, y = estimate_value, fill = outcome_cohort_name)) +
+ggplot2::ggplot(outcome_counts, ggplot2::aes(x = cdm_name, y = estimate_value, fill = cdm_name)) +
   ggplot2::geom_bar(stat = "identity", colour = "black") +
-  ggplot2::facet_wrap(~ cdm_name, scales = "free") +
+  paletteer::scale_fill_paletteer_d("vapoRwave::vapoRwave") +
+  ggplot2::facet_wrap(~ outcome_cohort_name, scales = "free") +
   ggplot2::theme(axis.text.x = ggplot2::element_blank()) 
 ```
 
@@ -139,23 +142,90 @@ char_3 <- data[["summarise_characteristics"]] |>
     estimate_value = as.numeric(estimate_value)
   ) |>
   dplyr::filter(estimate_name == "percentage",
-                estimate_value >= 10)
+                estimate_value >= 5)
 
 ggplot2::ggplot(char_3, ggplot2::aes(x = variable_level, y = estimate_value, fill = variable_level)) +
   ggplot2::geom_bar(stat = "identity", colour = "black") +
+  paletteer::scale_fill_paletteer_d("vapoRwave::vapoRwave") +
   ggplot2::facet_wrap(~ cdm_name + group_level, scales = "free") +
   ggplot2::theme(axis.text.x = ggplot2::element_blank())
 ```
 
+
+```{r prior use 2, echo=FALSE, message = FALSE, warning = FALSE}
+char_3 <- data[["summarise_characteristics"]] |>
+  dplyr::filter(variable_name == "Antibiotics (-14 to -1)",
+                strata_level == "overall") |>
+  dplyr::mutate(cdm_name = dplyr::case_when(
+    cdm_name == "IDRIL_1" ~ "Lancs",
+    cdm_name == "LTHT" ~ "Leeds",
+    cdm_name == "Barts Health" ~ "Barts",
+    .default = cdm_name
+  ),
+    group_level = stringr::str_replace(group_level, "^\\d+_", ""),
+    group_level = stringr::str_to_sentence(group_level), # capitalize first letter
+    variable_level = stringr::str_replace(variable_level, "^\\d+ ", ""),         # remove leading digits and underscore
+    variable_level = stringr::str_to_sentence(variable_level), # capitalize first letter
+    estimate_value = as.numeric(estimate_value) 
+  ) |>
+  dplyr::filter(estimate_name == "percentage",
+                !is.na(estimate_value),
+                estimate_value >= 5)
+
+ggplot2::ggplot(char_3, ggplot2::aes(x = cdm_name, y = estimate_value, fill = variable_level)) +
+  ggplot2::geom_bar(stat = "identity", colour = "black") +
+  ggplot2::facet_wrap(~ group_level, scales = "free") +
+  ggplot2::theme(
+    axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1)
+  ) +
+  ggplot2::ggtitle("Prior use of access antibiotics (-14 to -1)") +
+  ggplot2::xlab("Database") +
+  ggplot2::ylab("Percentage of Records") +
+  ggplot2::labs(fill = "Access antibiotics") +
+  paletteer::scale_fill_paletteer_d("vapoRwave::vapoRwave")
+```
+```{r prior use 3, echo=FALSE, message = FALSE, warning = FALSE}
+char_3 <- data[["summarise_characteristics"]] |>
+  dplyr::filter(variable_name == "Antibiotics (-14 to -1)",
+                strata_level == "overall") |>
+  dplyr::mutate(cdm_name = dplyr::case_when(
+    cdm_name == "IDRIL_1" ~ "Lancs",
+    cdm_name == "LTHT" ~ "Leeds",
+    cdm_name == "Barts Health" ~ "Barts",
+    .default = cdm_name
+  ),
+    group_level = stringr::str_replace(group_level, "^\\d+_", ""),
+    group_level = stringr::str_to_sentence(group_level), # capitalize first letter
+    variable_level = stringr::str_replace(variable_level, "^\\d+ ", ""),         # remove leading digits and underscore
+    variable_level = stringr::str_to_sentence(variable_level), # capitalize first letter
+    estimate_value = as.numeric(estimate_value) 
+  ) |>
+  dplyr::filter(estimate_name == "percentage",
+                !is.na(estimate_value),
+                estimate_value >= 5)
+
+ggplot2::ggplot(char_3, ggplot2::aes(x = cdm_name, y = estimate_value, fill = variable_level)) +
