feat(glucose): add the clinical glucose panel

Surface a clinical panel beneath the blood-glucose chart: time-in-range on the
consensus bands, the glucose management indicator and estimated A1C, and the
coefficient of variation with its instability flag by default, and the J-index
and the low and high blood-glucose risk indices with a per-context breakdown
behind an advanced disclosure. Below the calibration threshold it shows a calm
learning state, and it always carries the spot-reading caveat. The analytics
read, the dashboard snapshot, the coach and the doctor report all consume one
computed result over a fixed window, so the panel, the assistant and the
printed report cannot disagree.

docs/api/openapi.yaml

@@ -13837,6 +13837,8 @@ components:
                   propertyNames:
                     type: string
                   additionalProperties: {}
+                glucoseClinical:
+                  $ref: "#/components/schemas/GlucoseClinicalMetrics"
               required:
                 - bpInTargetPct
                 - bpInTargetPct7d
@@ -13845,6 +13847,7 @@ components:
                 - bpInTargetPctPriorMonth
                 - bpInTargetPctPriorYear
                 - glucoseByContext
+                - glucoseClinical
               additionalProperties: false
             - type: "null"
         medsToday:
@@ -13966,6 +13969,139 @@ components:
         `briefingStale: true`. `layoutCatalogue` (full 27-id widget catalogue) and `metricStates` (latest reading per
         metric, keyed by iOS `MetricKind` raw value) are additive cold-launch seeds for the native client; both derive
         in-process from data already fetched, adding no DB round-trip."
+    GlucoseClinicalMetrics:
+      type: object
+      properties:
+        stillLearning:
+          type: boolean
+        stillLearningReason:
+          anyOf:
+            - type: string
+            - type: "null"
+        windowDays:
+          type: integer
+          minimum: -9007199254740991
+          maximum: 9007199254740991
+        actualSpanDays:
+          type: number
+        readingCount:
+          type: integer
+          minimum: -9007199254740991
+          maximum: 9007199254740991
+        meanMgdl:
+          anyOf:
+            - type: number
+            - type: "null"
+        distribution:
+          anyOf:
+            - type: object
+              properties:
+                tir:
+                  type: number
+                tbrLevel1:
+                  type: number
+                tbrLevel2:
+                  type: number
+                tarLevel1:
+                  type: number
+                tarLevel2:
+                  type: number
+                minutesEquivalent:
+                  type: object
+                  properties:
+                    tir:
+                      type: number
+                    tbrLevel1:
+                      type: number
+                    tbrLevel2:
+                      type: number
+                    tarLevel1:
+                      type: number
+                    tarLevel2:
+                      type: number
+                  required:
+                    - tir
+                    - tbrLevel1
+                    - tbrLevel2
+                    - tarLevel1
+                    - tarLevel2
+                  additionalProperties: false
+              required:
+                - tir
+                - tbrLevel1
+                - tbrLevel2
+                - tarLevel1
+                - tarLevel2
+                - minutesEquivalent
+              additionalProperties: false
+            - type: "null"
+        gmi:
+          anyOf:
+            - type: number
+            - type: "null"
+        estimatedA1c:
+          anyOf:
+            - type: number
+            - type: "null"
+        variability:
+          anyOf:
+            - type: object
+              properties:
+                sd:
+                  type: number
+                cv:
+                  type: number
+                unstable:
+                  type: boolean
+              required:
+                - sd
+                - cv
+                - unstable
+              additionalProperties: false
+            - type: "null"
+        advanced:
+          anyOf:
+            - type: object
+              properties:
+                jIndex:
+                  anyOf:
+                    - type: number
+                    - type: "null"
+                lbgi:
+                  type: number
+                hbgi:
+                  type: number
+              required:
+                - jIndex
+                - lbgi
+                - hbgi
+              additionalProperties: false
+            - type: "null"
+        isSpotEstimate:
+          type: boolean
+          const: true
+      required:
+        - stillLearning
+        - stillLearningReason
+        - windowDays
+        - actualSpanDays
+        - readingCount
+        - meanMgdl
+        - distribution
+        - gmi
+        - estimatedA1c
+        - variability
+        - advanced
+        - isSpotEstimate
+      additionalProperties: false
+      description: Server-authoritative glucose clinical panel over the trailing 30-day window. Every figure is a SPOT-READING
+        ESTIMATE (a % of readings), not a CGM time-in-range AGP — `isSpotEstimate` is always true and `stillLearning`
+        gates assertion when the window has too few readings or too short a span. `distribution` carries the Battelino
+        2019 TIR/TBR/TAR fractions (level-2 nested in level-1) plus minutes-of-a-day equivalents; `gmi` (Bergenstal
+        2018) + `estimatedA1c` (Nathan 2008 ADAG) derive from the mean; `variability` is SD + CV% with the Monnier 2017
+        ≥36% instability flag; `advanced` is the disclosure tier — J-index (Wojcicki 1995) + LBGI/HBGI (Kovatchev
+        hypo/hyper risk). All blocks are null when there are no readings; `advanced.jIndex` is null for a single-reading
+        window.
     InsightsComprehensiveResponseEnvelope:
       type: object
       properties:

messages/de.json

@@ -2826,6 +2826,71 @@
       "emptyState": {
         "title": "Noch keine Glukosedaten",
         "description": "Blutzuckerwerte erscheinen hier, sobald du einen erfasst oder ein Gerät synchronisiert."
+      },
+      "clinical": {
+        "title": "Glukose-Überblick",
+        "subtitle": "Ein Blick auf deine letzten {days} Tage, aus {count} Messungen.",
+        "spotCaveat": "Das sind Schätzungen aus einzelnen Stichproben-Messungen, kein Profil eines kontinuierlichen Sensors – lies sie als Richtung, nicht als klinisches Urteil.",
+        "learningTitle": "Lerne deine Glukose noch kennen",
+        "learningBody": "Bisher sind das {count} über {days}. Mit etwas mehr Verlauf wird das Bild klarer – mess weiter oder lass es ein verbundenes Gerät ergänzen.",
+        "learningBodyEmpty": "Sobald ein paar Messungen vorliegen – von dir erfasst oder von einem Gerät synchronisiert – nehmen Zeit-im-Zielbereich, Durchschnitt und Schwankung hier Gestalt an.",
+        "readingsCount": "{count} Messungen",
+        "readingsCountOne": "1 Messung",
+        "daysCount": "{days} Tage",
+        "daysCountOne": "1 Tag",
+        "tir": {
+          "title": "Zeit im Zielbereich",
+          "caption": "Anteil der Messungen je Bereich (70–180 mg/dl ist das Ziel).",
+          "veryLow": "Sehr niedrig",
+          "low": "Niedrig",
+          "inRange": "Im Zielbereich",
+          "high": "Hoch",
+          "veryHigh": "Sehr hoch",
+          "ariaLabel": "Zeit im Zielbereich: {tir}% im Ziel, {below}% darunter, {above}% darüber.",
+          "empty": "Noch keine Messungen für das Diagramm."
+        },
+        "gmi": {
+          "label": "Glukose-Management-Indikator",
+          "help": "Eine HbA1c-ähnliche Schätzung aus deiner durchschnittlichen Glukose."
+        },
+        "eA1c": {
+          "label": "Geschätzter HbA1c",
+          "help": "Eine HbA1c-Schätzung aus deinem mittleren Glukosewert (ADAG)."
+        },
+        "mean": {
+          "label": "Durchschnittliche Glukose"
+        },
+        "cv": {
+          "label": "Schwankung",
+          "steady": "Stabil",
+          "unstable": "Instabil",
+          "help": "Variationskoeffizient. Ab 36 % gilt die Glukose als instabil; niedriger ist stabiler."
+        },
+        "advanced": {
+          "toggle": "Erweiterte Indizes",
+          "intro": "Forschungsnahe Kennzahlen für den genaueren Blick. Jede fasst deine Messungen zu einer risikogewichteten Zahl zusammen.",
+          "jIndex": {
+            "label": "J-Index",
+            "help": "Ein einzelner Wert aus Durchschnitt und Streuung – niedriger steht für engere Kontrolle."
+          },
+          "lbgi": {
+            "label": "Risiko für Tiefwerte (LBGI)",
+            "help": "Kovatchevs Index, gewichtet danach, wie oft und wie tief Werte ins Tief rutschen."
+          },
+          "hbgi": {
+            "label": "Risiko für Hochwerte (HBGI)",
+            "help": "Kovatchevs Index, gewichtet danach, wie oft und wie hoch Werte steigen."
+          },
+          "byContext": {
+            "title": "Nach Kontext",
+            "fasting": "Nüchtern",
+            "postprandial": "Nach dem Essen",
+            "random": "Beliebig",
+            "bedtime": "Vor dem Schlafen",
+            "readingsShort": "{count} Messungen",
+            "readingsShortOne": "1 Messung"
+          }
+        }
       }
     },
     "navBloodGlucose": "Glukose",

messages/en.json

@@ -2826,6 +2826,71 @@
       "emptyState": {
         "title": "No glucose data yet",
         "description": "Blood-glucose readings appear here once you log one or a connected device syncs."
+      },
+      "clinical": {
+        "title": "Glucose overview",
+        "subtitle": "A read on your last {days} days, from {count} readings.",
+        "spotCaveat": "These are spot-reading estimates from individual measurements, not a continuous-monitor profile — read them as a direction of travel rather than a clinical verdict.",
+        "learningTitle": "Still learning your glucose",
+        "learningBody": "So far that's {count} over {days}. A little more history and a fuller picture comes into focus — keep logging, or let a connected device fill it in.",
+        "learningBodyEmpty": "Once a handful of readings come in — logged by you or synced from a device — your time-in-range, average, and variability take shape here.",
+        "readingsCount": "{count} readings",
+        "readingsCountOne": "1 reading",
+        "daysCount": "{days} days",
+        "daysCountOne": "1 day",
+        "tir": {
+          "title": "Time in range",
+          "caption": "Share of readings in each band (70–180 mg/dL is the target).",
+          "veryLow": "Very low",
+          "low": "Low",
+          "inRange": "In range",
+          "high": "High",
+          "veryHigh": "Very high",
+          "ariaLabel": "Time in range: {tir}% in target, {below}% below, {above}% above.",
+          "empty": "No readings to chart yet."
+        },
+        "gmi": {
+          "label": "Glucose Management Indicator",
+          "help": "An A1C-like estimate derived from your average glucose."
+        },
+        "eA1c": {
+          "label": "Estimated A1C",
+          "help": "An A1C estimate from your mean glucose (ADAG)."
+        },
+        "mean": {
+          "label": "Average glucose"
+        },
+        "cv": {
+          "label": "Variability",
+          "steady": "Steady",
+          "unstable": "Unstable",
+          "help": "Coefficient of variation. At or above 36% glucose is considered unstable; lower is steadier."
+        },
+        "advanced": {
+          "toggle": "Advanced indices",
+          "intro": "Research-grade composites for a closer look. Each folds your readings into a single risk-weighted number.",
+          "jIndex": {
+            "label": "J-index",
+            "help": "A single score blending your average and its spread — lower reads as tighter control."
+          },
+          "lbgi": {
+            "label": "Low-glucose risk (LBGI)",
+            "help": "Kovatchev's index weighting how often and how deeply readings dip low."
+          },
+          "hbgi": {
+            "label": "High-glucose risk (HBGI)",
+            "help": "Kovatchev's index weighting how often and how high readings climb."
+          },
+          "byContext": {
+            "title": "By context",
+            "fasting": "Fasting",
+            "postprandial": "After meals",
+            "random": "Random",
+            "bedtime": "Bedtime",
+            "readingsShort": "{count} readings",
+            "readingsShortOne": "1 reading"
+          }
+        }
       }
     },
     "navBloodGlucose": "Glucose",

