The BD-Zielbereich headline, the Health-Score BP pillar and the coach
number now all read the same trailing-90-day in-target window. Re-derive
the integration expectations from the fixtures: the analytics headline is
the independent 90-day figure (distinct from the 30-day and all-time
windows), and the BP pillar grades from the 90-day window when readings
predate the trailing month rather than dropping out.
Blood-pressure fixtures in the in-target integration suite were copied
from live readings; they are now synthetic with the same in/out split so
every assertion holds. Hard-coded operator hostnames move behind env vars
(DEPLOY_LOGS_URL, HEALTHLOG_PROD_URL), the codex client identifies via
the public repository URL, the OpenAPI servers entry points at a neutral
example host, and remaining workflow, docs and comment references to the
operator's instance or working notes are generalised. The compose
whitelist also gains DEPLOY_WEBHOOK_SECRET, which was missing and made
the deploy webhook unusable on compose installs.
The W2-of-v1.4.20 BD-Zielbereich fix needed the complete sys + dia
series to compute the all-time + prior-month + prior-year windows,
so it pulled both tables via single-shot `findMany`. For a 5-year
power user (~9 000 rows per side) that's a 50-100 ms Prisma round-
trip and a ~2 MB working-set allocation per /api/analytics request.
Switch to a cursor-paged 5 000-row chunked read via the new
`fetchBpSeriesChunked()` helper. The accumulated `BpReading[]` is the
same shape `computeBpInTargetWindows()` already consumed; the
working-set ceiling is now `BP_CHUNK_SIZE` instead of unbounded. Safety
bound at 1 000 pages = 5 M rows so a cursor-staleness bug can't loop
forever.
Wide-event annotation `analytics.bp_in_target.row_count` (+ per-side
`sys_rows` / `dia_rows`) lets ops attribute slow requests to outlier
users without rerunning the DB queries.
Integration test seeds a 6 000-row dataset (3 000 sys + 3 000 dia)
spanning a chunk boundary and asserts the response shape stays the
same — last30Days, last7Days, allTime windows all carry the
hand-derivable percentages.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Up to v1.4.19 the BD-Zielbereich tile pinned 50/50/50 because the
route routed the headline through `windows.last30Days?.pct` — making
the headline a literal copy of the `30T` sub-value. v1.4.19 A1
re-anchored the headline to all-time so the three windows could
diverge. That fixed the algorithmic pin but introduced an emotional
problem: the headline became the slowest-moving aggregate possible,
punishing users who had recently dragged their compliance up. A user
seeing 7d 50 % / 30d 50 % alongside a stubborn 11 % all-time read it
as "your work doesn't count yet."
Re-anchor the headline to `windows.last30Days?.pct` and surface
all-time as a third sub-value (`bpInTargetPctAllTime`) so power users
still see the long-arc number without it dominating. The integration
test pins the new contract: with three legitimately divergent windows
the route's `bpInTargetPct` equals `last30Days.pct`, and the new
all-time field carries the historical figure.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Marc reported the BD-Zielbereich tile pinned at exactly 50/50/50 for
7T, 30T, and the headline ("total") on his real production data — the
fourth attempt at this surface (v1.4.15 → v1.4.16 → v1.4.18 → v1.4.19).
Root cause: the analytics route routed `bpInTargetPct` (the headline)
through `windows.last30Days?.pct` — a literal copy of the `30T`
sub-value. Since `computeBpInTargetWindows` only returned 7d + 30d
windows, the headline could never legitimately differ from `30T`. For
Marc's real data (572 paired readings since 2022, recent 30d = 50 %,
all-time ≈ 11 %) the tile read 50 % / 50 % / 50 % and looked
algorithmically pinned — exactly the symptom he reported.
The previous three passes treated this as either a predicate bug
(v1.4.16 ceiling-vs-narrow-band, real and merged) or a missing
`avg7`/`avg30` wiring (v1.4.18, also real and merged). Both fixes
landed correctly, but neither addressed the headline duplication.
