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>
This commit is contained in:
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frontend/src/pages/ClinicalAnalysis.tsx
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175
frontend/src/pages/ClinicalAnalysis.tsx
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import { useEffect, useState } from 'react';
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import { Activity } from 'lucide-react';
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import { statsApi, type InpatientClinicalResponse } from '@/services/api';
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import { Card, LoadingState, EmptyState } from '@/components/ui';
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import { ErrorBanner } from '@/components/ErrorBanner';
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import { TESTIDS } from '@/utils/testids';
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import { ClinicalKpiRow } from '@/components/clinical/ClinicalKpiRow';
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import { HistogramChart } from '@/components/clinical/HistogramChart';
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import { BoxPlotRows, type BoxRow } from '@/components/clinical/BoxPlotRows';
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import { CostVsLosScatter } from '@/components/clinical/CostVsLosScatter';
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import { CostByDiseaseChart } from '@/components/clinical/CostByDiseaseChart';
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import { DonutChart, type DonutSlice } from '@/components/clinical/DonutChart';
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import { CLINICAL_COLORS } from '@/components/clinical/chartColors';
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/** 数据是否完全为空（KPI 0 人次且各序列均空）。 */
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function isEmpty(d: InpatientClinicalResponse): boolean {
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return (
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(!d.kpis || d.kpis.total_admissions === 0) &&
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(d.los_histogram?.length ?? 0) === 0 &&
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(d.outcome_counts?.length ?? 0) === 0
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);
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}
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export function ClinicalAnalysis() {
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const [data, setData] = useState<InpatientClinicalResponse | null>(null);
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const [isLoading, setIsLoading] = useState(true);
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const [error, setError] = useState<string | null>(null);
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useEffect(() => {
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let cancelled = false;
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const fetchData = async () => {
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setIsLoading(true);
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setError(null);
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try {
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const res = await statsApi.getInpatientClinical();
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if (cancelled) return;
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setData(res);
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} catch {
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if (cancelled) return;
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setError('住院临床数据加载失败');
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} finally {
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if (!cancelled) setIsLoading(false);
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}
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};
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fetchData();
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return () => {
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cancelled = true;
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};
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}, []);
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const header = (
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<div>
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<h1 className="font-display text-[18px] font-semibold mb-1 flex items-center gap-2">
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<Activity className="w-5 h-5 text-primary" />
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住院临床分析
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</h1>
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<p className="text-[12px] text-text-secondary">
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住院天数、费用、出院结局与入院途径等临床特征分析
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</p>
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</div>
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);
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if (isLoading) {
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return (
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<div data-testid={TESTIDS.pageClinical} className="flex flex-col h-full overflow-auto p-6 space-y-6">
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{header}
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<LoadingState label="正在加载住院临床数据…" />
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</div>
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);
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}
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if (error || !data) {
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return (
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<div data-testid={TESTIDS.pageClinical} className="flex flex-col h-full overflow-auto p-6 space-y-6">
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{header}
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<ErrorBanner
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error={error ?? '住院临床数据加载失败'}
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onRetry={() => window.location.reload()}
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onDismiss={() => setError(null)}
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/>
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</div>
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);
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}
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if (isEmpty(data)) {
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return (
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<div data-testid={TESTIDS.pageClinical} className="flex flex-col h-full overflow-auto p-6 space-y-6">
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{header}
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<EmptyState title="暂无住院临床数据" description="当前筛选范围内没有可用的住院记录。" />
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</div>
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);
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}
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// 出院结局：治愈/好转在前（按严重程度排序展示更直观）。
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const outcomeSlices: DonutSlice[] = (data.outcome_counts ?? []).map((o) => ({
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name: o.outcome,
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value: o.count,
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}));
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const routeSlices: DonutSlice[] = (data.admission_route_counts ?? []).map((r) => ({
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name: r.route,
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value: r.count,
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}));
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const losBox: BoxRow[] = (data.los_by_disease ?? []).map((d) => ({
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label: d.diagnosis,
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p25: d.p25,
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median: d.median,
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p75: d.p75,
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n: d.n,
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}));
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const bmiBox: BoxRow[] = (data.bmi_by_age_band ?? []).map((d) => ({
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label: d.age_band,
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p25: d.p25,
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median: d.median,
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p75: d.p75,
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n: d.n,
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}));
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return (
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<div
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data-testid={TESTIDS.pageClinical}
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className="flex flex-col h-full overflow-auto"
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>
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<div className="p-6 space-y-6">
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{header}
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{/* KPI 行 */}
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<ClinicalKpiRow kpis={data.kpis} />
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{/* 住院天数：分布 + 各病种箱线 */}
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<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
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<Card title="住院天数分布">
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<HistogramChart data={data.los_histogram ?? []} color={CLINICAL_COLORS.los} countLabel="人次" />
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</Card>
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<Card title="各病种住院天数（P25–中位–P75）">
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<BoxPlotRows rows={losBox} unit="天" />
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</Card>
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</div>
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{/* 费用：分布 + 各病种平均费用 */}
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<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
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<Card title="住院费用分布">
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<HistogramChart data={data.cost_histogram ?? []} color={CLINICAL_COLORS.cost} countLabel="人次" />
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</Card>
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<Card title="各病种平均费用">
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<CostByDiseaseChart data={data.cost_by_disease ?? []} />
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</Card>
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</div>
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{/* 费用 vs 住院天数 散点 */}
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<Card title="费用 vs 住院天数">
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<CostVsLosScatter data={data.cost_vs_los ?? []} />
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</Card>
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{/* 出院结局 + 入院途径 双环 */}
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<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
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<Card title="出院结局构成">
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<DonutChart data={outcomeSlices} colorMap={CLINICAL_COLORS.outcome} />
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</Card>
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<Card title="入院途径构成">
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<DonutChart data={routeSlices} />
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</Card>
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</div>
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{/* 年龄别 BMI 箱线 */}
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<Card title="年龄别 BMI（P25–中位–P75）">
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<BoxPlotRows rows={bmiBox} />
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</Card>
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</div>
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</div>
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);
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}
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