messages/es.json

@@ -2826,6 +2826,71 @@
       "emptyState": {
         "title": "Aún no hay datos de glucosa",
         "description": "Las lecturas de glucosa aparecen aquí cuando registras una o un dispositivo sincroniza."
+      },
+      "clinical": {
+        "title": "Resumen de glucosa",
+        "subtitle": "Una lectura de tus últimos {days} días, a partir de {count} mediciones.",
+        "spotCaveat": "Son estimaciones a partir de mediciones puntuales, no un perfil de un sensor continuo: léelas como una tendencia, no como un veredicto clínico.",
+        "learningTitle": "Aún conociendo tu glucosa",
+        "learningBody": "De momento son {count} en {days}. Con algo más de historial el panorama se aclara: sigue registrando o deja que lo complete un dispositivo conectado.",
+        "learningBodyEmpty": "En cuanto lleguen unas cuantas mediciones —registradas por ti o sincronizadas desde un dispositivo— tu tiempo en rango, promedio y variabilidad tomarán forma aquí.",
+        "readingsCount": "{count} mediciones",
+        "readingsCountOne": "1 medición",
+        "daysCount": "{days} días",
+        "daysCountOne": "1 día",
+        "tir": {
+          "title": "Tiempo en rango",
+          "caption": "Proporción de mediciones en cada banda (70–180 mg/dl es el objetivo).",
+          "veryLow": "Muy bajo",
+          "low": "Bajo",
+          "inRange": "En rango",
+          "high": "Alto",
+          "veryHigh": "Muy alto",
+          "ariaLabel": "Tiempo en rango: {tir}% en objetivo, {below}% por debajo, {above}% por encima.",
+          "empty": "Aún no hay mediciones para el gráfico."
+        },
+        "gmi": {
+          "label": "Indicador de gestión de la glucosa",
+          "help": "Una estimación tipo HbA1c derivada de tu glucosa promedio."
+        },
+        "eA1c": {
+          "label": "HbA1c estimada",
+          "help": "Una estimación de HbA1c a partir de tu glucosa media (ADAG)."
+        },
+        "mean": {
+          "label": "Glucosa promedio"
+        },
+        "cv": {
+          "label": "Variabilidad",
+          "steady": "Estable",
+          "unstable": "Inestable",
+          "help": "Coeficiente de variación. A partir del 36 % la glucosa se considera inestable; menos es más estable."
+        },
+        "advanced": {
+          "toggle": "Índices avanzados",
+          "intro": "Compuestos de nivel investigador para mirar más de cerca. Cada uno reduce tus mediciones a un único número ponderado por riesgo.",
+          "jIndex": {
+            "label": "Índice J",
+            "help": "Una puntuación única que combina tu promedio y su dispersión: cuanto más bajo, más ajustado el control."
+          },
+          "lbgi": {
+            "label": "Riesgo de hipoglucemia (LBGI)",
+            "help": "Índice de Kovatchev que pondera con qué frecuencia y profundidad bajan las lecturas."
+          },
+          "hbgi": {
+            "label": "Riesgo de hiperglucemia (HBGI)",
+            "help": "Índice de Kovatchev que pondera con qué frecuencia y altura suben las lecturas."
+          },
+          "byContext": {
+            "title": "Por contexto",
+            "fasting": "En ayunas",
+            "postprandial": "Después de comer",
+            "random": "Aleatorio",
+            "bedtime": "Antes de dormir",
+            "readingsShort": "{count} mediciones",
+            "readingsShortOne": "1 medición"
+          }
+        }
       }
     },
     "navBloodGlucose": "Glucosa",

messages/fr.json

@@ -2826,6 +2826,71 @@
       "emptyState": {
         "title": "Aucune donnée de glycémie",
         "description": "Les relevés de glycémie apparaissent ici dès que vous en saisissez un ou qu’un appareil se synchronise."
+      },
+      "clinical": {
+        "title": "Aperçu du glucose",
+        "subtitle": "Un point sur vos {days} derniers jours, à partir de {count} mesures.",
+        "spotCaveat": "Ce sont des estimations issues de mesures ponctuelles, pas le profil d’un capteur continu : lisez-les comme une tendance, non comme un verdict clinique.",
+        "learningTitle": "Votre glucose se découvre encore",
+        "learningBody": "Pour l’instant, cela fait {count} sur {days}. Avec un peu plus d’historique, le tableau se précise : continuez à enregistrer ou laissez un appareil connecté compléter.",
+        "learningBodyEmpty": "Dès que quelques mesures arrivent — saisies par vous ou synchronisées depuis un appareil — votre temps dans la cible, votre moyenne et votre variabilité prennent forme ici.",
+        "readingsCount": "{count} mesures",
+        "readingsCountOne": "1 mesure",
+        "daysCount": "{days} jours",
+        "daysCountOne": "1 jour",
+        "tir": {
+          "title": "Temps dans la cible",
+          "caption": "Part des mesures dans chaque plage (70–180 mg/dl est la cible).",
+          "veryLow": "Très bas",
+          "low": "Bas",
+          "inRange": "Dans la cible",
+          "high": "Élevé",
+          "veryHigh": "Très élevé",
+          "ariaLabel": "Temps dans la cible : {tir}% dans la cible, {below}% en dessous, {above}% au-dessus.",
+          "empty": "Pas encore de mesures à afficher."
+        },
+        "gmi": {
+          "label": "Indicateur de gestion du glucose",
+          "help": "Une estimation de type HbA1c dérivée de votre glucose moyen."
+        },
+        "eA1c": {
+          "label": "HbA1c estimée",
+          "help": "Une estimation d’HbA1c à partir de votre glucose moyen (ADAG)."
+        },
+        "mean": {
+          "label": "Glucose moyen"
+        },
+        "cv": {
+          "label": "Variabilité",
+          "steady": "Stable",
+          "unstable": "Instable",
+          "help": "Coefficient de variation. À partir de 36 %, le glucose est considéré comme instable ; plus bas est plus stable."
+        },
+        "advanced": {
+          "toggle": "Indices avancés",
+          "intro": "Des indicateurs de niveau recherche pour regarder de plus près. Chacun condense vos mesures en un seul chiffre pondéré par le risque.",
+          "jIndex": {
+            "label": "Indice J",
+            "help": "Un score unique mêlant votre moyenne et sa dispersion — plus il est bas, plus le contrôle est serré."
+          },
+          "lbgi": {
+            "label": "Risque d’hypoglycémie (LBGI)",
+            "help": "Indice de Kovatchev pondérant la fréquence et la profondeur des baisses."
+          },
+          "hbgi": {
+            "label": "Risque d’hyperglycémie (HBGI)",
+            "help": "Indice de Kovatchev pondérant la fréquence et la hauteur des hausses."
+          },
+          "byContext": {
+            "title": "Par contexte",
+            "fasting": "À jeun",
+            "postprandial": "Après les repas",
+            "random": "Aléatoire",
+            "bedtime": "Au coucher",
+            "readingsShort": "{count} mesures",
+            "readingsShortOne": "1 mesure"
+          }
+        }
       }
     },
     "navBloodGlucose": "Glucose",

messages/it.json

@@ -2826,6 +2826,71 @@
       "emptyState": {
         "title": "Nessun dato di glicemia",
         "description": "Le letture di glicemia appaiono qui quando ne registri una o un dispositivo si sincronizza."
+      },
+      "clinical": {
+        "title": "Panoramica della glicemia",
+        "subtitle": "Una lettura dei tuoi ultimi {days} giorni, da {count} misurazioni.",
+        "spotCaveat": "Sono stime da singole misurazioni puntuali, non il profilo di un sensore continuo: leggile come una tendenza, non come un verdetto clinico.",
+        "learningTitle": "Stiamo ancora imparando la tua glicemia",
+        "learningBody": "Per ora sono {count} su {days}. Con un po’ più di storico il quadro si chiarisce: continua a registrare o lascia che lo completi un dispositivo connesso.",
+        "learningBodyEmpty": "Appena arrivano alcune misurazioni — registrate da te o sincronizzate da un dispositivo — il tempo nel range, la media e la variabilità prendono forma qui.",
+        "readingsCount": "{count} misurazioni",
+        "readingsCountOne": "1 misurazione",
+        "daysCount": "{days} giorni",
+        "daysCountOne": "1 giorno",
+        "tir": {
+          "title": "Tempo nel range",
+          "caption": "Quota di misurazioni in ciascuna fascia (70–180 mg/dl è l’obiettivo).",
+          "veryLow": "Molto basso",
+          "low": "Basso",
+          "inRange": "Nel range",
+          "high": "Alto",
+          "veryHigh": "Molto alto",
+          "ariaLabel": "Tempo nel range: {tir}% a target, {below}% sotto, {above}% sopra.",
+          "empty": "Ancora nessuna misurazione da mostrare."
+        },
+        "gmi": {
+          "label": "Indicatore di gestione della glicemia",
+          "help": "Una stima simile all’HbA1c derivata dalla tua glicemia media."
+        },
+        "eA1c": {
+          "label": "HbA1c stimata",
+          "help": "Una stima dell’HbA1c dalla tua glicemia media (ADAG)."
+        },
+        "mean": {
+          "label": "Glicemia media"
+        },
+        "cv": {
+          "label": "Variabilità",
+          "steady": "Stabile",
+          "unstable": "Instabile",
+          "help": "Coefficiente di variazione. Dal 36 % la glicemia è considerata instabile; più basso è più stabile."
+        },
+        "advanced": {
+          "toggle": "Indici avanzati",
+          "intro": "Indicatori di livello scientifico per uno sguardo più ravvicinato. Ognuno riduce le tue misurazioni a un singolo numero ponderato sul rischio.",
+          "jIndex": {
+            "label": "Indice J",
+            "help": "Un punteggio unico che combina media e dispersione: più è basso, più stretto è il controllo."
+          },
+          "lbgi": {
+            "label": "Rischio di ipoglicemia (LBGI)",
+            "help": "Indice di Kovatchev che pesa quanto spesso e quanto in basso scendono le letture."
+          },
+          "hbgi": {
+            "label": "Rischio di iperglicemia (HBGI)",
+            "help": "Indice di Kovatchev che pesa quanto spesso e quanto in alto salgono le letture."
+          },
+          "byContext": {
+            "title": "Per contesto",
+            "fasting": "A digiuno",
+            "postprandial": "Dopo i pasti",
+            "random": "Casuale",
+            "bedtime": "Prima di dormire",
+            "readingsShort": "{count} misurazioni",
+            "readingsShortOne": "1 misurazione"
+          }
+        }
       }
     },
     "navBloodGlucose": "Glucosio",

messages/pl.json

@@ -2826,6 +2826,71 @@
       "emptyState": {
         "title": "Brak danych o glukozie",
         "description": "Odczyty glukozy pojawią się tutaj po zapisaniu jednego lub synchronizacji urządzenia."
+      },
+      "clinical": {
+        "title": "Przegląd glukozy",
+        "subtitle": "Spojrzenie na ostatnie {days} dni, na podstawie {count} pomiarów.",
+        "spotCaveat": "To szacunki z pojedynczych pomiarów punktowych, a nie profil z czujnika ciągłego — traktuj je jako kierunek, nie jako diagnozę.",
+        "learningTitle": "Wciąż poznajemy Twoją glukozę",
+        "learningBody": "Na razie to {count} w ciągu {days}. Przy nieco dłuższej historii obraz się wyostrza — rejestruj dalej lub pozwól uzupełnić to podłączonemu urządzeniu.",
+        "learningBodyEmpty": "Gdy pojawi się kilka pomiarów — wpisanych przez Ciebie lub zsynchronizowanych z urządzenia — czas w zakresie, średnia i zmienność nabiorą tu kształtu.",
+        "readingsCount": "{count} pomiarów",
+        "readingsCountOne": "1 pomiar",
+        "daysCount": "{days} dni",
+        "daysCountOne": "1 dzień",
+        "tir": {
+          "title": "Czas w zakresie",
+          "caption": "Udział pomiarów w każdym przedziale (70–180 mg/dl to cel).",
+          "veryLow": "Bardzo niski",
+          "low": "Niski",
+          "inRange": "W zakresie",
+          "high": "Wysoki",
+          "veryHigh": "Bardzo wysoki",
+          "ariaLabel": "Czas w zakresie: {tir}% w celu, {below}% poniżej, {above}% powyżej.",
+          "empty": "Brak pomiarów do wykresu."
+        },
+        "gmi": {
+          "label": "Wskaźnik zarządzania glukozą",
+          "help": "Szacunek zbliżony do HbA1c na podstawie średniej glukozy."
+        },
+        "eA1c": {
+          "label": "Szacowane HbA1c",
+          "help": "Szacunek HbA1c na podstawie średniej glukozy (ADAG)."
+        },
+        "mean": {
+          "label": "Średnia glukoza"
+        },
+        "cv": {
+          "label": "Zmienność",
+          "steady": "Stabilna",
+          "unstable": "Niestabilna",
+          "help": "Współczynnik zmienności. Od 36 % glukozę uznaje się za niestabilną; niżej znaczy stabilniej."
+        },
+        "advanced": {
+          "toggle": "Wskaźniki zaawansowane",
+          "intro": "Złożone miary o poziomie badawczym dla bliższego spojrzenia. Każda sprowadza Twoje pomiary do jednej liczby ważonej ryzykiem.",
+          "jIndex": {
+            "label": "Indeks J",
+            "help": "Pojedynczy wynik łączący średnią i jej rozrzut — niższy oznacza ściślejszą kontrolę."
+          },
+          "lbgi": {
+            "label": "Ryzyko niedocukrzeń (LBGI)",
+            "help": "Indeks Kovatcheva ważący, jak często i jak głęboko odczyty spadają."
+          },
+          "hbgi": {
+            "label": "Ryzyko przecukrzeń (HBGI)",
+            "help": "Indeks Kovatcheva ważący, jak często i jak wysoko odczyty rosną."
+          },
+          "byContext": {
+            "title": "Wg kontekstu",
+            "fasting": "Na czczo",
+            "postprandial": "Po posiłku",
+            "random": "Losowy",
+            "bedtime": "Przed snem",
+            "readingsShort": "{count} pomiarów",
+            "readingsShortOne": "1 pomiar"
+          }
+        }
       }
     },
     "navBloodGlucose": "Glukoza",

src/app/api/analytics/route.ts

@@ -20,6 +20,10 @@ import { computeUserHealthScoreFastPath } from "@/lib/analytics/health-score-fas
 import { buildHealthScoreBpInputs } from "@/lib/analytics/health-score-inputs";
 import { deriveBpWindow90 } from "@/lib/analytics/window-confidence";
 import { computeCorrelationHypothesesFastPath } from "@/lib/analytics/correlations-fast-path";
+import {
+  computeGlucoseClinicalMetrics,
+  type GlucoseClinicalMetrics,
+} from "@/lib/analytics/glucose-metrics";
 
 export const dynamic = "force-dynamic";
 
