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chore(dashboard): retire the GLP-1 tile
Drop the standalone GLP-1 dashboard tile and its data-fetch route. The /api/dashboard/glp1 endpoint has no consumer outside the retired tile (no native client reads it), so the route, the tile component, its test, the e2e spec, the locale keys, the query-key entry and the drift-guard assertion all retire together. The medication detail page and its bidirectional contracts stay untouched. An opt-in dashboard widget that surfaces the same level chart will land later in this cycle, anchored on the existing dashboard-layout toggle list.
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Marc-André Bombeck committed
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@@ -1,203 +0,0 @@
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/**
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* GET /api/dashboard/glp1 — v1.4.25 W6
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*
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* Powers the dashboard's `<Glp1Tile>`. Returns the user's active GLP-1
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* medications (treatmentClass = "GLP1"), each enriched with a tiny
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* weight series + the dates the user logged an injection. Returns
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* `null` data when the user has no active GLP-1 medication — the tile
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* then suppresses itself per Marc's empty-state hide rule.
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*
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* Bridge layer: the heavy lifting (current dose / last + next injection
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* / titration history / inventory math) is delegated to
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* `buildGlp1SnapshotBlock` so the Coach's GLP-1-aware reply path and
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* this dashboard tile read from the exact same shape. The extras we
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* add on top here are purely UI-facing:
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* - weightSeries[] — daily aggregates since the first dose change
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* (or 90 days back, whichever is later) for
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* the mini-chart on the tile
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* - weightDeltaKg — convenience caption value (current − start);
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* the tile renders "−4.2 kg seit Beginn" off
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* this number, with `null` when either side
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* is missing
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* - injectionDates[] — `YYYY-MM-DD` keys for every recorded intake
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* event so the chart can paint the vertical
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* injection-day markers Marc wants
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*/
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import { apiHandler, requireAuth } from "@/lib/api-handler";
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import { apiSuccess } from "@/lib/api-response";
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import { annotate } from "@/lib/logging/context";
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import { prisma } from "@/lib/db";
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import { buildGlp1SnapshotBlock } from "@/lib/ai/coach/glp1-snapshot";
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import { DEFAULT_TIMEZONE } from "@/lib/tz/resolver";
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const WEIGHT_LOOKBACK_DAYS = 90;
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const MS_PER_DAY = 24 * 60 * 60 * 1000;
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function isoDate(d: Date): string {
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return d.toISOString().slice(0, 10);
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}
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/**
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* Bucket raw weight measurements into one daily average so the mini-
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* chart doesn't render the noisy raw stream. Same `YYYY-MM-DD` keying
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* the dashboard chart layer uses (UTC-noon anchor — DST-safe).
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*/
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function bucketDaily(
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rows: Array<{ measuredAt: Date; value: number }>,
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): Array<{ date: string; weight: number }> {
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const sums = new Map<string, { sum: number; count: number }>();
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for (const row of rows) {
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const key = isoDate(row.measuredAt);
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const slot = sums.get(key) ?? { sum: 0, count: 0 };
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slot.sum += row.value;
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slot.count += 1;
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sums.set(key, slot);
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}
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return Array.from(sums.entries())
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.map(([date, { sum, count }]) => ({
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date,
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weight: Math.round((sum / count) * 100) / 100,
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}))
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.sort((a, b) => (a.date < b.date ? -1 : 1));
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}
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export const GET = apiHandler(async () => {
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const { user } = await requireAuth();
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const userTz = user.timezone ?? DEFAULT_TIMEZONE;
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const now = new Date();
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const snapshot = await buildGlp1SnapshotBlock(user.id, now);
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// No active GLP-1 medication → the tile suppresses itself. We still
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// return 200 + `data: null` so the client doesn't have to special-
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// case the 404 path.
