streamlit_app.py

"""
Nursing Case Study Builder
Streamlit app — Hugging Face Spaces (free CPU tier)
"""

import streamlit as st
from cases.bank import (
    get_all_cases, get_categories, get_by_category, get_by_difficulty,
    get_by_id, search_cases, get_difficulties,
)

# ---------------------------------------------------------------------------
# Page config
# ---------------------------------------------------------------------------
st.set_page_config(
    page_title="Nursing Case Studies — Student Nurses",
    page_icon="🏥",
    layout="wide",
    initial_sidebar_state="expanded",
)

# ---------------------------------------------------------------------------
# CSS
# ---------------------------------------------------------------------------
st.markdown("""
<style>
.case-card {
    background:#f8fafc; border:1px solid #d0dae8;
    border-radius:10px; padding:1.2rem 1.4rem; margin-bottom:1rem;
}
.patient-banner {
    background:#e3f2fd; border-left:5px solid #1565c0;
    padding:0.8rem 1.2rem; border-radius:4px; margin-bottom:0.8rem;
}
.warning-banner {
    background:#fff3e0; border-left:5px solid #e65100;
    padding:0.8rem 1.2rem; border-radius:4px; margin-bottom:0.8rem;
}
.critical-banner {
    background:#fce4ec; border-left:5px solid #c62828;
    padding:0.8rem 1.2rem; border-radius:4px; margin-bottom:0.8rem;
}
.success-banner {
    background:#e8f5e9; border-left:5px solid #2e7d32;
    padding:0.8rem 1.2rem; border-radius:4px; margin-bottom:0.8rem;
}
.info-banner {
    background:#e8eaf6; border-left:5px solid #3949ab;
    padding:0.8rem 1.2rem; border-radius:4px; margin-bottom:0.8rem;
}
.badge-beginner   { background:#e8f5e9; color:#2e7d32; padding:3px 10px;
                    border-radius:12px; font-size:0.78em; font-weight:700; }
.badge-intermediate { background:#fff8e1; color:#f57f17; padding:3px 10px;
                      border-radius:12px; font-size:0.78em; font-weight:700; }
.badge-advanced   { background:#fce4ec; color:#c62828; padding:3px 10px;
                    border-radius:12px; font-size:0.78em; font-weight:700; }
.vital-box {
    background:#f5f5f5; border-radius:8px; padding:0.6rem 1rem;
    text-align:center; margin-bottom:0.4rem;
}
.nd-card {
    background:#fafafa; border:1px solid #e0e0e0;
    border-radius:8px; padding:1rem 1.2rem; margin-bottom:0.8rem;
}
</style>
""", unsafe_allow_html=True)


# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
DIFF_COLOURS = {"Beginner": "#2e7d32", "Intermediate": "#f57f17", "Advanced": "#c62828"}
CAT_ICONS = {
    "Cardiovascular": "❤️",
    "Respiratory": "🫁",
    "Endocrine": "🩸",
    "Neurological": "🧠",
    "Multi-system / Infectious": "🦠",
    "Musculoskeletal / Surgical": "🦴",
    "Maternal / Obstetric": "🤰",
    "Paediatric": "👶",
    "Mental Health / Toxicology": "💜",
    "Renal": "💧",
}


def diff_badge(difficulty: str) -> str:
    cls = f"badge-{difficulty.lower()}"
    return f'<span class="{cls}">{difficulty}</span>'


def cat_icon(category: str) -> str:
    return CAT_ICONS.get(category, "📋")


def init_state():
    if "selected_case_id" not in st.session_state:
        st.session_state.selected_case_id = None
    if "adpie_answers" not in st.session_state:
        st.session_state.adpie_answers = {}
    if "quiz_answers" not in st.session_state:
        st.session_state.quiz_answers = {}
    if "quiz_submitted" not in st.session_state:
        st.session_state.quiz_submitted = False
    if "careplan_items" not in st.session_state:
        st.session_state.careplan_items = {}


init_state()