@@ -365,6 +369,19 @@ async function buildAnalyticsResponse(user: AuthedUser) {
     }
   }
 
+  // v1.17.0 — server-authoritative glucose clinical panel. The TIR / GMI /
+  // eA1C / CV% headline and the advanced J-index + LBGI/HBGI tier are computed
+  // ONCE here over the declared 30-day window (matching `glucoseSince`) so the
+  // insights panel, the coach snapshot, and the doctor report all render the
+  // same numbers instead of each re-deriving. The learning gate keeps a thin
+  // spot-data window from being asserted as a clinical AGP. Always present in
+  // the payload (even with zero readings) so the client renders the calm
+  // "still learning" state from a populated object rather than a missing key.
+  const glucoseClinical: GlucoseClinicalMetrics = computeGlucoseClinicalMetrics(
+    glucoseRows.map((r) => ({ measuredAt: r.measuredAt, mgdl: r.value })),
+    { windowDays: 30, now: new Date() },
+  );
+
   // v1.4.20 phase B3 — three pre-defined correlation hypotheses.
   // v1.4.37 W2 — probe-gated helper. The 28-day scan window (down
   // from 30 to keep the cold critical path tight while still
@@ -420,6 +437,7 @@ async function buildAnalyticsResponse(user: AuthedUser) {
     bpInTargetCount90,
     bpInTargetSpanDays90,
     glucoseByContext,
+    glucoseClinical,
     correlations,
     healthScore,
     sleepStages,

src/app/insights/blood-glucose/page.tsx

@@ -3,6 +3,7 @@
 import { Droplet } from "lucide-react";
 
 import { HealthKitMetricPage } from "@/components/insights/healthkit-metric-page";
+import { GlucoseClinicalPanel } from "@/components/insights/glucose/glucose-clinical-panel";
 import { useAuth } from "@/hooks/use-auth";
 import { useTranslations } from "@/lib/i18n/context";
 import { resolveGlucoseUnit } from "@/lib/glucose";
@@ -51,6 +52,7 @@ export default function InsightsBlutzuckerPage() {
       emptyStateIcon={<Droplet className="size-6" />}
       emptyStateCtaType={null}
       targetSummarySlug="blood-glucose"
+      afterChart={<GlucoseClinicalPanel />}
       coachPrefill="I haven't logged any blood glucose yet — what does this metric tell me about my health, and how do I improve it?"
     />
   );

src/components/clinician/__tests__/clinician-view.test.tsx

@@ -12,6 +12,7 @@ import { ClinicianView } from "../clinician-view";
 import { getServerTranslator } from "@/lib/i18n/server-translator";
 import { DEFAULT_DOCTOR_REPORT_PREFS } from "@/lib/validations/doctor-report-prefs";
 import type { DoctorReportData } from "@/lib/doctor-report-data";
+import { computeGlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
 
 function makeReport(
   overrides: Partial<DoctorReportData> = {},
@@ -36,6 +37,9 @@ function makeReport(
     },
     glucoseStats: {},
     glucoseRanges: {},
+    glucoseClinical: computeGlucoseClinicalMetrics([], {
+      now: new Date("2026-01-31T00:00:00.000Z"),
+    }),
     glucoseUnit: "mg/dL",
     bmi: 24.5,
     compliance: {},

src/components/insights/glucose/__tests__/glucose-clinical-panel.test.tsx

@@ -0,0 +1,217 @@
+import { describe, it, expect, vi, beforeEach } from "vitest";
+import { renderToStaticMarkup } from "react-dom/server";
+
+import { I18nProvider } from "@/lib/i18n/context";
+import { computeGlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
+import type { DataSummary } from "@/lib/analytics/trends";
+import { GlucoseTirBar } from "../glucose-tir-bar";
+import { GlucoseAdvancedDisclosure } from "../glucose-advanced-disclosure";
+
+/** Minimal valid `DataSummary` — the panel + disclosure only read `count`. */
+function summary(count: number): DataSummary {
+  return {
+    count,
+    latest: 95,
+    min: 60,
+    max: 140,
+    mean: 100,
+    median: 98,
+    avg7: null,
+    avg30: null,
+    slope7: null,
+    slope30: null,
+    slope90: null,
+    anomalyCount: 0,
+  };
+}
+
+/**
+ * v1.17.0 — glucose clinical panel render tests.
+ *
+ * Covers the two states the maintainer called out: the calm "still learning"
+ * branch (no asserted TIR / GMI off thin spot data) and the asserted branch
+ * with the advanced progressive disclosure. The panel leans on `useAuth` +
+ * `useAnalyticsQuery`; both are mocked so the branch under test is
+ * deterministic. The TIR bar + advanced disclosure are pure props, tested
+ * directly.
+ */
+
+const authMock = vi.fn();
+vi.mock("@/hooks/use-auth", () => ({
+  useAuth: () => authMock(),
+}));
+
+const analyticsMock = vi.fn();
+vi.mock("@/lib/queries/use-analytics-query", () => ({
+  useAnalyticsQuery: () => analyticsMock(),
+}));
+
+// Import after the mocks are registered.
+const { GlucoseClinicalPanel } = await import("../glucose-clinical-panel");
+
+function render(node: React.ReactNode, locale: "en" | "de" = "en") {
+  return renderToStaticMarkup(
+    <I18nProvider initialLocale={locale}>{node}</I18nProvider>,
+  );
+}
+
+const NOW = new Date("2026-06-14T12:00:00Z");
+const DAY = 24 * 60 * 60 * 1000;
+
+beforeEach(() => {
+  authMock.mockReturnValue({
+    user: { glucoseUnit: "mg/dL" },
+    isAuthenticated: true,
+  });
+  analyticsMock.mockReset();
+});
+
+describe("<GlucoseClinicalPanel> learning state", () => {
+  it("renders the calm still-learning copy and asserts NO TIR/GMI", () => {
+    // 5 readings over 4 days — below the 14-reading default floor.
+    const readings = [100, 110, 120, 130, 140].map((mgdl, i) => ({
+      measuredAt: new Date(NOW.getTime() - (4 - i) * DAY),
+      mgdl,
+    }));
+    const glucoseClinical = computeGlucoseClinicalMetrics(readings, { now: NOW });
+    expect(glucoseClinical.stillLearning).toBe(true);
+
+    analyticsMock.mockReturnValue({
+      isLoading: false,
+      data: { glucoseClinical, glucoseByContext: {} },
+    });
+
+    const html = render(<GlucoseClinicalPanel />);
+    expect(html).toContain('data-state="learning"');
+    expect(html).toContain("Still learning your glucose");
+    // the asserted blocks must NOT be present in the learning state
+    expect(html).not.toContain("data-slot=\"glucose-tir-bar\"");
+    expect(html).not.toContain("Glucose Management Indicator");
+    // the spot-reading caveat is always carried
+    expect(html).toContain("spot-reading estimates");
+  });
+
+  it("renders the empty learning copy when there are zero readings", () => {
+    const glucoseClinical = computeGlucoseClinicalMetrics([], { now: NOW });
+    analyticsMock.mockReturnValue({
+      isLoading: false,
+      data: { glucoseClinical, glucoseByContext: {} },
+    });
+    const html = render(<GlucoseClinicalPanel />);
+    expect(html).toContain('data-state="learning"');
+    expect(html).toContain("Once a handful of readings come in");
+  });
+});
+
+describe("<GlucoseClinicalPanel> asserted state", () => {
+  function assertedClinical() {
+    // 20 readings, one per day → clears the gate; a spread that lands in all
+    // three TIR bands so the bar has real segments and CV% is non-trivial.
+    const values = [
+      60, 90, 120, 150, 180, 200, 100, 110, 95, 130, 170, 220, 80, 140, 160,
+      105, 115, 125, 135, 145,
+    ];
+    const readings = values.map((mgdl, i) => ({
+      measuredAt: new Date(NOW.getTime() - (values.length - 1 - i) * DAY),
+      mgdl,
+    }));
+    return computeGlucoseClinicalMetrics(readings, { now: NOW, windowDays: 30 });
+  }
+
+  it("renders TIR bar, GMI, eA1C, a CV badge, and the advanced disclosure", () => {
+    const glucoseClinical = assertedClinical();
+    expect(glucoseClinical.stillLearning).toBe(false);
+
+    analyticsMock.mockReturnValue({
+      isLoading: false,
+      data: {
+        glucoseClinical,
+        glucoseByContext: {
+          FASTING: summary(8),
+        },
+      },
+    });
+
+    const html = render(<GlucoseClinicalPanel />);
+    expect(html).toContain('data-state="asserted"');
+    expect(html).toContain('data-slot="glucose-tir-bar"');
+    expect(html).toContain("Glucose Management Indicator");
+    expect(html).toContain("Estimated A1C");
+    expect(html).toContain('data-slot="glucose-cv-badge"');
+    // advanced disclosure trigger is present (region collapsed by default in SSR)
+    expect(html).toContain('data-slot="glucose-advanced-toggle"');
+    expect(html).toContain("aria-expanded=\"false\"");
+    expect(html).toContain("J-index");
+  });
+
+  it("flags the CV badge unstable at CV% >= 36", () => {
+    // wide spread → CV well above 36
+    const values = Array.from({ length: 20 }, (_, i) =>
+      i % 2 === 0 ? 60 : 260,
+    );
+    const readings = values.map((mgdl, i) => ({
+      measuredAt: new Date(NOW.getTime() - (values.length - 1 - i) * DAY),
+      mgdl,
+    }));
+    const glucoseClinical = computeGlucoseClinicalMetrics(readings, {
+      now: NOW,
+      windowDays: 30,
+    });
+    expect(glucoseClinical.variability?.unstable).toBe(true);
+
+    analyticsMock.mockReturnValue({
+      isLoading: false,
+      data: { glucoseClinical, glucoseByContext: {} },
+    });
+    const html = render(<GlucoseClinicalPanel />);
+    expect(html).toContain('data-unstable="true"');
+    expect(html).toContain("Unstable");
+  });
+
+  it("renders nothing when the thick slice carries no glucoseClinical", () => {
+    analyticsMock.mockReturnValue({ isLoading: false, data: { summaries: {} } });
+    const html = render(<GlucoseClinicalPanel />);
+    expect(html).toBe("");
+  });
+});
+
+describe("<GlucoseTirBar>", () => {
+  it("renders one segment per non-empty Battelino band summing to 100%", () => {
+    const dist = computeGlucoseClinicalMetrics(
+      [40, 60, 120, 200, 300].map((mgdl, i) => ({
+        measuredAt: new Date(NOW.getTime() - i * DAY),
+        mgdl,
+      })),
+      { now: NOW, minReadings: 1, minSpanDays: 1 },
+    ).distribution!;
+    const html = render(<GlucoseTirBar distribution={dist} />);
+    // very-low (40), low (60), in-range (120), high (200), very-high (300)
+    expect(html).toContain("glucose-tir-segment-veryLow");
+    expect(html).toContain("glucose-tir-segment-low");
+    expect(html).toContain("glucose-tir-segment-inRange");
+    expect(html).toContain("glucose-tir-segment-high");
+    expect(html).toContain("glucose-tir-segment-veryHigh");
+    // aria summary present
+    expect(html).toContain('role="img"');
+  });
+});
+
+describe("<GlucoseAdvancedDisclosure>", () => {
+  it("is collapsed by default and exposes a toggle + the three indices", () => {
+    const html = render(
+      <GlucoseAdvancedDisclosure
+        advanced={{ jIndex: 23.7, lbgi: 1.2, hbgi: 6.8 }}
+        byContext={{
+          FASTING: summary(1),
+        }}
+      />,
+    );
+    expect(html).toContain('aria-expanded="false"');
+    expect(html).toContain("hidden"); // region hidden in initial SSR state
+    expect(html).toContain("J-index");
+    expect(html).toContain("LBGI");
+    expect(html).toContain("HBGI");
+    // singular reading label for a single-reading context
+    expect(html).toContain("1 reading");
+  });
+});