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if (!snapshot) {
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annotate({
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action: { name: "dashboard.glp1" },
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meta: { active: 0 },
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});
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return apiSuccess(null);
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}
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// Anchor the weight series to the earliest meaningful date: the user
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// wants to see the trend SINCE THEY STARTED the GLP-1, not just the
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// last 90 days. We pick the earlier of:
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// - the first dose-change `effectiveFrom` across all GLP-1 meds
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// - 90 days back from today (so brand-new accounts still get a
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// reasonable window when they only just logged their first dose)
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let anchor = new Date(now.getTime() - WEIGHT_LOOKBACK_DAYS * MS_PER_DAY);
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for (const med of snapshot.medications) {
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if (med.doseHistory.length === 0) continue;
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const firstDose = med.doseHistory[0].effectiveFrom;
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const firstDoseMs = Date.parse(`${firstDose}T00:00:00Z`);
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if (Number.isFinite(firstDoseMs) && firstDoseMs < anchor.getTime()) {
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anchor = new Date(firstDoseMs);
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}
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}
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const [weights, intakeRows] = await Promise.all([
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prisma.measurement.findMany({
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where: {
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userId: user.id,
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type: "WEIGHT",
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measuredAt: { gte: anchor },
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},
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orderBy: { measuredAt: "asc" },
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select: { measuredAt: true, value: true },
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}),
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prisma.medicationIntakeEvent.findMany({
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where: {
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userId: user.id,
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takenAt: { not: null, gte: anchor },
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medication: { treatmentClass: "GLP1" },
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},
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orderBy: { takenAt: "asc" },
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select: {
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medicationId: true,
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takenAt: true,
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medication: { select: { name: true } },
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},
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}),
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]);
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const weightSeries = bucketDaily(weights);
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// Per-med injection date set — used by the chart's vertical markers.
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// Multiple injection events on the same day collapse to a single
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// marker so the chart doesn't paint stacked overlapping lines.
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const injectionDatesByMed = new Map<string, Set<string>>();
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for (const ev of intakeRows) {
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if (!ev.takenAt) continue;
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const set = injectionDatesByMed.get(ev.medicationId) ?? new Set<string>();
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set.add(isoDate(ev.takenAt));
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injectionDatesByMed.set(ev.medicationId, set);
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}
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// We also need to know the medication id per snapshot entry. The
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// snapshot exposes name + genericName but not the id; re-fetch the
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// id list ordered by `createdAt: desc` (matches the snapshot
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// ordering) and zip the two lists. Cheap re-query — already in cache
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// from the snapshot's first hit.
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const idsForOrder = await prisma.medication.findMany({
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where: { userId: user.id, treatmentClass: "GLP1", active: true },
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orderBy: { createdAt: "desc" },
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select: { id: true, name: true },
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});
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// Build the enriched per-med payload. `startWeight` = the first daily
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// bucket on/after the med's first dose-change date; `currentWeight`
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// = the most recent daily bucket. Both `null` when no weight data
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// exists in the window — the tile suppresses the delta caption then.
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const medications = snapshot.medications.map((med, idx) => {
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const medId = idsForOrder[idx]?.id ?? null;
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let startWeight: number | null = null;
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let currentWeight: number | null = null;
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let medSeries: Array<{ date: string; weight: number }> = [];
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if (weightSeries.length > 0) {
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const firstDoseDate =
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med.doseHistory.length > 0 ? med.doseHistory[0].effectiveFrom : null;
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// Filter the series to "since the user started this medication".
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// If we don't have a dose-change row (legacy data) we fall back
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// to the whole 90-day window so the chart isn't empty.
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medSeries = firstDoseDate
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? weightSeries.filter((p) => p.date >= firstDoseDate)
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: weightSeries.slice();
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startWeight = medSeries[0]?.weight ?? null;
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currentWeight = medSeries[medSeries.length - 1]?.weight ?? null;
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}
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const weightDeltaKg =
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startWeight !== null && currentWeight !== null
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? Math.round((currentWeight - startWeight) * 100) / 100
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: null;
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const injectionDates = medId
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? Array.from(injectionDatesByMed.get(medId) ?? []).sort()
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: [];
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return {
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...med,
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medicationId: medId,
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startWeight,
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currentWeight,
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weightDeltaKg,
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weightSeries: medSeries,
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injectionDates,
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};
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});
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annotate({
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action: { name: "dashboard.glp1" },
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meta: {
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active: medications.length,
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tz: userTz,
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},
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});
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return apiSuccess({
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active: snapshot.active,
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medications,
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});
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});
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