feat: deep statistical analytics — clinical, symptoms, incidence, env correlation, weekday

Adds a substantial layer of data-backed statistics (all grounded in verified,
clean source data — no fabricated metrics).

Backend (new routers/statistics.py, prefix /api/stats; +106 pytest still green):
- /inpatient-clinical: LOS dist + by-disease quartiles, cost dist + by-disease +
  cost-vs-LOS, outcome counts, admission-route counts, BMI-by-age, KPIs
  (5822 admissions, median LOS 4d, mean ¥6294, cure 99.1%, emergency 47%)
- /symptoms: 主诉 keyword frequencies (发热/咳嗽/肺炎…) + revisit ratio (36%)
- /incidence-rate: per-10k-population standardized rate by district (cases ÷ pop)
- /env-correlation: pollutant×cases Pearson + 7×7 pairwise matrix + PM2.5 scatter
- /temporal: weekday distribution (+ month/yoy returned but UI omits them — data
  is December-only, so seasonality/YoY would be misleading)

Frontend:
- NEW 住院临床分析 page (/analysis/clinical, nav 临床分析): 9 charts + KPI row —
  LOS histogram + box-by-disease, cost histogram + scatter + by-disease, outcome
  donut (severity-colored), admission-route donut, age-band BMI box
- DiseaseAnalysis: 主诉症状词频 horizontal bar + revisit ratio
- DistrictComparison: 标化发病率（每万人）with 病例数↔发病率 toggle (rate is
  epidemiologically correct; raw counts mislead by population)
- EnvironmentalHealth: pollutant-cases correlation bar + 7×7 correlation heatmap +
  PM2.5×cases scatter with least-squares regression line
- TrendAnalysis: 星期就诊分布 + honest "data is December-only" note
- statsApi client + types

Gates: tsc 0 · build ok · functional e2e 43/43 (incl 2 new clinical) · verified
live against real backend data via dev proxy

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

frontend/src/components/clinical/ClinicalKpiRow.tsx

@@ -0,0 +1,47 @@
+import { memo } from 'react';
+import { Users, CalendarDays, Wallet, HeartPulse, Siren } from 'lucide-react';
+import { StatCard } from '@/components/StatCard';
+import { TESTIDS } from '@/utils/testids';
+import type { InpatientClinicalResponse } from '@/services/api';
+
+interface ClinicalKpiRowProps {
+  kpis: InpatientClinicalResponse['kpis'];
+}
+
+/** 住院临床 5 项核心指标。375px 下 2 列，sm 起 5 列。 */
+export const ClinicalKpiRow = memo(function ClinicalKpiRow({ kpis }: ClinicalKpiRowProps) {
+  return (
+    <div
+      data-testid={TESTIDS.clinicalKpis}
+      className="grid grid-cols-2 sm:grid-cols-5 gap-3"
+    >
+      <StatCard
+        icon={<Users className="w-4 h-4 text-primary" />}
+        label="住院总人次"
+        value={kpis.total_admissions.toLocaleString()}
+      />
+      <StatCard
+        icon={<CalendarDays className="w-4 h-4 text-primary" />}
+        label="中位住院日"
+        value={`${kpis.median_los_days} 天`}
+      />
+      <StatCard
+        icon={<Wallet className="w-4 h-4 text-primary" />}
+        label="人均费用"
+        value={`¥${Math.round(kpis.mean_cost).toLocaleString()}`}
+      />
+      <StatCard
+        icon={<HeartPulse className="w-4 h-4 text-success" />}
+        label="治愈好转率"
+        value={`${(kpis.cure_rate * 100).toFixed(1)}%`}
+        color="#16A34A"
+      />
+      <StatCard
+        icon={<Siren className="w-4 h-4 text-warning" />}
+        label="急诊入院占比"
+        value={`${(kpis.emergency_admit_ratio * 100).toFixed(1)}%`}
+        color="#D97706"
+      />
+    </div>
+  );
+});