src/components/insights/glucose/glucose-advanced-disclosure.tsx

@@ -0,0 +1,159 @@
+"use client";
+
+import { useId, useState } from "react";
+import { ChevronDown } from "lucide-react";
+
+import { useTranslations } from "@/lib/i18n/context";
+import { cn } from "@/lib/utils";
+import type { GlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
+import type { DataSummary } from "@/lib/analytics/trends";
+
+/**
+ * v1.17.0 — "advanced" progressive disclosure for the glucose panel.
+ *
+ * The default panel view leads with TIR / GMI / eA1C / CV%. The research-grade
+ * composites the maintainer chose for v1.17.0 — J-index (Wojcicki) and the
+ * Kovatchev low/high blood-glucose risk indices — live behind this disclosure
+ * so a casual user is not confronted with them, while a clinician or an engaged
+ * user can open them. Per-context reading counts ride along so the advanced
+ * view also answers "where do these readings come from". Values are computed
+ * server-side; this only renders them.
+ *
+ * No Collapsible primitive exists in the UI kit, so this is a minimal,
+ * accessible button + region disclosure (the same pattern other insights cards
+ * use): `aria-expanded` on the trigger, `aria-controls`/`hidden` on the region.
+ */
+
+const CONTEXT_LABEL_KEYS: Record<string, string> = {
+  FASTING: "insights.bloodGlucose.clinical.advanced.byContext.fasting",
+  POSTPRANDIAL: "insights.bloodGlucose.clinical.advanced.byContext.postprandial",
+  RANDOM: "insights.bloodGlucose.clinical.advanced.byContext.random",
+  BEDTIME: "insights.bloodGlucose.clinical.advanced.byContext.bedtime",
+};
+
+export interface GlucoseAdvancedDisclosureProps {
+  advanced: NonNullable<GlucoseClinicalMetrics["advanced"]>;
+  /** Per-context summaries keyed by `GlucoseContext`; optional. */
+  byContext?: Record<string, DataSummary> | undefined;
+  /** Decimals for the index values. Defaults to 1. */
+  fractionDigits?: number;
+}
+
+export function GlucoseAdvancedDisclosure({
+  advanced,
+  byContext,
+  fractionDigits = 1,
+}: GlucoseAdvancedDisclosureProps) {
+  const { t } = useTranslations();
+  const [open, setOpen] = useState(false);
+  const regionId = useId();
+
+  const fmt = (v: number | null) =>
+    v === null ? "—" : v.toFixed(fractionDigits);
+
+  const contexts = Object.entries(byContext ?? {}).filter(
+    ([, s]) => s && s.count > 0,
+  );
+
+  return (
+    <div data-slot="glucose-advanced" className="border-border border-t pt-3">
+      <button
+        type="button"
+        onClick={() => setOpen((v) => !v)}
+        aria-expanded={open}
+        aria-controls={regionId}
+        data-slot="glucose-advanced-toggle"
+        className="text-muted-foreground hover:text-foreground flex min-h-11 w-full items-center justify-between gap-2 text-sm font-medium transition-colors"
+      >
+        <span>{t("insights.bloodGlucose.clinical.advanced.toggle")}</span>
+        <ChevronDown
+          aria-hidden="true"
+          className={cn(
+            "h-4 w-4 transition-transform",
+            open && "rotate-180",
+          )}
+        />
+      </button>
+
+      <div
+        id={regionId}
+        hidden={!open}
+        data-slot="glucose-advanced-region"
+        className="space-y-4 pt-3"
+      >
+        <p className="text-muted-foreground text-xs">
+          {t("insights.bloodGlucose.clinical.advanced.intro")}
+        </p>
+
+        <dl className="grid grid-cols-3 gap-3">
+          <AdvancedStat
+            label={t("insights.bloodGlucose.clinical.advanced.jIndex.label")}
+            help={t("insights.bloodGlucose.clinical.advanced.jIndex.help")}
+            value={fmt(advanced.jIndex)}
+          />
+          <AdvancedStat
+            label={t("insights.bloodGlucose.clinical.advanced.lbgi.label")}
+            help={t("insights.bloodGlucose.clinical.advanced.lbgi.help")}
+            value={fmt(advanced.lbgi)}
+          />
+          <AdvancedStat
+            label={t("insights.bloodGlucose.clinical.advanced.hbgi.label")}
+            help={t("insights.bloodGlucose.clinical.advanced.hbgi.help")}
+            value={fmt(advanced.hbgi)}
+          />
+        </dl>
+
+        {contexts.length > 0 ? (
+          <div className="space-y-2" data-slot="glucose-advanced-context">
+            <p className="text-foreground text-xs font-medium">
+              {t("insights.bloodGlucose.clinical.advanced.byContext.title")}
+            </p>
+            <ul className="text-muted-foreground space-y-1 text-xs">
+              {contexts.map(([ctx, summary]) => (
+                <li
+                  key={ctx}
+                  className="flex items-center justify-between gap-2"
+                >
+                  <span>
+                    {CONTEXT_LABEL_KEYS[ctx] ? t(CONTEXT_LABEL_KEYS[ctx]) : ctx}
+                  </span>
+                  <span className="tabular-nums">
+                    {summary.count === 1
+                      ? t(
+                          "insights.bloodGlucose.clinical.advanced.byContext.readingsShortOne",
+                        )
+                      : t(
+                          "insights.bloodGlucose.clinical.advanced.byContext.readingsShort",
+                          { count: summary.count },
+                        )}
+                  </span>
+                </li>
+              ))}
+            </ul>
+          </div>
+        ) : null}
+      </div>
+    </div>
+  );
+}
+
+function AdvancedStat({
+  label,
+  help,
+  value,
+}: {
+  label: string;
+  help: string;
+  value: string;
+}) {
+  return (
+    <div className="space-y-0.5">
+      <dt className="text-muted-foreground text-xs" title={help}>
+        {label}
+      </dt>
+      <dd className="text-foreground text-base font-semibold tabular-nums">
+        {value}
+      </dd>
+    </div>
+  );
+}

src/components/insights/glucose/glucose-clinical-panel.tsx

@@ -0,0 +1,254 @@
+"use client";
+
+import { Activity, Droplet, TrendingUp } from "lucide-react";
+
+import { Badge } from "@/components/ui/badge";
+import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
+import { Skeleton } from "@/components/ui/skeleton";
+import { useAuth } from "@/hooks/use-auth";
+import { useAnalyticsQuery } from "@/lib/queries/use-analytics-query";
+import { useTranslations } from "@/lib/i18n/context";
+import { convertGlucose, resolveGlucoseUnit } from "@/lib/glucose";
+import type { DataSummary } from "@/lib/analytics/trends";
+import { GlucoseTirBar } from "./glucose-tir-bar";
+import { GlucoseAdvancedDisclosure } from "./glucose-advanced-disclosure";
+
+/**
+ * v1.17.0 — glucose clinical panel.
+ *
+ * The default view leads with the three numbers that matter to a person
+ * managing glucose: time-in-range (Battelino bands, as a stacked bar), a GMI +
+ * estimated-A1C pair, and a variability badge that flags "unstable" at CV% ≥ 36
+ * (Monnier). The advanced indices (J-index, LBGI/HBGI) sit behind a calm
+ * disclosure. Every number is server-computed by the one literature-locked
+ * engine — the panel renders verbatim and never re-derives.
+ *
+ * Honesty contract: HealthLog stores SPOT readings, not a CGM trace, so the
+ * copy always carries the "spot-reading estimate" caveat, and a thin window
+ * shows a warm "still learning" state instead of asserting a clinical profile.
+ * Tone follows the cycle-phase texts: warm, professional, grounded — never
+ * alarmist, never breezy.
+ *
+ * Reads the thick `/api/analytics` payload directly (the slim slice does not
+ * carry `glucoseClinical`); the cache cell is shared with the dashboard so the
+ * mount is usually a free hit.
+ */
+export function GlucoseClinicalPanel() {
+  const { user, isAuthenticated } = useAuth();
+  const { t } = useTranslations();
+  const query = useAnalyticsQuery({});
+
+  const glucoseUnit = resolveGlucoseUnit(user?.glucoseUnit ?? null);
+  const isMmol = glucoseUnit === "mmol/L";
+
+  if (!isAuthenticated) return null;
+
+  if (query.isLoading) {
+    return (
+      <Card data-slot="glucose-clinical-panel-skeleton">
+        <CardHeader className="pb-2">
+          <Skeleton className="h-5 w-40" />
+        </CardHeader>
+        <CardContent className="space-y-4">
+          <Skeleton className="h-6 w-full" />
+          <div className="grid grid-cols-3 gap-3">
+            <Skeleton className="h-12" />
+            <Skeleton className="h-12" />
+            <Skeleton className="h-12" />
+          </div>
+        </CardContent>
+      </Card>
+    );
+  }
+
+  const clinical = query.data?.glucoseClinical;
+  // No glucose data at all, or the thick slice did not carry the block — the
+  // page's own empty state already covers the truly-no-data case, so render
+  // nothing rather than a redundant card.
+  if (!clinical) return null;
+
+  const byContext = query.data?.glucoseByContext as
+    | Record<string, DataSummary>
+    | undefined;
+
+  const formatGlucoseValue = (mgdl: number): string => {
+    const v = convertGlucose(mgdl, glucoseUnit);
+    return isMmol ? v.toFixed(1) : String(Math.round(v));
+  };
+
+  // Learning state — calm, never asserting TIR / GMI off thin data.
+  if (clinical.stillLearning) {
+    const hasAny = clinical.readingCount > 0;
+    const readingsLabel =
+      clinical.readingCount === 1
+        ? t("insights.bloodGlucose.clinical.readingsCountOne")
+        : t("insights.bloodGlucose.clinical.readingsCount", {
+            count: clinical.readingCount,
+          });
+    const spanDays = Math.max(1, Math.round(clinical.actualSpanDays));
+    const daysLabel =
+      spanDays === 1
+        ? t("insights.bloodGlucose.clinical.daysCountOne")
+        : t("insights.bloodGlucose.clinical.daysCount", { days: spanDays });
+
+    return (
+      <Card data-slot="glucose-clinical-panel" data-state="learning">
+        <CardHeader className="pb-2">
+          <CardTitle className="flex items-center gap-2 text-base font-semibold">
+            <Droplet className="h-4 w-4" aria-hidden="true" />
+            {t("insights.bloodGlucose.clinical.learningTitle")}
+          </CardTitle>
+        </CardHeader>
+        <CardContent className="space-y-3">
+          <p className="text-muted-foreground text-sm" data-slot="glucose-learning-body">
+            {hasAny
+              ? t("insights.bloodGlucose.clinical.learningBody", {
+                  count: readingsLabel,
+                  days: daysLabel,
+                })
+              : t("insights.bloodGlucose.clinical.learningBodyEmpty")}
+          </p>
+          <p className="text-muted-foreground/80 text-xs">
+            {t("insights.bloodGlucose.clinical.spotCaveat")}
+          </p>
+        </CardContent>
+      </Card>
+    );
+  }
+
+  // Asserted view.
+  const dist = clinical.distribution;
+  const cv = clinical.variability;
+
+  return (
+    <Card data-slot="glucose-clinical-panel" data-state="asserted">
+      <CardHeader className="pb-2">
+        <div className="flex flex-col gap-0.5">
+          <CardTitle className="flex items-center gap-2 text-base font-semibold">
+            <Droplet className="h-4 w-4" aria-hidden="true" />
+            {t("insights.bloodGlucose.clinical.title")}
+          </CardTitle>
+          <span className="text-muted-foreground text-xs">
+            {t("insights.bloodGlucose.clinical.subtitle", {
+              days: Math.max(1, Math.round(clinical.actualSpanDays)),
+              count: clinical.readingCount,
+            })}
+          </span>
+        </div>
+      </CardHeader>
+      <CardContent className="space-y-5">
+        {/* Time in range */}
+        {dist ? (
+          <section className="space-y-2" data-slot="glucose-tir-section">
+            <div className="flex items-center justify-between gap-2">
+              <h3 className="text-foreground text-sm font-medium">
+                {t("insights.bloodGlucose.clinical.tir.title")}
+              </h3>
+            </div>
+            <GlucoseTirBar distribution={dist} />
+            <p className="text-muted-foreground text-xs">
+              {t("insights.bloodGlucose.clinical.tir.caption")}
+            </p>
+          </section>
+        ) : null}
+
+        {/* Headline metrics */}
+        <section className="grid grid-cols-2 gap-3 sm:grid-cols-4" data-slot="glucose-headline">
+          {clinical.meanMgdl !== null ? (
+            <Metric
+              icon={<Droplet className="h-3.5 w-3.5" aria-hidden="true" />}
+              label={t("insights.bloodGlucose.clinical.mean.label")}
+              value={formatGlucoseValue(clinical.meanMgdl)}
+              unit={glucoseUnit}
+            />
+          ) : null}
+          {clinical.gmi !== null ? (
+            <Metric
+              icon={<Activity className="h-3.5 w-3.5" aria-hidden="true" />}
+              label={t("insights.bloodGlucose.clinical.gmi.label")}
+              help={t("insights.bloodGlucose.clinical.gmi.help")}
+              value={clinical.gmi.toFixed(1)}
+              unit="%"
+            />
+          ) : null}
+          {clinical.estimatedA1c !== null ? (
+            <Metric
+              icon={<TrendingUp className="h-3.5 w-3.5" aria-hidden="true" />}
+              label={t("insights.bloodGlucose.clinical.eA1c.label")}
+              help={t("insights.bloodGlucose.clinical.eA1c.help")}
+              value={clinical.estimatedA1c.toFixed(1)}
+              unit="%"
+            />
+          ) : null}
+          {cv ? (
+            <div className="space-y-0.5" data-slot="glucose-cv">
+              <span
+                className="text-muted-foreground flex items-center gap-1 text-xs"
+                title={t("insights.bloodGlucose.clinical.cv.help")}
+              >
+                {t("insights.bloodGlucose.clinical.cv.label")}
+              </span>
+              <div className="flex items-center gap-1.5">
+                <span className="text-foreground text-lg font-semibold tabular-nums">
+                  {Math.round(cv.cv)}%
+                </span>
+                <Badge
+                  variant={cv.unstable ? "destructive" : "secondary"}
+                  data-slot="glucose-cv-badge"
+                  data-unstable={cv.unstable}
+                >
+                  {cv.unstable
+                    ? t("insights.bloodGlucose.clinical.cv.unstable")
+                    : t("insights.bloodGlucose.clinical.cv.steady")}
+                </Badge>
+              </div>
+            </div>
+          ) : null}
+        </section>
+
+        {/* Spot-reading honesty caveat — always present. */}
+        <p className="text-muted-foreground/80 text-xs" data-slot="glucose-spot-caveat">
+          {t("insights.bloodGlucose.clinical.spotCaveat")}
+        </p>
+
+        {/* Advanced indices behind a disclosure. */}
+        {clinical.advanced ? (
+          <GlucoseAdvancedDisclosure
+            advanced={clinical.advanced}
+            byContext={byContext}
+          />
+        ) : null}
+      </CardContent>
+    </Card>
+  );
+}
+
+function Metric({
+  icon,
+  label,
+  help,
+  value,
+  unit,
+}: {
+  icon: React.ReactNode;
+  label: string;
+  help?: string;
+  value: string;
+  unit: string;
+}) {
+  return (
+    <div className="space-y-0.5">
+      <span
+        className="text-muted-foreground flex items-center gap-1 text-xs"
+        title={help}
+      >
+        {icon}
+        {label}
+      </span>
+      <span className="text-foreground flex items-baseline gap-1">
+        <span className="text-lg font-semibold tabular-nums">{value}</span>
+        <span className="text-muted-foreground text-xs">{unit}</span>
+      </span>
+    </div>
+  );
+}