Fix:
- `computeBpInTargetWindows` now returns a third `allTime` window
that aggregates EVERY paired reading in the input series.
- The analytics route fetches all paired BP rows (no 30-day cutoff)
and routes the headline through `windows.allTime?.pct`. The route
only re-pairs once internally so the cost is paid once per request.
- The 7T / 30T sub-values are unchanged (still windowed slices of
the same input).
Failing test reproduces the bug with Marc's data shape (`allTime` MUST
not equal `last30Days` once older history is present); fix turns it
green. Integration test seeds 40 paired readings against real Postgres
and asserts all three windows compute independently.
Hand-counted against Marc's prod data:
- 7T: 50 % (1/2) — matches what he sees, real coincidence
- 30T: 50 % (5/10) — matches what he sees, real coincidence
- Headline: ~11 % (62/572) — was 50 %, now correct
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Pre-existing format drift accumulated across v1.4.x; running
prettier brings the whole tree back to baseline so future diffs
read clean. No behaviour change.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The tile rendered the 30-day headline correctly but the `7T:` and
`30T:` sub-values fell back to "—" even when the user had paired BP
readings in both windows. Root cause was that `/api/analytics` only
returned a single `bpInTargetPct`; the tile received `avg7={null}`
and `avg30={null}` and the TrendCard rendered the dash placeholder.
Add `computeBpInTargetWindows()` next to the existing `computeBpInTargetPct()`
helper. It filters the input series by `measuredAt` against the supplied
clock and runs the same pair-and-count logic over the trailing 7-day and
30-day windows. The route fetches the last 30 days of data once, derives
both shares from the result, and surfaces them as `bpInTargetPct7d` and
`bpInTargetPct30d` on the response. The dashboard tile maps them to
`avg7` and `avg30` so the sub-values now show the actual percentages.
Coverage:
- 6 unit tests for the windowed helper (empty input, mixed window data,
null-7d-with-real-30d, default-clock, Marc's production fixture).
- 2 integration tests against testcontainers seeding 30 days of paired
BP measurements; both windows produce the expected hand-counted shares.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The BD-Zielbereich tile rendered 0% for users whose readings sat below
the ESH 2023 narrow goal band (Sys 120-129 / Dia 70-79 for under-65).
Marc's actual production data has many readings like 117/79 — textbook
normotensive, well-controlled — that v1.4.15 A4 still counted as OUT
of target because sys < sysLow (120). 5 of 10 of his last-30-day pairs
should be in-target by clinical interpretation; v1.4.15 reported 0.
Root cause: "in target" was defined as the narrow goal band, which is
the ESH treatment goal for hypertensive patients ON therapy — NOT the
desirable range for a normotensive HealthLog user. Users (and the
dashboard label) intuitively mean "BP is well-controlled = at or below
the ceiling, not implausibly hypotensive".
Fix: change semantics from `sysLow <= sys <= sysHigh && diaLow <= dia <=
diaHigh` to `90 <= sys <= sysHigh && 50 <= dia <= diaHigh`. The 90/50
floors guard against counting symptomatic hypotension as "good control".
Centralised the check in `isBpReadingInTarget()` so the 6 historical
call sites (analytics route, blood-pressure-status, features,
general-status, insights/cards, insights/comprehensive, insights/targets)
share one definition — pre-fix they had 5 independent inline copies of
the narrow-band formula, easy to drift on a future refactor.
Tests:
- 6 new unit tests pin the new ceiling+floor semantics including Marc's
exact production fixture (10 paired readings -> 50% under v1.4.16,
was 0% under v1.4.15).
- New `tests/integration/bp-in-target.test.ts` seeds Postgres
testcontainer with Marc's reading shape + null-tolerance + hypotension
edge cases.
Cache invalidation already correct: `measurementDependentKeys` includes
`analytics()` so adding a BP measurement invalidates the tile's
TanStack Query cache.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Marc-André Bombeck