"""Streamlit dashboard for InHospGlyWard-Kor (인합글라이워드코어). Run: streamlit run app.py - Ward별 ADA/KDA inpatient TIR radar / bar - basal-bolus vs sliding-scale 비율 - DKA / HHS / Hypo episode trajectory - perioperative / steroid / TPN-PN / ER subgroup KPI - discharge transition + 30-day readmission KM 본 도구는 참고용·연구용입니다 — 임상 의사결정용 아님. """ from __future__ import annotations import os import sys # Lazy import streamlit so this file can still be syntax-checked w/o streamlit. try: import streamlit as st import pandas as pd import plotly.express as px import plotly.graph_objects as go except Exception as _err: # pragma: no cover print("[InHospGlyWard-Kor] streamlit/plotly/pandas 미설치:", _err) print("pip install -r requirements.txt 후 다시 시도하세요.") sys.exit(0) HERE = os.path.dirname(os.path.abspath(__file__)) sys.path.insert(0, HERE) from modules import ingest, tir, regimen, episode, subgroup, transition, report # noqa: E402 DATA_DIR = os.path.join(HERE, "data") DISCLAIMER = ("본 대시보드는 **참고용·연구용**입니다. 임상 의사결정 도구가 아닙니다. " "표시된 데이터는 모두 de-identified surrogate (synthetic).") def ensure_data(): if not os.path.exists(os.path.join(DATA_DIR, "patients.csv")): st.warning("data/ 디렉토리에 CSV가 없습니다 — synthetic data 를 생성합니다.") ingest.generate_synthetic(out_dir=DATA_DIR, n_patients=320, seed=42) @st.cache_data(show_spinner=False) def load_bundle(): patients, poct, orders, episodes, irep = ingest.load_all(DATA_DIR) return { "patients": patients, "poct": poct, "orders": orders, "episodes": episodes, "irep": irep, } def page_overview(bundle): st.subheader("1. Ward별 ADA/KDA inpatient TIR") ward_rows = tir.compute_ward_tir(bundle["patients"], bundle["poct"]) df = pd.DataFrame([w.__dict__ for w in ward_rows]) st.dataframe(df, use_container_width=True, hide_index=True) fig = px.bar(df, x="ward", y="pct_in_range", color="kda_compliance_score", color_continuous_scale="Viridis", hover_data=["mean_bg", "pct_hypo_l1", "pct_hyper_180"], title="Ward TIR (% in target band)") st.plotly_chart(fig, use_container_width=True) # radar of TIR / hypo / hyper / persistent radar = go.Figure() metrics = ["pct_in_range", "pct_hyper_180", "pct_hypo_l1", "kda_compliance_score"] for _, row in df.iterrows(): radar.add_trace(go.Scatterpolar( r=[row[m] for m in metrics], theta=metrics, fill="toself", name=row["ward"], )) radar.update_layout(title="Ward KPI radar", polar=dict(radialaxis=dict(visible=True))) st.plotly_chart(radar, use_container_width=True) def page_regimen(bundle): st.subheader("2. Ward별 insulin regimen mix") rows = regimen.compute_regimen_mix(bundle["patients"], bundle["orders"]) df = pd.DataFrame([r.__dict__ for r in rows]) st.dataframe(df, use_container_width=True, hide_index=True) stack_cols = ["pct_basal_bolus", "pct_sliding_scale_only", "pct_iv_infusion", "pct_basal_only", "pct_no_insulin"] long = df.melt(id_vars=["ward"], value_vars=stack_cols, var_name="regimen", value_name="pct") fig = px.bar(long, x="ward", y="pct", color="regimen", barmode="stack", title="Insulin regimen mix per ward (%)") st.plotly_chart(fig, use_container_width=True) def page_episodes(bundle): st.subheader("3. DKA / HHS / Hypo / Hyper episode trajectory") rows = episode.summarize_episodes(bundle["episodes"]) df = pd.DataFrame([r.