src/components/insights/glucose/glucose-tir-bar.tsx

@@ -0,0 +1,102 @@
+"use client";
+
+import { useTranslations } from "@/lib/i18n/context";
+import type { TimeInRangeDistribution } from "@/lib/analytics/glucose-metrics";
+
+/**
+ * v1.17.0 — Battelino 2019 time-in-range stacked bar.
+ *
+ * A single horizontal 100%-width bar split into the five consensus bands
+ * (very low / low / in range / high / very high), bottom-to-top severity
+ * read left-to-right with the in-range band centred and dominant. Fractions
+ * arrive already computed by the server engine — this component only renders
+ * them, it never re-derives a band. The level-2 sub-bands are NESTED inside
+ * level-1 in the source distribution (TBR2 ⊆ TBR1, TAR2 ⊆ TAR1), so the
+ * segment widths here use the EXCLUSIVE slices to fill exactly 100%.
+ */
+
+const BAND_COLORS = {
+  veryLow: "#ff5555", // dracula-red — urgent low
+  low: "#ffb86c", // dracula-orange — low
+  inRange: "#50fa7b", // dracula-green — target
+  high: "#f1fa8c", // dracula-yellow — high
+  veryHigh: "#ff79c6", // dracula-pink — urgent high
+} as const;
+
+type BandKey = keyof typeof BAND_COLORS;
+
+export interface GlucoseTirBarProps {
+  distribution: TimeInRangeDistribution;
+}
+
+export function GlucoseTirBar({ distribution }: GlucoseTirBarProps) {
+  const { t } = useTranslations();
+
+  // Exclusive slices from the nested consensus fractions: level-2 is a subset
+  // of level-1, so the level-1-only slice = level1 − level2.
+  const veryLow = distribution.tbrLevel2;
+  const low = Math.max(0, distribution.tbrLevel1 - distribution.tbrLevel2);
+  const inRange = distribution.tir;
+  const high = Math.max(0, distribution.tarLevel1 - distribution.tarLevel2);
+  const veryHigh = distribution.tarLevel2;
+
+  const segments: Array<{ key: BandKey; label: string; fraction: number }> = [
+    { key: "veryLow", label: t("insights.bloodGlucose.clinical.tir.veryLow"), fraction: veryLow },
+    { key: "low", label: t("insights.bloodGlucose.clinical.tir.low"), fraction: low },
+    { key: "inRange", label: t("insights.bloodGlucose.clinical.tir.inRange"), fraction: inRange },
+    { key: "high", label: t("insights.bloodGlucose.clinical.tir.high"), fraction: high },
+    { key: "veryHigh", label: t("insights.bloodGlucose.clinical.tir.veryHigh"), fraction: veryHigh },
+  ];
+
+  const pct = (f: number) => Math.round(f * 100);
+  const ariaLabel = t("insights.bloodGlucose.clinical.tir.ariaLabel", {
+    tir: pct(inRange),
+    below: pct(distribution.tbrLevel1),
+    above: pct(distribution.tarLevel1),
+  });
+
+  return (
+    <div data-slot="glucose-tir-bar" className="space-y-2">
+      <div
+        role="img"
+        aria-label={ariaLabel}
+        className="bg-muted flex h-6 w-full overflow-hidden rounded-md"
+      >
+        {segments.map((s) =>
+          s.fraction > 0 ? (
+            <div
+              key={s.key}
+              data-slot={`glucose-tir-segment-${s.key}`}
+              className="h-full"
+              style={{
+                width: `${s.fraction * 100}%`,
+                background: BAND_COLORS[s.key],
+              }}
+              title={`${s.label} · ${pct(s.fraction)}%`}
+            />
+          ) : null,
+        )}
+      </div>
+      <ul
+        className="text-muted-foreground grid grid-cols-2 gap-x-4 gap-y-1 text-xs sm:grid-cols-3"
+        data-slot="glucose-tir-legend"
+      >
+        {segments.map((s) => (
+          <li key={s.key} className="flex items-center justify-between gap-2">
+            <span className="flex items-center gap-1.5">
+              <span
+                aria-hidden="true"
+                className="inline-block h-2 w-2 rounded-sm"
+                style={{ background: BAND_COLORS[s.key] }}
+              />
+              {s.label}
+            </span>
+            <span className="text-foreground tabular-nums font-medium">
+              {pct(s.fraction)}%
+            </span>
+          </li>
+        ))}
+      </ul>
+    </div>
+  );
+}

src/components/insights/healthkit-metric-page.tsx

@@ -154,6 +154,15 @@ export interface HealthKitMetricPageProps {
    * 90-day p50 is not read as an all-time central value.
    */
   statMedianLabel?: string;
+  /**
+   * v1.17.0 — optional extra content rendered beneath the chart + target
+   * summary, before the metric-status card. Blood glucose mounts its clinical
+   * panel (TIR / GMI / eA1C / CV% + advanced indices) here. Only rendered on
+   * the data-bearing branch (the empty / loading / error branches skip it, so
+   * a no-data metric never shows a void panel). Additive: every other page
+   * omits it and renders byte-identically.
+   */
+  afterChart?: ReactNode;
 }
 
 export function HealthKitMetricPage({
@@ -176,6 +185,7 @@ export function HealthKitMetricPage({
   forecast = false,
   statFractionDigits,
   statMedianLabel,
+  afterChart,
 }: HealthKitMetricPageProps) {
   const { user, isAuthenticated } = useAuth();
   const { t } = useTranslations();
@@ -337,6 +347,9 @@ export function HealthKitMetricPage({
       {targetSummarySlug ? (
         <MetricTargetSummary slug={targetSummarySlug} />
       ) : null}
+      {/* v1.17.0 — page-specific extra block (blood glucose: the clinical
+          panel). Mounted on the data-bearing branch only. */}
+      {afterChart}
       {forecast && isTrajectoryType(measurementType) ? (
         <TrajectoryForecastCard
           type={measurementType}

src/lib/__tests__/doctor-report-pdf-core.test.ts

@@ -10,6 +10,7 @@ import {
 } from "../doctor-report-pdf-core";
 import { measurementTypeEnum } from "../validations/measurement";
 import type { DoctorReportData } from "../doctor-report-data";
+import { computeGlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
 import { getServerTranslator } from "../i18n/server-translator";
 
 async function extractText(bytes: Uint8Array): Promise<string> {
@@ -67,6 +68,7 @@ function makeData(overrides?: Partial<DoctorReportData>): DoctorReportData {
       FASTING: { avg: 92, min: 85, max: 100, count: 4, latest: 90 },
     },
     glucoseRanges: { FASTING: { min: 70, max: 99 } },
+    glucoseClinical: computeGlucoseClinicalMetrics([], { now: FIXED_NOW }),
     glucoseUnit: "mg/dL",
     bmi: 24.1,
     compliance: {

src/lib/ai/coach/snapshot.ts

@@ -24,6 +24,7 @@ import {
 } from "@/lib/validations/coach-prefs";
 import { DEFAULT_TIMEZONE } from "@/lib/tz/resolver";
 import { convertGlucose, resolveGlucoseUnit } from "@/lib/glucose";
+import { computeGlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
 import {
   reconstructSleepNights,
   type SleepStageRow,
@@ -80,6 +81,15 @@ const DAILY_TIMELINE_DAYS = 14;
 /** Default window when the caller doesn't pass a scope. */
 const DEFAULT_WINDOW: CoachScopeWindow = "last30days";
 
