pages/2_Samenvatting.py

@@ -4,6 +4,7 @@ import streamlit as st
 from auth import require_auth
 from nightscout_client import NightscoutConfigError
 from reporting import (
+    gmi_mmol_per_mol,
     gmi_percent,
     percent_cv,
     sensor_active_percent,
@@ -43,6 +44,7 @@ active_pct = sensor_active_percent(glucose, start, end)
 
 mean_mmol = glucose["mmol"].mean()
 gmi = gmi_percent(mean_mmol)
+gmi_mmol_mol = gmi_mmol_per_mol(gmi)
 cv = percent_cv(glucose)
 tir = tir_breakdown_5band(glucose)
 
@@ -50,7 +52,11 @@ st.subheader("Kerncijfers")
 col1, col2, col3, col4 = st.columns(4)
 col1.metric("Sensordekking", f"{active_pct:.0f}%", help="Streefwaarde: ≥70%")
 col2.metric("Gemiddelde glucose", f"{mean_mmol:.1f} mmol/L")
-col3.metric("Geschat HbA1c (GMI)", f"{gmi:.1f}%", help="Bergenstal et al. 2018 — geen labwaarde")
+col3.metric(
+    "Geschat HbA1c (GMI)",
+    f"{gmi:.1f}% ({gmi_mmol_mol:.0f} mmol/mol)",
+    help="Bergenstal et al. 2018 — geen labwaarde",
+)
 col4.metric("Variabiliteit (%CV)", f"{cv:.0f}%", help="Streefwaarde: ≤36%")
 
 st.subheader("Tijd in bereik (5 klinische banden)")

pdf_export.py

@@ -28,6 +28,7 @@ from reporting import (
     agp_percentile_bands,
     completeness_warning,
     detect_events,
+    gmi_mmol_per_mol,
     gmi_percent,
     percent_cv,
     sensor_active_percent,
@@ -178,7 +179,8 @@ def _add_summary_section(pdf: FPDF, glucose: pd.DataFrame, start, end) -> None:
     pdf.set_font("Helvetica", "", 11)
     pdf.cell(0, 6, f"Sensordekking: {active_pct:.0f}%", **_LINE_KWARGS)
     pdf.cell(0, 6, f"Gemiddelde glucose: {mean_mmol:.1f} mmol/L", **_LINE_KWARGS)
-    pdf.cell(0, 6, f"Geschat HbA1c (GMI): {gmi_percent(mean_mmol):.1f}%", **_LINE_KWARGS)
+    gmi = gmi_percent(mean_mmol)
+    pdf.cell(0, 6, f"Geschat HbA1c (GMI): {gmi:.1f}% ({gmi_mmol_per_mol(gmi):.0f} mmol/mol)", **_LINE_KWARGS)
     pdf.cell(0, 6, f"Variabiliteit (%CV): {percent_cv(glucose):.0f}%", **_LINE_KWARGS)
     pdf.ln(2)
     pdf.cell(0, 6, f"Zeer laag (<3.0 mmol/L): {tir['very_low']:.0f}%", **_LINE_KWARGS)

reporting.py

@@ -36,6 +36,17 @@ def gmi_percent(mean_mmol: float) -> float:
     return round(3.31 + 0.4311 * mean_mmol, 1)
 
 
+def gmi_mmol_per_mol(gmi_pct: float) -> int:
+    """Zet een GMI-percentage (DCCT/NGSP) om naar IFCC mmol/mol.
+
+    mmol/mol = 10.929 x (% - 2.15) — de standaard IFCC-omrekening
+    (Hoelzel et al. 2004, Clin Chem 50(1):166-174), gangbare eenheid in
+    Nederlandse labuitslagen naast het %-getal (gitea #25). Bijv. 6.5% =
+    48 mmol/mol, de bekende diagnostische drempel.
+    """
+    return round(10.929 * (gmi_pct - 2.15))
+
+
 GMI_TREND_COLUMNS = ["date", "gmi", "rolling_avg", "trend", "trend_lower", "trend_upper"]
 
 

tests/test_reporting.py

@@ -12,6 +12,7 @@ from reporting import (
     daily_gmi,
     day_of_week_pattern,
     detect_events,
+    gmi_mmol_per_mol,
     gmi_percent,
     gmi_trend,
     minutes_per_day,
@@ -35,6 +36,12 @@ def test_gmi_percent_matches_bergenstal_formula():
     assert gmi_percent(7.0) == pytest.approx(6.3, abs=0.05)
 
 
+def test_gmi_mmol_per_mol_matches_known_ifcc_reference_values():
+    # 6.5% is de bekende diagnostische drempel = 48 mmol/mol (IFCC).
+    assert gmi_mmol_per_mol(6.5) == 48
+    assert gmi_mmol_per_mol(7.0) == 53
+
+
 def test_daily_gmi_aggregates_per_calendar_day():
     glucose = _series(
         [