# ---------------------------------------------------------------------------
# Sidebar
# ---------------------------------------------------------------------------
with st.sidebar:
    st.markdown("## 🏥 Case Studies")
    st.divider()

    all_cases = get_all_cases()
    categories = get_categories()
    difficulties = get_difficulties()

    st.markdown("**Quick Stats**")
    st.markdown(f"- 📋 {len(all_cases)} clinical cases")
    st.markdown(f"- 🏷️ {len(categories)} body systems")
    diff_counts = {d: len(get_by_difficulty(d)) for d in difficulties}
    for d, n in diff_counts.items():
        colour = DIFF_COLOURS[d]
        st.markdown(f'- <span style="color:{colour}">⬤</span> {d}: {n} cases', unsafe_allow_html=True)

    st.divider()
    st.markdown("**Cases by System**")
    for cat in categories:
        icon = cat_icon(cat)
        n = len(get_by_category(cat))
        st.markdown(f"{icon} **{cat}** — {n}")

    st.divider()
    st.markdown("**ADPIE Framework**")
    st.markdown("""
- **A**ssessment
- **D**iagnosis
- **P**lanning
- **I**mplementation
- **E**valuation
    """)
    st.divider()
    st.caption(
        "Part of the [Nursing Citizen Development](https://huggingface.co/NurseCitizenDeveloper) suite"
    )

# ---------------------------------------------------------------------------
# Header
# ---------------------------------------------------------------------------
st.title("🏥 Nursing Case Studies")
st.caption(
    "10 clinical scenarios across major body systems · ADPIE Framework · "
    "Nursing Diagnoses · Care Planning · For educational purposes only"
)

# ---------------------------------------------------------------------------
# Tabs
# ---------------------------------------------------------------------------
tab_lib, tab_case, tab_adpie, tab_quiz, tab_plan = st.tabs([
    "📚 Case Library",
    "🔍 Full Case",
    "🧠 ADPIE Reasoning",
    "❓ Quiz Questions",
    "📝 Care Plan",
])


# ========================= CASE LIBRARY =====================================
with tab_lib:
    st.subheader("📚 Clinical Case Library")
    st.caption("Browse 10 evidence-based patient scenarios. Click any case to open it.")

    col_search, col_diff, col_cat = st.columns([3, 2, 2])
    with col_search:
        lib_query = st.text_input("🔍 Search cases", placeholder="e.g. sepsis, chest pain, stroke")
    with col_diff:
        diff_filter = st.selectbox("Difficulty", ["All"] + difficulties)
    with col_cat:
        cat_filter = st.selectbox("Body system", ["All"] + categories)

    st.divider()

    # Filter
    if lib_query.strip():
        display_cases = search_cases(lib_query)
        if not display_cases:
            st.info(f"No cases found for '{lib_query}'.")
    elif diff_filter != "All" and cat_filter != "All":
        display_cases = [c for c in get_by_category(cat_filter)
                         if c["difficulty"] == diff_filter]
    elif diff_filter != "All":
        display_cases = get_by_difficulty(diff_filter)
    elif cat_filter != "All":
        display_cases = get_by_category(cat_filter)
    else:
        display_cases = all_cases

    st.markdown(f"**Showing {len(display_cases)} case(s)**")
    st.markdown("")

    for case in display_cases:
        icon = cat_icon(case["category"])
        col_a, col_b = st.columns([5, 1])
        with col_a:
            st.markdown(
                f'<div class="case-card">'
                f'<b>{icon} {case["title"]}</b> &nbsp;'
                f'{diff_badge(case["difficulty"])}<br/>'
                f'<small>🏷️ {case["category"]} &nbsp;·&nbsp; '
                f'👤 {case["patient"]["name"]}, {case["patient"]["age"]}yo &nbsp;·&nbsp; '
                f'🔖 {", ".join(case["tags"][:4])}</small>'
                f'</div>',
                unsafe_allow_html=True
            )
        with col_b:
            if st.button("Open →", key=f"open_{case['id']}", use_container_width=True):
                st.session_state.selected_case_id = case["id"]
                st.session_state.quiz_answers = {}
                st.session_state.quiz_submitted = False
                st.session_state.adpie_answers = {}
                st.success(f"✅ Case loaded: **{case['title']}** — navigate to other tabs.")