+/**
+ * v1.17.0 — the glucose clinical panel is a fixed trailing-30-day artifact,
+ * identical across the insights panel, the dashboard snapshot, the doctor
+ * report, and (here) the coach. Pinned independently of the coach's variable
+ * narration window so the coach's TIR/GMI/CV% always equals what the panel
+ * renders.
+ */
+const GLUCOSE_CLINICAL_WINDOW_DAYS = 30;
+
 /**
  * v1.7.0 — assembled-snapshot soft char cap. After the snapshot is
  * built we measure `JSON.stringify(snapshot).length` as a ~4-chars-per-
@@ -846,6 +856,29 @@ async function buildCoachSnapshotImpl(
         },
       })
     : null;
+  // v1.17.0 — the glucose CLINICAL panel is a fixed 30-day clinical artifact,
+  // identical to the one the insights panel + doctor report render. It must NOT
+  // ride the coach's variable narration window (7/30/90/365) or the
+  // multi-cluster timeline cap, or the coach would quote a TIR/GMI/CV% the panel
+  // never shows. So read the panel's own trailing-30-day glucose rows directly
+  // (one indexed query, only when glucose is active) and compute the clinical
+  // block off THOSE rows. The per-context narration timelines below keep using
+  // the coach-window rows — only the clinical summary is pinned to 30 days.
+  const glucoseClinicalCutoff = new Date(
+    now.getTime() - GLUCOSE_CLINICAL_WINDOW_DAYS * 24 * 60 * 60 * 1000,
+  );
+  const glucoseClinicalRowsPromise = sources.has("glucose")
+    ? prisma.measurement.findMany({
+        where: {
+          userId,
+          type: "BLOOD_GLUCOSE" as never,
+          measuredAt: { gte: glucoseClinicalCutoff },
+          deletedAt: null,
+        },
+        orderBy: { measuredAt: "asc" },
+        select: { value: true, measuredAt: true },
+      })
+    : null;
   const glp1BlockPromise = excludesMedications
     ? null
     : buildGlp1SnapshotBlock(userId, now);
@@ -879,6 +912,7 @@ async function buildCoachSnapshotImpl(
     complianceMeds,
     sleepRows,
     workoutRows,
+    glucoseClinicalRows,
     glp1Block,
     derivedBlock,
     trajectoryBlock,
@@ -889,6 +923,7 @@ async function buildCoachSnapshotImpl(
     complianceMedsPromise,
     sleepRowsPromise,
     workoutRowsPromise,
+    glucoseClinicalRowsPromise,
     glp1BlockPromise,
     derivedBlockPromise,
     trajectoryBlockPromise,
@@ -1344,9 +1379,70 @@ async function buildCoachSnapshotImpl(
         );
         contexts[ctx] = { recent, weekly };
       }
+      // v1.17.0 — clinical panel summary from the ONE literature-locked engine
+      // the insights panel + doctor report also consume, computed over the SAME
+      // fixed trailing-30-day window + rows the panel uses (`glucoseClinicalRows`,
+      // not the coach-window / cap-trimmed `glucoseRows`), so the coach can never
+      // quote a TIR / GMI / CV% figure the panel doesn't show — true numeric
+      // parity, independent of the user's coach scope. Gated by `stillLearning`
+      // so a thin spot-data window is offered as a calm "still learning" note
+      // rather than asserted as a clinical AGP. The headline mean is converted
+      // ONCE to the user's display unit; the unit-agnostic fractions / indices
+      // travel as-is.
+      const clinicalRaw = computeGlucoseClinicalMetrics(
+        (glucoseClinicalRows ?? []).map((r) => ({
+          measuredAt: r.measuredAt,
+          mgdl: r.value,
+        })),
+        { windowDays: GLUCOSE_CLINICAL_WINDOW_DAYS, now },
+      );
+      const clinical = clinicalRaw.stillLearning
+        ? {
+            stillLearning: true as const,
+            reason: clinicalRaw.stillLearningReason,
+            readingCount: clinicalRaw.readingCount,
+            spanDays: Math.round(clinicalRaw.actualSpanDays),
+          }
+        : {
+            stillLearning: false as const,
+            windowDays: clinicalRaw.windowDays,
+            spanDays: Math.round(clinicalRaw.actualSpanDays),
+            readingCount: clinicalRaw.readingCount,
+            meanInRange:
+              clinicalRaw.meanMgdl !== null
+                ? Math.round(
+                    convertGlucose(clinicalRaw.meanMgdl, glucoseUnit) *
+                      (glucoseUnit === "mmol/L" ? 10 : 1),
+                  ) / (glucoseUnit === "mmol/L" ? 10 : 1)
+                : null,
+            tirPercent: clinicalRaw.distribution
+              ? Math.round(clinicalRaw.distribution.tir * 100)
+              : null,
+            timeBelowPercent: clinicalRaw.distribution
+              ? Math.round(clinicalRaw.distribution.tbrLevel1 * 100)
+              : null,
+            timeAbovePercent: clinicalRaw.distribution
+              ? Math.round(clinicalRaw.distribution.tarLevel1 * 100)
+              : null,
+            gmi:
+              clinicalRaw.gmi !== null
+                ? Math.round(clinicalRaw.gmi * 10) / 10
+                : null,
+            estimatedA1c:
+              clinicalRaw.estimatedA1c !== null
+                ? Math.round(clinicalRaw.estimatedA1c * 10) / 10
+                : null,
+            cvPercent: clinicalRaw.variability
+              ? Math.round(clinicalRaw.variability.cv)
+              : null,
+            unstable: clinicalRaw.variability?.unstable ?? null,
+            // Spot-reading estimate, never a CGM AGP — pinned so the model
+            // never narrates these as continuous-trace clinical figures.
+            isSpotEstimate: true as const,
+          };
       // The display unit travels with the block so the prompt renders
       // "<value> <unit>" and the EVIDENCE BLOCK tags glucose lines correctly.
-      snapshot.glucose = { unit: glucoseUnit, byContext: contexts };
+      snapshot.glucose = { unit: glucoseUnit, byContext: contexts, clinical };
       metrics.add("glucose");
       counts.glucose = glucoseRows.length;
       registerBlock("glucose", "glucose");

src/lib/analytics/__tests__/glucose-metrics.test.ts

@@ -10,11 +10,13 @@ import { describe, expect, it } from "vitest";
 import {
   CV_INSTABILITY_THRESHOLD,
   DEFAULT_WINDOW_DAYS,
+  bloodGlucoseRiskIndices,
   computeGlucoseClinicalMetrics,
   estimatedA1c,
   glucoseSD,
   glucoseVariability,
   gmi,
+  jIndex,
   timeInRange,
   type GlucoseReading,
 } from "../glucose-metrics";
@@ -128,6 +130,51 @@ describe("timeInRange (Battelino 2019 bands)", () => {
   });
 });
 
+describe("jIndex (Wojcicki 1995)", () => {
+  it("returns null for fewer than two values", () => {
+    expect(jIndex([])).toBeNull();
+    expect(jIndex([120])).toBeNull();
+  });
+
+  it("folds mean + SD: J = 0.001 × (mean + SD)²", () => {
+    // 14 identical 154 readings → SD 0 → J = 0.001 × 154² = 23.716
+    expect(jIndex(Array.from({ length: 14 }, () => 154))).toBeCloseTo(
+      23.716,
+      3,
+    );
+    // {100,110,120,130,140}: mean 120, sample SD √250 = 15.81139 →
+    // J = 0.001 × 135.81139² = 18.444733
+    expect(jIndex([100, 110, 120, 130, 140])).toBeCloseTo(18.444733, 5);
+  });
+});
+
+describe("bloodGlucoseRiskIndices (Kovatchev 1997/2006)", () => {
+  it("returns null when no usable reading remains", () => {
+    expect(bloodGlucoseRiskIndices([])).toBeNull();
+    // non-positive / non-finite readings are skipped (ln undefined)
+    expect(bloodGlucoseRiskIndices([0, -5, NaN])).toBeNull();
+  });
+
+  it("splits a low/high pair onto the correct branches", () => {
+    // f(50) = -1.500015 → low branch r = 22.500445
+    // f(300) = 1.842607 → high branch r = 33.951988
+    // n = 2 → LBGI = 22.500445/2 = 11.250223, HBGI = 33.951988/2 = 16.975994
+    const r = bloodGlucoseRiskIndices([50, 300]);
+    expect(r).not.toBeNull();
+    expect(r!.lbgi).toBeCloseTo(11.250223, 5);
+    expect(r!.hbgi).toBeCloseTo(16.975994, 5);
+  });
+
+  it("reads near-zero hypo risk and zero hyper risk for a stable normoglycaemic set", () => {
+    // every reading sits below the ~112.5 symmetrization centre, so HBGI = 0
+    const r = bloodGlucoseRiskIndices([100, 110, 95, 105, 100]);
+    expect(r!.hbgi).toBe(0);
+    expect(r!.lbgi).toBeCloseTo(0.427869, 5);
+    // minimal-risk band (< 1.1)
+    expect(r!.lbgi).toBeLessThan(1.1);
+  });
+});
+
 describe("computeGlucoseClinicalMetrics — window + adequacy", () => {
   const now = new Date("2026-06-14T12:00:00Z");
 
@@ -155,6 +202,26 @@ describe("computeGlucoseClinicalMetrics — window + adequacy", () => {
     expect(m.readingCount).toBe(1);
   });
 
+  it("excludes non-positive readings so every index shares one denominator", () => {
+    // a 0 / negative glucose is non-physiological and ln-undefined; it must be
+    // dropped from readingCount AND from the risk-index denominator so the
+    // advanced indices never use a different N than mean / TIR.
+    const readings: GlucoseReading[] = [
+      { mgdl: 120, measuredAt: new Date(now.getTime() - 1 * DAY) },
+      { mgdl: 0, measuredAt: new Date(now.getTime() - 2 * DAY) },
+      { mgdl: -5, measuredAt: new Date(now.getTime() - 3 * DAY) },
+    ];
+    const m = computeGlucoseClinicalMetrics(readings, {
+      now,
+      minReadings: 1,
+      minSpanDays: 0,
+    });
+    expect(m.readingCount).toBe(1);
+    expect(m.meanMgdl).toBe(120);
+    // advanced indices resolve from the single usable reading
+    expect(m.advanced).not.toBeNull();
+  });
+
   it("always marks the result as a spot estimate", () => {
     const m = computeGlucoseClinicalMetrics(
       dailyReadings([100], now),
@@ -173,6 +240,7 @@ describe("computeGlucoseClinicalMetrics — window + adequacy", () => {
       expect(m.gmi).toBeNull();
       expect(m.estimatedA1c).toBeNull();
       expect(m.variability).toBeNull();
+      expect(m.advanced).toBeNull();
     });
 
     it("fires below the minimum reading count, reporting N and D", () => {
@@ -220,6 +288,26 @@ describe("computeGlucoseClinicalMetrics — window + adequacy", () => {
       expect(m.distribution!.tir).toBeCloseTo(1, 10); // all in range
       expect(m.variability!.sd).toBe(0);
       expect(m.variability!.unstable).toBe(false);
+      // advanced tier: J-index from mean+SD, LBGI/HBGI from the risk model.
+      // mean 154, SD 0 → J = 0.001 × 154² = 23.716.
+      expect(m.advanced).not.toBeNull();
+      expect(m.advanced!.jIndex).toBeCloseTo(23.716, 3);
+      // 154 mg/dL sits above the symmetrization centre → all hyper risk,
+      // zero hypo risk.
+      expect(m.advanced!.lbgi).toBe(0);
+      expect(m.advanced!.hbgi).toBeGreaterThan(0);
+    });
+
+    it("resolves LBGI/HBGI but holds J-index null for a single reading", () => {
+      const m = computeGlucoseClinicalMetrics(dailyReadings([100], now), {
+        now,
+      });
+      expect(m.advanced).not.toBeNull();
+      // one reading → sample SD undefined → J held null
+      expect(m.advanced!.jIndex).toBeNull();
+      // the risk indices still resolve from the lone reading
+      expect(m.advanced!.hbgi).toBe(0);
+      expect(m.advanced!.lbgi).toBeGreaterThan(0);
     });
 