+  ggplot2::geom_bar(stat = "identity", colour = "black", position = "dodge") +
+  ggplot2::facet_wrap(~ group_level, scales = "free") +
+  ggplot2::theme(
+    axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1)
+  ) +
+  ggplot2::ggtitle("Prior use of access antibiotics (-14 to -1)") +
+  ggplot2::xlab("Database") +
+  ggplot2::ylab("Percentage of Records") +
+  ggplot2::labs(fill = "Access antibiotics") +
+  paletteer::scale_fill_paletteer_d("vapoRwave::vapoRwave")
+```
 ## Figure 3 - Indications
 
 ```{r indications, echo=FALSE, message = FALSE, warning = FALSE}
 char_4 <- data[["summarise_characteristics"]] |>
   dplyr::filter(variable_name == "Indication flag",
                 strata_level == "overall") |>
   dplyr::mutate(cdm_name = dplyr::case_when(
-    cdm_name == "IDRIL_1" ~ "Lancashire",
+    cdm_name == "IDRIL_1" ~ "Lancs",
     cdm_name == "LTHT" ~ "Leeds",
+    cdm_name == "Barts Health" ~ "Barts",
     .default = cdm_name
   ),
     group_level = stringr::str_replace(group_level, "^\\d+_", ""),         # remove leading digits and underscore
@@ -165,14 +235,51 @@ char_4 <- data[["summarise_characteristics"]] |>
     estimate_value = as.numeric(estimate_value)
   ) |>
   dplyr::filter(estimate_name == "percentage",
-                estimate_value >= 10)
+                estimate_value >= 5)
+
+ggplot2::ggplot(char_4, ggplot2::aes(x = cdm_name, y = estimate_value, fill = variable_level)) +
+  ggplot2::geom_bar(stat = "identity", colour = "black", position = "dodge") +
+  ggplot2::facet_wrap(~ group_level, scales = "free") +
+  ggplot2::theme(
+    axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1)
+  ) +
+  ggplot2::ggtitle("Indications of Use") +
+  ggplot2::xlab("Database") +
+  ggplot2::ylab("Percentage of Records") +
+  ggplot2::labs(fill = "Indications") +
+  paletteer::scale_fill_paletteer_d("MetBrewer::Signac")
+```
+```{r indications 2, echo=FALSE, message = FALSE, warning = FALSE}
+char_4 <- data[["summarise_characteristics"]] |>
+  dplyr::filter(variable_name == "Indication flag",
+                strata_level == "overall") |>
+  dplyr::mutate(cdm_name = dplyr::case_when(
+    cdm_name == "IDRIL_1" ~ "Lancs",
+    cdm_name == "LTHT" ~ "Leeds",
+    cdm_name == "Barts Health" ~ "Barts",
+    .default = cdm_name
+  ),
+    group_level = stringr::str_replace(group_level, "^\\d+_", ""),         # remove leading digits and underscore
+    group_level = stringr::str_to_sentence(group_level), # capitalize first letter
+    variable_level = stringr::str_replace(variable_level, "^\\d+ ", ""),         # remove leading digits and underscore
+    variable_level = stringr::str_to_sentence(variable_level), # capitalize first letter
+    estimate_value = as.numeric(estimate_value)
+  ) |>
+  dplyr::filter(estimate_name == "percentage",
+                estimate_value >= 5)
 
-ggplot2::ggplot(char_4, ggplot2::aes(x = group_level, y = estimate_value, fill = group_level)) +
+ggplot2::ggplot(char_4, ggplot2::aes(x = cdm_name, y = estimate_value, fill = variable_level)) +
   ggplot2::geom_bar(stat = "identity", colour = "black") +
-  ggplot2::facet_wrap(~ cdm_name + variable_level, scales = "free") +
-  ggplot2::theme(axis.text.x = ggplot2::element_blank())
+  ggplot2::facet_wrap(~ group_level, scales = "free") +
+  ggplot2::theme(
+    axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1)
+  ) +
+  ggplot2::ggtitle("Indications of Use") +
+  ggplot2::xlab("Database") +
+  ggplot2::ylab("Percentage of Records") +
+  ggplot2::labs(fill = "Indications") +
+  paletteer::scale_fill_paletteer_d("MetBrewer::Signac")
 ```
-
 ## Figure 4 - Incidence of Ciprofloxacin Use
 
 ```{r incidence, echo=FALSE, message = FALSE, warning = FALSE}