# ========================= FULL CASE ========================================
with tab_case:
    st.subheader("🔍 Full Case Study")

    if not st.session_state.selected_case_id:
        st.info("💡 Select a case from the **Case Library** tab to begin.")
    else:
        case = get_by_id(st.session_state.selected_case_id)
        if not case:
            st.error("Case not found.")
        else:
            p = case["patient"]

            # Title banner
            icon = cat_icon(case["category"])
            st.markdown(
                f'<div class="patient-banner">'
                f'<h3 style="margin:0">{icon} {case["title"]}</h3>'
                f'<span>{diff_badge(case["difficulty"])}</span> &nbsp;'
                f'<small>{case["category"]}</small>'
                f'</div>',
                unsafe_allow_html=True
            )

            # Learning objectives
            with st.expander("🎯 Learning Objectives", expanded=False):
                for lo in case["learning_objectives"]:
                    st.markdown(f"• {lo}")

            st.divider()

            # Patient demographics
            col1, col2 = st.columns(2)
            with col1:
                st.markdown("### 👤 Patient Profile")
                st.markdown(f"**Name:** {p['name']}")
                st.markdown(f"**Age / Gender:** {p['age']} years · {p['gender']}")
                st.markdown(f"**Weight / Height:** {p['weight_kg']} kg · {p['height_cm']} cm")
                st.markdown(f"**Allergies:** {', '.join(p['allergies'])}")

            with col2:
                st.markdown("### 📋 Medical History")
                st.markdown("**Past Medical History:**")
                for h in p["pmhx"]:
                    st.markdown(f"• {h}")
                st.markdown(f"**Medications:** {', '.join(p['medications'])}")
                st.markdown(f"**Social:** {p['social']}")
                st.markdown(f"**Family History:** {p.get('family_hx', 'Nil relevant')}")

            st.divider()

            # Presentation
            st.markdown("### 🚨 Presentation")
            st.markdown(
                f'<div class="warning-banner">📋 {case["presentation"]}</div>',
                unsafe_allow_html=True
            )

            # Vital signs
            st.markdown("### 📊 Vital Signs")
            vitals = case["vitals"]
            v_keys = list(vitals.keys())
            cols = st.columns(min(len(v_keys), 5))
            for i, key in enumerate(v_keys):
                with cols[i % len(cols)]:
                    st.markdown(
                        f'<div class="vital-box"><small>{key}</small><br/>'
                        f'<b>{vitals[key]}</b></div>',
                        unsafe_allow_html=True
                    )

            # Physical exam
            st.markdown("### 🩺 Physical Examination")
            st.markdown(case["physical_exam"])

            st.divider()

            # Investigations
            st.markdown("### 🔬 Investigations")
            inv = case["investigations"]
            inv_keys = list(inv.keys())
            col_a, col_b = st.columns(2)
            for i, key in enumerate(inv_keys):
                col = col_a if i % 2 == 0 else col_b
                with col:
                    val = inv[key]
                    flag = "🔴 " if ("↑↑" in val or "CRITICAL" in val or "severe" in val.lower()) else ""
                    st.markdown(f"**{key}:** {flag}{val}")

            st.divider()

            # Medical diagnosis
            st.markdown("### 🏥 Medical Diagnosis")
            st.markdown(
                f'<div class="critical-banner">⚕️ <b>{case["medical_diagnosis"]}</b></div>',
                unsafe_allow_html=True
            )

            # Nursing priorities
            st.markdown("### 🔔 Nursing Priorities")
            for i, priority in enumerate(case["nursing_priorities"], 1):
                colour = "#c62828" if i <= 3 else "#e65100" if i <= 6 else "#2e7d32"
                st.markdown(
                    f'<div style="padding:4px 0"><span style="color:{colour};font-weight:700">'
                    f'{i}.</span> {priority}</div>',
                    unsafe_allow_html=True
                )


# ========================= ADPIE REASONING ==================================
with tab_adpie:
    st.subheader("🧠 ADPIE Clinical Reasoning Framework")
    st.caption("Work through the case using the ADPIE nursing process. Reveal the model answer when ready.")