     it("honours configurable thresholds", () => {

src/lib/analytics/__tests__/glucose-panel-coherence.test.ts

@@ -0,0 +1,132 @@
+/**
+ * v1.17.0 — glucose panel coherence.
+ *
+ * The server-authoritative contract: the insights panel, the AI coach, and the
+ * doctor-report PDF all read ONE computed `computeGlucoseClinicalMetrics`
+ * result for the same readings — none re-derives a clinical number. This test
+ * pins that invariant by deriving each surface's headline numbers from the SAME
+ * engine output and asserting they agree:
+ *
+ *   - panel   → renders `gmi` / `estimatedA1c` / `distribution.tir` / `cv`
+ *               verbatim (rounded for display only).
+ *   - coach   → `snapshot.glucose.clinical` rounds `gmi` (1dp), `tirPercent`
+ *               (whole %), `cvPercent` (whole %) from the same result.
+ *   - doctor  → `glucoseClinical` IS the engine result, carried whole.
+ *
+ * Because the three consumers all call the one pure function, identical
+ * readings MUST produce identical headline figures. The projections below
+ * mirror the rounding each surface applies; the assertions prove no surface can
+ * drift onto a different denominator or formula.
+ */
+import { describe, expect, it } from "vitest";
+import { computeGlucoseClinicalMetrics } from "../glucose-metrics";
+
+const NOW = new Date("2026-06-14T12:00:00Z");
+const DAY = 24 * 60 * 60 * 1000;
+
+/** A spread that clears the learning gate and lands in all three TIR bands. */
+const VALUES = [
+  60, 90, 120, 150, 180, 200, 100, 110, 95, 130, 170, 220, 80, 140, 160, 105,
+  115, 125, 135, 145,
+];
+
+function readings() {
+  return VALUES.map((mgdl, i) => ({
+    measuredAt: new Date(NOW.getTime() - (VALUES.length - 1 - i) * DAY),
+    mgdl,
+  }));
+}
+
+/** Coach projection — mirrors `snapshot.glucose.clinical` (asserted branch). */
+function coachProjection(
+  m: ReturnType<typeof computeGlucoseClinicalMetrics>,
+) {
+  return {
+    tirPercent: m.distribution ? Math.round(m.distribution.tir * 100) : null,
+    gmi: m.gmi !== null ? Math.round(m.gmi * 10) / 10 : null,
+    estimatedA1c:
+      m.estimatedA1c !== null ? Math.round(m.estimatedA1c * 10) / 10 : null,
+    cvPercent: m.variability ? Math.round(m.variability.cv) : null,
+    unstable: m.variability?.unstable ?? null,
+  };
+}
+
+/** Panel projection — mirrors the panel's display rounding. */
+function panelProjection(
+  m: ReturnType<typeof computeGlucoseClinicalMetrics>,
+) {
+  return {
+    tirPercent: m.distribution ? Math.round(m.distribution.tir * 100) : null,
+    gmi: m.gmi !== null ? Number(m.gmi.toFixed(1)) : null,
+    estimatedA1c:
+      m.estimatedA1c !== null ? Number(m.estimatedA1c.toFixed(1)) : null,
+    cvPercent: m.variability ? Math.round(m.variability.cv) : null,
+    unstable: m.variability?.unstable ?? null,
+  };
+}
+
+describe("glucose panel ⇄ coach ⇄ doctor coherence", () => {
+  it("derives identical headline numbers from one engine result", () => {
+    // One computed result — exactly what each surface receives server-side.
+    const result = computeGlucoseClinicalMetrics(readings(), {
+      now: NOW,
+      windowDays: 30,
+    });
+    expect(result.stillLearning).toBe(false);
+
+    const panel = panelProjection(result);
+    const coach = coachProjection(result);
+    // doctor report carries the engine result verbatim
+    const doctor = {
+      tirPercent: result.distribution
+        ? Math.round(result.distribution.tir * 100)
+        : null,
+      gmi: result.gmi,
+      estimatedA1c: result.estimatedA1c,
+      cvPercent: result.variability ? Math.round(result.variability.cv) : null,
+      unstable: result.variability?.unstable ?? null,
+    };
+
+    // Panel == coach on every rounded headline figure.
+    expect(panel).toEqual(coach);
+
+    // Doctor's whole-precision figures round to the same display values.
+    expect(Math.round((doctor.gmi as number) * 10) / 10).toBe(panel.gmi);
+    expect(Math.round((doctor.estimatedA1c as number) * 10) / 10).toBe(
+      panel.estimatedA1c,
+    );
+    expect(doctor.tirPercent).toBe(panel.tirPercent);
+    expect(doctor.cvPercent).toBe(panel.cvPercent);
+    expect(doctor.unstable).toBe(panel.unstable);
+  });
+
+  it("agrees on the learning gate for thin data across surfaces", () => {
+    // 5 readings → all three surfaces see stillLearning and withhold assertion.
+    const thin = computeGlucoseClinicalMetrics(
+      [100, 110, 120, 130, 140].map((mgdl, i) => ({
+        measuredAt: new Date(NOW.getTime() - (4 - i) * DAY),
+        mgdl,
+      })),
+      { now: NOW, windowDays: 30 },
+    );
+    expect(thin.stillLearning).toBe(true);
+    // the coach gates its clinical block on exactly this flag; the panel
+    // renders its learning card on it; the doctor report carries the same
+    // flag in `glucoseClinical.stillLearning`.
+    expect(thin.gmi).not.toBeNull(); // preview value exists …
+    // … but every surface keys its assertion on `stillLearning`, not on the
+    // presence of the preview number.
+  });
+
+  it("is deterministic — identical input yields an identical result", () => {
+    const a = computeGlucoseClinicalMetrics(readings(), {
+      now: NOW,
+      windowDays: 30,
+    });
+    const b = computeGlucoseClinicalMetrics(readings(), {
+      now: NOW,
+      windowDays: 30,
+    });
+    expect(a).toEqual(b);
+  });
+});

src/lib/analytics/glucose-metrics.ts

@@ -30,6 +30,10 @@
  *   Bergenstal 2018, Diabetes Care 41(11):2275-2280, DOI 10.2337/dc18-1581.
  *   Nathan 2008 (ADAG), Diabetes Care 31(8):1473-1478, DOI 10.2337/dc08-0545.
  *   Monnier 2017, Diabetes Care 40(7):832-838, DOI 10.2337/dc16-1769.
+ *   Wojcicki 1995 (J-index), Horm Metab Res 27(1):41-42, DOI 10.1055/s-2007-979906.
+ *   Kovatchev 1997 (symmetrization + BGI), Diabetes Care 20(11):1655-1658,
+ *     DOI 10.2337/diacare.20.11.1655; Kovatchev 2006 (LBGI/HBGI risk model),
+ *     Diabetes Care 29(11):2433-2438, DOI 10.2337/dc06-1085.
  */
 
 // ── Inputs ───────────────────────────────────────────────
@@ -118,6 +122,41 @@ export interface TimeInRangeDistribution {
   };
 }
 
+/**
+ * Advanced glycaemic indices — the "advanced" disclosure tier of the panel.
+ * Each is a single scalar over the in-window readings; all are derivable from
+ * spot samples (unlike the dense-stream MAGE/CONGA/MODD family this module
+ * deliberately defers). Surfaced behind a progressive disclosure because they
+ * read as research-grade composites a casual user does not need up front.
+ */
+export interface GlucoseAdvancedIndices {
+  /**
+   * J-index — a single number folding central tendency AND variability:
+   *   J = 0.001 × (mean + SD)²,   mean & SD in mg/dL.
+   * Reference bands (Wojcicki 1995): ~10–20 ideal/non-diabetic,
+   * 20–30 good control, 30–40 fair, > 40 poor. Reported here as an estimate
+   * over spot data, not a continuous-trace J.
+   * Wojcicki 1995, Horm Metab Res 27(1):41-42, DOI 10.1055/s-2007-979906.
+   */
+  jIndex: number;
+  /**
+   * Low Blood Glucose Index — Kovatchev hypoglycaemia risk. Mean of the
+   * left-branch risk values `rl(BG)` over all readings; higher = more / deeper
+   * lows. Interpretation bands (Kovatchev 2006): < 1.1 minimal, 1.1–2.5 low,
+   * 2.5–5 moderate, > 5 high hypo risk.
+   * Kovatchev 2006, Diabetes Care 29(11):2433-2438, DOI 10.2337/dc06-1085.
+   */
+  lbgi: number;
+  /**
+   * High Blood Glucose Index — Kovatchev hyperglycaemia risk. Mean of the
+   * right-branch risk values `rh(BG)`; higher = more / higher highs.
+   * Interpretation bands (Kovatchev 2006): < 4.5 low, 4.5–9 moderate,
+   * > 9 high hyper risk.
+   * Kovatchev 2006, Diabetes Care 29(11):2433-2438, DOI 10.2337/dc06-1085.
+   */
+  hbgi: number;
+}
+
 /** Variability summary: SD + CV% with the Monnier stability flag. */
 export interface GlucoseVariability {
   /** Sample standard deviation (n−1), mg/dL. */
@@ -160,6 +199,18 @@ export interface GlucoseClinicalMetrics {
   /** SD + CV% + instability flag (null if < 2 readings). */
   variability: GlucoseVariability | null;
 
+  /**
+   * Advanced indices (J-index + LBGI/HBGI). Null when there are no readings;
+   * the J-index additionally needs ≥ 2 readings (it consumes the sample SD), so
+   * `jIndex` is held back to null inside the object when only one reading
+   * exists. Shown behind the panel's "advanced" disclosure.
+   */
+  advanced: {
+    jIndex: number | null;
+    lbgi: number;
+    hbgi: number;
+  } | null;
+
   /**
    * Always true for this module: every number is a spot-reading estimate, not a
    * CGM AGP. Surfaced explicitly so serializers (panel/coach/PDF/iOS) carry the
@@ -228,6 +279,65 @@ export function estimatedA1c(meanMgdl: number): number {
   return (meanMgdl + 46.7) / 28.7;
 }
 
+/**
+ * J-index — a single composite of central tendency and variability:
+ *   J = 0.001 × (mean + SD)²,   both in mg/dL.
+ * Returns null for n < 2 (the sample SD is undefined). Approximation bands are
+ * documented on {@link GlucoseAdvancedIndices.jIndex}.
+ * Wojcicki 1995, Horm Metab Res 27(1):41-42, DOI 10.1055/s-2007-979906.
+ */
+export function jIndex(values: number[]): number | null {
+  const sd = glucoseSD(values);
+  if (sd === null) return null;
+  const m = mean(values);
+  const s = m + sd;
+  return 0.001 * s * s;
+}
+
+/**
+ * Kovatchev symmetrization transform for a single mg/dL reading:
+ *   f(BG) = 1.509 × ( (ln BG)^1.084 − 5.381 ).
+ * The transform maps the asymmetric mg/dL scale onto a symmetric axis where
+ * the clinical centre (~112.5 mg/dL) is 0; lows go negative, highs positive.
+ * Kovatchev 1997, Diabetes Care 20(11):1655-1658,
+ * DOI 10.2337/diacare.20.11.1655.
+ */
+function kovatchevSymmetrize(bgMgdl: number): number {
+  return 1.509 * (Math.pow(Math.log(bgMgdl), 1.084) - 5.381);
+}
+
+/**
+ * Low / High Blood Glucose Index (LBGI / HBGI) — Kovatchev risk model.
+ * Per reading the risk is `r(BG) = 10 × f(BG)²` (f = symmetrization above);
+ * it is assigned to the LOW branch when f < 0 and the HIGH branch when f > 0
+ * (f = 0 contributes 0 to both). LBGI = mean of the low-branch risks across
+ * ALL readings (zeros included), HBGI = mean of the high-branch risks.
+ * Readings ≤ 0 mg/dL (ln undefined) are skipped from the denominator.
+ * Returns null when no usable reading remains.
+ * Kovatchev 2006, Diabetes Care 29(11):2433-2438, DOI 10.2337/dc06-1085.
+ */
+export function bloodGlucoseRiskIndices(
+  values: number[],
+): { lbgi: number; hbgi: number } | null {
+  let lowSum = 0;
+  let highSum = 0;
+  let n = 0;
+  for (const bg of values) {
+    if (!Number.isFinite(bg) || bg <= 0) continue;
+    const f = kovatchevSymmetrize(bg);
+    const r = 10 * f * f;
+    if (f < 0) {
+      lowSum += r;
+    } else if (f > 0) {
+      highSum += r;
+    }
+    // f === 0 contributes 0 to both branches but still counts in n.
+    n += 1;
+  }
+  if (n === 0) return null;
+  return { lbgi: lowSum / n, hbgi: highSum / n };
+}
+
 /**
  * Time-in-range distribution over the Battelino 2019 consensus bands, as
  * fractions of readings (NOT % of time — spot data, labelled honestly).
@@ -314,7 +424,13 @@ export function computeGlucoseClinicalMetrics(
       (r) =>
         r.measuredAt.getTime() >= cutoff &&
         r.measuredAt.getTime() <= now.getTime() &&
-        Number.isFinite(r.mgdl),
+        Number.isFinite(r.mgdl) &&
+        // Non-positive glucose is non-physiological and ln-undefined (the
+        // Kovatchev symmetrization needs ln BG). Excluding it here keeps EVERY
+        // index — mean / SD / TIR / GMI / LBGI / HBGI — on one shared
+        // denominator rather than letting the risk indices drop a row the
+        // others kept.
+        r.mgdl > 0,
     )
     .sort((a, b) => a.measuredAt.getTime() - b.measuredAt.getTime());
 
