z230

CTMS/PanoramaContacts/filter_state.json

@@ -1,6 +1,6 @@
 {
   "sel_status": "Aktivní",
-  "sel_proto": "42847922MDD3003",
+  "sel_proto": "77242113UCO3001",
   "sel_role": [
     "Principal Investigator",
     "Sub-Investigator",

IWRS/Drugs/create_report.py

@@ -355,12 +355,21 @@ def load_patients(cursor, study):
     mid = cursor.fetchone()["mid"]
     if mid is None:
         raise RuntimeError(f"Žádná data v MySQL pro pacienty {study}")
+    extra_cols = ""
+    if study == "77242113UCO3001":
+        extra_cols = """
+            rescreened_subject                   AS `Rescreened Subject`,
+            adt_ir                               AS `ADT-IR`,
+            three_or_more_advanced_therapies     AS `3+ Adv. Therapies`,
+            only_oral_5asa_compounds             AS `Only 5-ASA`,
+            ustekinumab                          AS `Ustekinumab`,
+            isolated_proctitis                   AS `Isolated Proctitis`,"""
     sql = f"""
         SELECT
             subject                              AS `Subject`,
             investigator                         AS `Investigator`,
             age                                  AS `Subject's age collection`,
-            cohort_per_irt                       AS `Cohort per IRT`,
+            cohort_per_irt                       AS `Cohort per IRT`,{extra_cols}
             irt_subject_status                   AS `IRT Subject Status`,
             last_irt_transaction                 AS `Last Recorded IRT Transaction`,
             next_irt_transaction                 AS `Next Expected IRT Transaction`,
@@ -403,15 +412,30 @@ def _write_prehled(wb, df_raw, study):
     ws = wb.create_sheet("Přehled", 0)
     ws.sheet_view.showGridLines = False
 
-    ws.merge_cells("A1:H1")
+    is_uco = (study == "77242113UCO3001")
+
+    if is_uco:
+        display_headers = ["Subject", "Investigator", "Věk", "Cohort",
+                           "Rescreened", "ADT-IR", "≥3 Adv.Th.", "5-ASA only",
+                           "Uste.", "Isol.Proct.",
+                           "Status", "Last IRT", "Next Visit", "Next Date"]
+        col_widths       = [14, 22, 6, 12, 11, 8, 11, 10, 8, 12, 14, 12, 12, 13]
+        status_col       = 11
+        flag_cols        = set(range(5, 11))  # 1-indexed sloupce s Yes/No hodnotami
+    else:
+        display_headers = ["Subject", "Investigator", "Věk", "Cohort", "Status", "Last IRT", "Next Visit", "Next Date"]
+        col_widths       = [14, 22, 6, 12, 14, 12, 12, 13]
+        status_col       = 5
+        flag_cols        = set()
+
+    last_col = get_column_letter(len(display_headers))
+    ws.merge_cells(f"A1:{last_col}1")
     title = ws["A1"]
     title.value     = f"Subject Summary — {study}   ({date.today().strftime('%d-%b-%Y')})"
     title.font      = Font(name="Arial", bold=True, size=12, color="1F4E79")
     title.alignment = Alignment(horizontal="left", vertical="center")
     ws.row_dimensions[1].height = 22
 
-    display_headers = ["Subject", "Investigator", "Věk", "Cohort", "Status", "Last IRT", "Next Visit", "Next Date"]
-    col_widths       = [14, 22, 6, 12, 14, 12, 12, 13]
     for c, (h, w) in enumerate(zip(display_headers, col_widths), 1):
         cell = ws.cell(row=2, column=c, value=h)
         cell.font = _PAT_HEADER_FONT
@@ -421,16 +445,28 @@ def _write_prehled(wb, df_raw, study):
         ws.column_dimensions[get_column_letter(c)].width = w
     ws.row_dimensions[2].height = 18
 
-    display = pd.DataFrame({
+    base = {
         "Subject":      df_raw["Subject"].fillna(""),
         "Investigator": df_raw["Investigator"].fillna(""),
         "Věk":          df_raw["Subject's age collection"].apply(lambda v: "" if pd.isna(v) else int(v)),
         "Cohort":       df_raw["Cohort per IRT"].apply(_simplify_cohort),
+    }
+    if is_uco:
+        base.update({
+            "Rescreened":  df_raw["Rescreened Subject"].fillna(""),
+            "ADT-IR":      df_raw["ADT-IR"].fillna(""),
+            "≥3 Adv.Th.": df_raw["3+ Adv. Therapies"].fillna(""),
+            "5-ASA only":  df_raw["Only 5-ASA"].fillna(""),
+            "Uste.":       df_raw["Ustekinumab"].fillna(""),
+            "Isol.Proct.": df_raw["Isolated Proctitis"].fillna(""),
+        })
+    base.update({
         "Status":     df_raw["IRT Subject Status"].fillna(""),
         "Last IRT":   df_raw["Last Recorded IRT Transaction"].fillna("—"),
         "Next Visit": df_raw["Next Expected IRT Transaction"].fillna("—"),
         "Next Date":  df_raw["Next Expected IRT Transaction Date [Local]"].apply(_fmt_date),
-    }).sort_values("Subject").reset_index(drop=True)
+    })
+    display = pd.DataFrame(base).sort_values("Subject").reset_index(drop=True)
 
     for r_idx, row in display.iterrows():
         excel_row     = r_idx + 3
@@ -440,17 +476,14 @@ def _write_prehled(wb, df_raw, study):
         is_adolescent = row["Cohort"] == "Adolescent"
         fill = _PAT_EVEN_FILL if r_idx % 2 == 0 else _PAT_ODD_FILL
 
-        values = [row["Subject"], row["Investigator"], row["Věk"],
+        for c_idx, val in enumerate(row, 1):
-                  row["Cohort"], row["Status"], row["Last IRT"],
-                  row["Next Visit"], row["Next Date"]]
-        for c_idx, val in enumerate(values, 1):
             cell = ws.cell(row=excel_row, column=c_idx, value=val if val != "" else None)
             cell.fill      = fill
             cell.border    = _PAT_BORDER
-            cell.alignment = _PAT_CENTER if c_idx == 3 else _PAT_LEFT
+            cell.alignment = _PAT_CENTER if (c_idx == 3 or c_idx in flag_cols) else _PAT_LEFT
             if is_failed:
                 cell.font = _PAT_STRIKE_FONT
-            elif c_idx == 5 and is_randomized:
+            elif c_idx == status_col and is_randomized:
                 cell.font = _PAT_BOLD_FONT
             elif c_idx == 4 and is_adolescent:
                 cell.font = _PAT_ADOLESC_FONT
@@ -459,7 +492,7 @@ def _write_prehled(wb, df_raw, study):
         ws.row_dimensions[excel_row].height = 16
 
     ws.freeze_panes = "A3"
-    ws.auto_filter.ref = f"A2:H{len(display) + 2}"
+    ws.auto_filter.ref = f"A2:{last_col}{len(display) + 2}"
 
 
 def _write_next_visits(wb, df_raw, study):