    if not st.session_state.selected_case_id:
        st.info("💡 Select a case from the **Case Library** tab first.")
    else:
        case = get_by_id(st.session_state.selected_case_id)
        adpie = case["adpie"]

        st.markdown(
            f'<div class="patient-banner">🏥 Active Case: <b>{case["title"]}</b> &nbsp;·&nbsp; '
            f'👤 {case["patient"]["name"]}</div>',
            unsafe_allow_html=True
        )

        st.markdown("**Instructions:** Read the case, then write your own answers before revealing the model answers.")
        st.divider()

        steps = [
            ("A", "Assessment", "📋", "What are the key subjective and objective findings?", "assessment"),
            ("D", "Nursing Diagnosis", "🔴", "Identify priority nursing diagnoses (NANDA format: problem r/t aetiology AEB evidence)", "diagnosis"),
            ("P", "Planning", "🎯", "What are your SMART nursing goals (short and long term)?", "planning"),
            ("I", "Implementation", "⚙️", "What nursing interventions will you implement and why?", "implementation"),
            ("E", "Evaluation", "✅", "How will you evaluate if goals were met? What actually happened?", "evaluation"),
        ]

        for letter, title, icon, prompt, key in steps:
            st.markdown(f"### {icon} {letter} — {title}")
            st.markdown(f"*{prompt}*")

            # Student input
            ans_key = f"adpie_{case['id']}_{key}"
            student_ans = st.text_area(
                f"Your {title}:",
                value=st.session_state.adpie_answers.get(ans_key, ""),
                height=100,
                key=f"adpie_input_{case['id']}_{key}",
                placeholder=f"Write your {title.lower()} here...",
                label_visibility="collapsed",
            )
            st.session_state.adpie_answers[ans_key] = student_ans

            # Reveal model answer
            with st.expander(f"🔍 Reveal Model Answer — {title}"):
                st.markdown(adpie[key])

            st.markdown("")

        # Nursing diagnoses deep-dive
        st.divider()
        st.markdown("### 🔴 Nursing Diagnoses — Detailed")
        for nd in case["nursing_diagnoses"]:
            with st.expander(f"📌 {nd['diagnosis']}", expanded=False):
                st.markdown(
                    f'<div class="nd-card">'
                    f'<b>Supporting Evidence:</b> {nd["evidence"]}<br/><br/>'
                    f'<b>Goal:</b> {nd["goal"]}'
                    f'</div>',
                    unsafe_allow_html=True
                )
                st.markdown("**Nursing Interventions:**")
                for inv in nd["interventions"]:
                    st.markdown(f"• {inv}")


# ========================= QUIZ QUESTIONS ===================================
with tab_quiz:
    st.subheader("❓ Case-Based Quiz Questions")
    st.caption("NCLEX-style questions based on the active case. Select answers and submit for feedback.")

    if not st.session_state.selected_case_id:
        st.info("💡 Select a case from the **Case Library** tab first.")
    else:
        case = get_by_id(st.session_state.selected_case_id)

        st.markdown(
            f'<div class="patient-banner">🏥 Active Case: <b>{case["title"]}</b></div>',
            unsafe_allow_html=True
        )

        # Generate case-specific questions dynamically
        nd_names = [nd["diagnosis"].split(" related to")[0] for nd in case["nursing_diagnoses"]]
        priorities = case["nursing_priorities"]

        # Build 5 consistent case-based questions
        questions = [
            {
                "q": f"Based on the case of {case['patient']['name']}, which nursing diagnosis should be prioritised FIRST?",
                "options": nd_names + ["Pain management only"],
                "answer": 0,
                "rationale": (
                    f"The priority nursing diagnosis is '{nd_names[0]}'. "
                    f"Using Maslow's hierarchy, physiological and safety needs are addressed first. "
                    f"The supporting evidence is: {case['nursing_diagnoses'][0]['evidence']}."
                ),
            },
            {
                "q": f"What is the FIRST priority nursing action for {case['patient']['name']}?",
                "options": [
                    priorities[0] if len(priorities) > 0 else "Call the doctor",
                    priorities[2] if len(priorities) > 2 else "Reassess vitals",
                    "Complete full medication history",
                    "Discharge planning",
                ],
                "answer": 0,
                "rationale": (
                    f"The immediate priority is: '{priorities[0]}'. "
                    "Nursing priorities are ordered by urgency — life-threatening physiological "
                    "problems must be addressed before less urgent concerns."
                ),
            },
            {
                "q": f"Which assessment finding in {case['patient']['name']}'s case is MOST concerning?",
                "options": list(case["vitals"].items())[:4],
                "answer": 0,
                "rationale": (
                    "The most concerning vital sign is the first listed, which is outside normal limits. "
                    "Always assess using ABCDE — Airway, Breathing, Circulation, Disability, Exposure — "
                    "to prioritise life-threatening abnormalities."
                ),
                "is_vitals": True,
            },
            {
                "q": f"The goal for the priority nursing diagnosis in this case is: '{case['nursing_diagnoses'][0]['goal']}'. Which nursing intervention BEST addresses this goal?",
                "options": case["nursing_diagnoses"][0]["interventions"][:4],
                "answer": 0,
                "rationale": (
                    f"The first listed intervention directly addresses the priority goal. "
                    f"Rationale: {case['nursing_diagnoses'][0]['interventions'][0]}"
                ),
            },
            {
                "q": f"In evaluating the outcomes for {case['patient']['name']}, which finding would indicate the PRIORITY nursing goal has been MET?",
                "options": [
                    case["nursing_diagnoses"][0]["goal"],
                    "Patient is pain-free",
                    "Family is satisfied with care",
                    "All documentation is complete",
                ],
                "answer": 0,
                "rationale": (
                    f"The priority goal for this case is: '{case['nursing_diagnoses'][0]['goal']}'. "
                    "Goals must be patient-centred, measurable, and time-bound (SMART). "
                    "This outcome directly measures resolution of the priority nursing diagnosis."
                ),
            },
        ]