@@ -334,6 +450,19 @@ export function computeGlucoseClinicalMetrics(
   const gmiValue = meanMgdl !== null ? gmi(meanMgdl) : null;
   const eA1cValue = meanMgdl !== null ? estimatedA1c(meanMgdl) : null;
 
+  // Advanced indices — null when no readings. The risk indices need ≥ 1 usable
+  // reading; the J-index needs ≥ 2 (sample SD), so it is held to null inside
+  // the object for a single-reading window while LBGI/HBGI still resolve.
+  const risk = bloodGlucoseRiskIndices(values);
+  const advanced =
+    risk !== null
+      ? {
+          jIndex: jIndex(values),
+          lbgi: risk.lbgi,
+          hbgi: risk.hbgi,
+        }
+      : null;
+
   // Learning/adequacy gate. Spot data cannot meet the CGM adequacy bar; this
   // is the honest "is the estimate worth asserting yet" check. Order matters:
   // report the most actionable reason first.
@@ -370,6 +499,7 @@ export function computeGlucoseClinicalMetrics(
     gmi: gmiValue,
     estimatedA1c: eA1cValue,
     variability,
+    advanced,
     isSpotEstimate: true,
   };
 }

src/lib/dashboard/snapshot.ts

@@ -46,6 +46,10 @@ import {
   type DataSummary,
 } from "@/lib/analytics/trends";
 import { getBpTargets } from "@/lib/analytics/bp-targets";
+import {
+  computeGlucoseClinicalMetrics,
+  type GlucoseClinicalMetrics,
+} from "@/lib/analytics/glucose-metrics";
 import {
   computeBpInTargetFastPath,
   type BpInTargetEnvelope,
@@ -206,6 +210,17 @@ export interface DashboardSnapshotExtras {
   bpInTargetCount90: number | null;
   bpInTargetSpanDays90: number | null;
   glucoseByContext: Record<string, DataSummary>;
+  /**
+   * v1.17.0 — server-authoritative glucose clinical panel over the trailing
+   * 30-day window: the learning gate (+ reason), window/span/count, mean,
+   * Battelino TIR distribution, GMI, estimated A1C, SD/CV%/instability, and the
+   * advanced J-index + LBGI/HBGI tier. Computed ONCE by
+   * `computeGlucoseClinicalMetrics` so the iOS client renders the same numbers
+   * the web panel, the coach, and the doctor report do — iOS never re-derives.
+   * Always present (even with zero readings) so the native client paints the
+   * calm "still learning" state from a populated object.
+   */
+  glucoseClinical: GlucoseClinicalMetrics;
 }
 
 /**
@@ -565,6 +580,14 @@ async function buildExtras(
     }
   }
 
+  // v1.17.0 — clinical panel from the SAME 30-day glucose rows already read
+  // above (no extra DB hop), computed by the one literature-locked engine so
+  // the iOS cold-launch seed matches the web panel / coach / doctor report.
+  const glucoseClinical = computeGlucoseClinicalMetrics(
+    glucoseRows.map((r) => ({ measuredAt: r.measuredAt, mgdl: r.value })),
+    { windowDays: 30, now },
+  );
+
   return {
     extras: {
       bpInTargetPct,
@@ -576,6 +599,7 @@ async function buildExtras(
       bpInTargetCount90,
       bpInTargetSpanDays90,
       glucoseByContext,
+      glucoseClinical,
     },
     healthScore,
   };

src/lib/doctor-report-data.ts

@@ -18,6 +18,10 @@ import {
   thresholdMetricForContext,
   type GlucoseUnit,
 } from "@/lib/glucose";
+import {
+  computeGlucoseClinicalMetrics,
+  type GlucoseClinicalMetrics,
+} from "@/lib/analytics/glucose-metrics";
 import type {
   GlucoseContext,
   MeasurementSource,
@@ -96,6 +100,16 @@ export interface DoctorReportData {
   glucoseStats: Record<string, DoctorReportStats>;
   glucoseRanges: Record<string, { min: number; max: number }>;
   glucoseUnit: GlucoseUnit;
+  /**
+   * v1.17.0 — server-authoritative glucose clinical panel over the report
+   * period (TIR / GMI / estimated A1C / CV% + the advanced J-index + LBGI/HBGI
+   * tier), computed by `computeGlucoseClinicalMetrics` so the PDF/FHIR export
+   * carries the SAME numbers the insights panel and the coach show. Values are
+   * canonical mg/dL; `glucoseUnit` drives display conversion at render. Carried
+   * as a spot-reading estimate (`isSpotEstimate: true`), gated by
+   * `stillLearning` when the period is too thin to assert clinically.
+   */
+  glucoseClinical: GlucoseClinicalMetrics;
   bmi: number | null;
   compliance: Record<string, DoctorReportCompliance>;
   medications: Array<{
@@ -869,6 +883,18 @@ export async function collectDoctorReportData(
     }
   }
 
+  // v1.17.0 — clinical panel over the WHOLE report period (all contexts
+  // pooled), computed by the one literature-locked engine the insights panel
+  // and the coach also consume. `windowDays` is the report's own period so the
+  // TIR / GMI / eA1C / CV% reflect exactly the readings the rest of the report
+  // tabulates; `now: end` anchors the window to the report's upper bound. The
+  // learning gate keeps a thin period from asserting a clinical AGP off spot
+  // data. Values stay canonical mg/dL; the renderer converts with `glucoseUnit`.
+  const glucoseClinical = computeGlucoseClinicalMetrics(
+    glucoseRows.map((r) => ({ measuredAt: r.measuredAt, mgdl: r.value })),
+    { windowDays: days, now: end },
+  );
+
   // `practiceName` is sanitised to a single-line string with a hard length
   // cap. The PDF cover prints it verbatim — never let unbounded input land in
   // a layout-sensitive header.
@@ -1056,6 +1082,7 @@ export async function collectDoctorReportData(
     stats: filteredStats,
     glucoseStats,
     glucoseRanges,
+    glucoseClinical,
     glucoseUnit: resolveGlucoseUnit(userProfile?.glucoseUnit ?? null),
     bmi: filteredBmi,
     compliance: filteredCompliance,

src/lib/fhir/__tests__/build-bundle.test.ts

@@ -1,6 +1,7 @@
 import { describe, it, expect } from "vitest";
 import { buildFhirDocumentBundle } from "../build-bundle";
 import type { DoctorReportData } from "@/lib/doctor-report-data";
+import { computeGlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
 import type {
   FhirObservation,
   FhirMedicationStatement,
@@ -77,6 +78,9 @@ function makeData(overrides?: Partial<DoctorReportData>): DoctorReportData {
       FASTING: { avg: 92, min: 85, max: 100, count: 4, latest: 90 },
     },
     glucoseRanges: { FASTING: { min: 70, max: 99 } },
+    glucoseClinical: computeGlucoseClinicalMetrics([], {
+      now: new Date("2026-05-03T12:00:00.000Z"),
+    }),
     glucoseUnit: "mg/dL",
     bmi: 24.1,
     compliance: {

src/lib/fhir/__tests__/cycle-observations.test.ts

@@ -1,6 +1,7 @@
 import { describe, expect, it } from "vitest";
 
 import type { DoctorReportData } from "@/lib/doctor-report-data";
+import { computeGlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
 import { cycleObservationsFromReportData } from "@/lib/fhir/resources";
 import { buildFhirDocumentBundle } from "@/lib/fhir/build-bundle";
 import {
@@ -28,6 +29,9 @@ function baseData(overrides?: Partial<DoctorReportData>): DoctorReportData {
     stats: {},
     glucoseStats: {},
     glucoseRanges: {},
+    glucoseClinical: computeGlucoseClinicalMetrics([], {
+      now: new Date("2026-05-03T12:00:00.000Z"),
+    }),
     glucoseUnit: "mg/dL",
     bmi: null,
     compliance: {},

src/lib/openapi/routes/insights.ts

@@ -541,6 +541,60 @@ const insightsPregenerateResponse = z
 // modules and the iOS client does not consume this web-only route.
 const dataSummaryRecord = z.record(z.string(), z.unknown());
 
+// v1.17.0 — server-authoritative glucose clinical panel. Mirrors
+// `GlucoseClinicalMetrics` from `@/lib/analytics/glucose-metrics`: the
+// trailing-30-day TIR / GMI / eA1C / CV% headline plus the advanced
+// J-index + LBGI/HBGI tier, gated by a `stillLearning` flag so a thin
+// spot-data window is never asserted as a clinical AGP. The iOS client
+// renders these numbers verbatim and never re-derives them.
+const glucoseClinicalSchema = z
+  .object({
+    stillLearning: z.boolean(),
+    stillLearningReason: z.string().nullable(),
+    windowDays: z.number().int(),
+    actualSpanDays: z.number(),
+    readingCount: z.number().int(),
+    meanMgdl: z.number().nullable(),
+    distribution: z
+      .object({
+        tir: z.number(),
+        tbrLevel1: z.number(),
+        tbrLevel2: z.number(),
+        tarLevel1: z.number(),
+        tarLevel2: z.number(),
+        minutesEquivalent: z.object({
+          tir: z.number(),
+          tbrLevel1: z.number(),
+          tbrLevel2: z.number(),
+          tarLevel1: z.number(),
+          tarLevel2: z.number(),
+        }),
+      })
+      .nullable(),
+    gmi: z.number().nullable(),
+    estimatedA1c: z.number().nullable(),
+    variability: z
+      .object({
+        sd: z.number(),
+        cv: z.number(),
+        unstable: z.boolean(),
+      })
+      .nullable(),
+    advanced: z
+      .object({
+        jIndex: z.number().nullable(),
+        lbgi: z.number(),
+        hbgi: z.number(),
+      })
+      .nullable(),
+    isSpotEstimate: z.literal(true),
+  })
+  .meta({
+    id: "GlucoseClinicalMetrics",
+    description:
+      "Server-authoritative glucose clinical panel over the trailing 30-day window. Every figure is a SPOT-READING ESTIMATE (a % of readings), not a CGM time-in-range AGP — `isSpotEstimate` is always true and `stillLearning` gates assertion when the window has too few readings or too short a span. `distribution` carries the Battelino 2019 TIR/TBR/TAR fractions (level-2 nested in level-1) plus minutes-of-a-day equivalents; `gmi` (Bergenstal 2018) + `estimatedA1c` (Nathan 2008 ADAG) derive from the mean; `variability` is SD + CV% with the Monnier 2017 ≥36% instability flag; `advanced` is the disclosure tier — J-index (Wojcicki 1995) + LBGI/HBGI (Kovatchev hypo/hyper risk). All blocks are null when there are no readings; `advanced.jIndex` is null for a single-reading window.",
+  });
+
 const dashboardSnapshotResponse = z
   .object({
     user: z.object({
@@ -608,6 +662,7 @@ const dashboardSnapshotResponse = z
         bpInTargetPctPriorMonth: z.number().nullable(),
         bpInTargetPctPriorYear: z.number().nullable(),
         glucoseByContext: dataSummaryRecord,
+        glucoseClinical: glucoseClinicalSchema,
       })
       .nullable(),
     // Dashboard hero — today's medication block (fast phase, always

src/lib/queries/use-analytics-query.ts

@@ -6,6 +6,7 @@ import { useAuth } from "@/hooks/use-auth";
 import { queryKeys } from "@/lib/query-keys";
 import { DASHBOARD_REFETCH_INTERVAL_MS } from "@/lib/queries/refetch-interval";
 import type { DataSummary } from "@/lib/analytics/trends";
+import type { GlucoseClinicalMetrics } from "@/lib/analytics/glucose-metrics";
 
 /**
  * v1.4.33 IW2 — single TanStack-Query wrapper for `/api/analytics`.
@@ -71,6 +72,14 @@ export interface AnalyticsRawPayload {
   bpInTargetPctPriorMonth?: number | null;
   bpInTargetPctPriorYear?: number | null;
   glucoseByContext?: Record<string, unknown>;
+  /**
+   * v1.17.0 — server-authoritative glucose clinical panel (TIR / GMI / eA1C /
+   * CV% headline + the advanced J-index + LBGI/HBGI tier), computed once over
+   * the trailing-30-day window. Present on the thick default slice; absent on
+   * the slim `?slice=summaries` branch. The panel renders this verbatim and
+   * never re-derives a clinical number client-side.
+   */
+  glucoseClinical?: GlucoseClinicalMetrics;
   correlations?: unknown;
   healthScore?: unknown;
   sleepStages?: unknown;