__dict__ for r in rows]) st.dataframe(df, use_container_width=True, hide_index=True) if not df.empty: fig = px.bar(df, x="episode_type", y="protocol_compliance_pct", hover_data=["n_total", "resolution_rate", "median_resolution_h"], title="ADA DKA/HHS protocol compliance (%)") st.plotly_chart(fig, use_container_width=True) fig2 = px.scatter(df, x="median_resolution_h", y="resolution_rate", size="n_total", color="episode_type", title="Resolution rate vs median resolution time") st.plotly_chart(fig2, use_container_width=True) def page_subgroups(bundle): st.subheader("4. Subgroup: perioperative / steroid / TPN-PN / ER") rows = subgroup.compute_subgroups(bundle["patients"], bundle["poct"]) df = pd.DataFrame([r.__dict__ for r in rows]) st.dataframe(df, use_container_width=True, hide_index=True) if not df.empty: fig = px.bar(df, x="subgroup", y="pct_in_140_180", hover_data=["mean_bg", "pct_hypo_l1", "pct_hyper_250", "protocol_label", "protocol_compliance_pct"], title="Subgroup 140-180 band coverage (%)") st.plotly_chart(fig, use_container_width=True) def page_transition(bundle): st.subheader("5. Discharge transition + 30-day readmission") trans = transition.summarize_transition(bundle["patients"]) cols = st.columns(3) cols[0].metric("Total patients", trans.n_total) cols[1].metric("30-day readmits", f"{trans.n_readmit_30d} ({trans.readmit_rate_pct}%)") cols[2].metric("Median time to readmit (d)", trans.median_time_to_readmit_d) st.write("**Discharge regimen mix**", trans.discharge_regimen_mix) st.write("**Readmit reason mix**", trans.readmit_reason_mix) by_reg = pd.DataFrame(transition.regimen_vs_readmit(bundle["patients"])) st.dataframe(by_reg, use_container_width=True, hide_index=True) if not by_reg.empty: fig = px.bar(by_reg, x="regimen", y="readmit_rate_pct", hover_data=["n", "n_readmit"], title="30-day readmission % by discharge regimen") st.plotly_chart(fig, use_container_width=True) km = transition.kaplan_meier_30d(bundle["patients"]) if km: km_df = pd.DataFrame(km, columns=["day", "S(t)", "n_at_risk"]) fig = px.line(km_df, x="day", y="S(t)", markers=True, title="Kaplan-Meier — 30일 내 무재입원 생존") st.plotly_chart(fig, use_container_width=True) st.dataframe(km_df, use_container_width=True, hide_index=True) def page_report(bundle): st.subheader("6. SHM GCMIP-analog KPI 리포트 (md/docx)") lang = st.radio("언어", ["ko", "en"], horizontal=True) if st.button("리포트 생성"): ward_rows = tir.compute_ward_tir(bundle["patients"], bundle["poct"]) reg_rows = regimen.compute_regimen_mix(bundle["patients"], bundle["orders"]) ep_rows = episode.summarize_episodes(bundle["episodes"]) sub_rows = subgroup.compute_subgroups(bundle["patients"], bundle["poct"]) trans = transition.summarize_transition(bundle["patients"]) km = transition.kaplan_meier_30d(bundle["patients"]) md = report.build_markdown(ward_rows, reg_rows, ep_rows, sub_rows, trans, km, language=lang) out_md = os.path.join(HERE, "reports", f"inhospglyward_{lang}.md") out_docx = os.path.join(HERE, "reports", f"inhospglyward_{lang}.docx") report.write_markdown(out_md, md) written = report.write_docx(out_docx, md, title="InHospGlyWard-Kor KPI 리포트") st.success(f"생성 완료: md={out_md} / docx={written}") st.download_button("MD 다운로드", md, file_name=os.path.basename(out_md)) def main(): st.set_page_config(page_title="InHospGlyWard-Kor", layout="wide") st.title("인합글라이워드코어 (InHospGlyWard-Kor)") st.caption("종합병원 입원 환자 glycemic management cohort dashboard") st.warning(DISCLAIMER) ensure_data() bundle = load_bundle() tabs = st.tabs([ "Ward TIR", "Regimen mix", "Episodes", "Subgroups", "Discharge & readmit", "Report", ]) with tabs[0]: page_overview(bundle) with tabs[1]: page_regimen(bundle) with tabs[2]: page_episodes(bundle) with tabs[3]: page_subgroups(bundle) with tabs[4]: page_transition(bundle) with tabs[5]: page_report(bundle) if __name__ == "__main__": main()