        if st.button("🔄 Reset Quiz", use_container_width=False):
            st.session_state.quiz_answers = {}
            st.session_state.quiz_submitted = False
            st.rerun()

        st.divider()

        for i, q in enumerate(questions):
            st.markdown(f"**Question {i + 1}:** {q['q']}")

            if q.get("is_vitals"):
                opts = [f"{k}: {v}" for k, v in q["options"]]
            else:
                opts = q["options"]

            selected = st.radio(
                f"Q{i+1}",
                options=opts,
                key=f"quiz_{case['id']}_q{i}",
                label_visibility="collapsed",
            )
            st.session_state.quiz_answers[i] = selected

            if st.session_state.quiz_submitted:
                correct_opt = opts[q["answer"]]
                if selected == correct_opt:
                    st.markdown(
                        f'<div class="success-banner">✅ <b>Correct!</b> {q["rationale"]}</div>',
                        unsafe_allow_html=True
                    )
                else:
                    st.markdown(
                        f'<div class="critical-banner">❌ <b>Incorrect.</b> '
                        f'Correct answer: <b>{correct_opt}</b><br/>{q["rationale"]}</div>',
                        unsafe_allow_html=True
                    )

            st.markdown("")

        col_sub, col_score = st.columns([2, 3])
        with col_sub:
            if st.button("✅ Submit Answers", type="primary", use_container_width=True):
                st.session_state.quiz_submitted = True
                st.rerun()

        if st.session_state.quiz_submitted:
            score = 0
            for i, q in enumerate(questions):
                if q.get("is_vitals"):
                    opts = [f"{k}: {v}" for k, v in q["options"]]
                else:
                    opts = q["options"]
                if st.session_state.quiz_answers.get(i) == opts[q["answer"]]:
                    score += 1

            pct = round((score / len(questions)) * 100)
            colour = "#2e7d32" if pct >= 80 else "#e65100" if pct >= 60 else "#c62828"
            with col_score:
                st.markdown(
                    f'<div style="padding:0.6rem 1rem; background:#f5f5f5; border-radius:8px; '
                    f'font-size:1.1em; font-weight:700; color:{colour};">'
                    f'Score: {score} / {len(questions)} ({pct}%)</div>',
                    unsafe_allow_html=True
                )


# ========================= CARE PLAN ========================================
with tab_plan:
    st.subheader("📝 Nursing Care Plan Builder")
    st.caption("Build a structured care plan for the active case using the NANDA-NIC-NOC framework.")

    if not st.session_state.selected_case_id:
        st.info("💡 Select a case from the **Case Library** tab first.")
    else:
        case = get_by_id(st.session_state.selected_case_id)

        st.markdown(
            f'<div class="patient-banner">🏥 <b>{case["patient"]["name"]}</b> · '
            f'{case["patient"]["age"]} y/o · {case["medical_diagnosis"]}</div>',
            unsafe_allow_html=True
        )

        st.markdown("Complete the care plan below. Toggle **Show Model Answer** to reveal guidance.")
        st.divider()

        for idx, nd in enumerate(case["nursing_diagnoses"]):
            st.markdown(f"### 📌 Nursing Diagnosis {idx + 1}")
            st.markdown(
                f'<div class="nd-card"><b>{nd["diagnosis"]}</b></div>',
                unsafe_allow_html=True
            )

            cp_key = f"cp_{case['id']}_{idx}"
            if cp_key not in st.session_state.careplan_items:
                st.session_state.careplan_items[cp_key] = {
                    "diagnosis": "", "goal": "", "interventions": "", "evaluation": ""
                }

            c1, c2 = st.columns(2)

            with c1:
                st.markdown("**Your Nursing Diagnosis (NANDA format):**")
                nd_input = st.text_area(
                    "nd",
                    value=st.session_state.careplan_items[cp_key]["diagnosis"],
                    height=80,
                    placeholder="[Problem] related to [Aetiology] as evidenced by [Signs/Symptoms]",
                    key=f"{cp_key}_nd",
                    label_visibility="collapsed",
                )
                st.session_state.careplan_items[cp_key]["diagnosis"] = nd_input

                st.markdown("**Your SMART Goal:**")
                goal_input = st.text_area(
                    "goal",
                    value=st.session_state.careplan_items[cp_key]["goal"],
                    height=80,
                    placeholder="Patient will [outcome] by [time] as measured by [indicator]",
                    key=f"{cp_key}_goal",
                    label_visibility="collapsed",
                )
                st.session_state.careplan_items[cp_key]["goal"] = goal_input

            with c2:
                st.markdown("**Your Nursing Interventions (with rationale):**")
                inv_input = st.text_area(
                    "interventions",
                    value=st.session_state.careplan_items[cp_key]["interventions"],
                    height=80,
                    placeholder="1. Intervention (Rationale)\n2. Intervention (Rationale)\n3. ...",
                    key=f"{cp_key}_inv",
                    label_visibility="collapsed",
                )
                st.session_state.careplan_items[cp_key]["interventions"] = inv_input

                st.markdown("**Evaluation Criteria:**")
                eval_input = st.text_area(
                    "evaluation",
                    value=st.session_state.careplan_items[cp_key]["evaluation"],
                    height=80,
                    placeholder="Goal met / partially met / not met because...",
                    key=f"{cp_key}_eval",
                    label_visibility="collapsed",
                )
                st.session_state.careplan_items[cp_key]["evaluation"] = eval_input

            # Model answer toggle
            with st.expander("🔍 Show Model Answer"):
                st.markdown(f"**Diagnosis:** {nd['diagnosis']}")
                st.markdown(f"**Evidence:** {nd['evidence']}")
                st.markdown(f"**Goal:** {nd['goal']}")
                st.markdown("**Model Interventions:**")
                for i in nd["interventions"]:
                    st.markdown(f"• {i}")

            st.divider()

        # Print / export summary
        if any(
            any(v for v in st.session_state.careplan_items.get(f"cp_{case['id']}_{i}", {}).values())
            for i in range(len(case["nursing_diagnoses"]))
        ):
            st.markdown("### 📄 Care Plan Summary")
            summary_lines = [f"# Care Plan: {case['patient']['name']}\n",
                             f"**Diagnosis:** {case['medical_diagnosis']}\n"]
            for idx, nd in enumerate(case["nursing_diagnoses"]):
                cp_key = f"cp_{case['id']}_{idx}"
                item = st.session_state.careplan_items.get(cp_key, {})
                summary_lines.append(f"\n## Nursing Diagnosis {idx+1}\n")
                summary_lines.append(f"**Diagnosis:** {item.get('diagnosis', '—')}\n")
                summary_lines.append(f"**Goal:** {item.get('goal', '—')}\n")
                summary_lines.append(f"**Interventions:** {item.get('interventions', '—')}\n")
                summary_lines.append(f"**Evaluation:** {item.get('evaluation', '—')}\n")

            summary_text = "\n".join(summary_lines)
            st.download_button(
                "⬇️ Download Care Plan (.txt)",
                data=summary_text,
                file_name=f"care_plan_{case['id']}.txt",
                mime="text/plain",
                use_container_width=False,
            )


# ---------------------------------------------------------------------------
# Footer
# ---------------------------------------------------------------------------
st.divider()
st.caption(
    "Cases are fictional composite scenarios for educational purposes only. "
    "Always follow your institution's clinical guidelines, evidence-based practice, "
    "and clinical supervisor guidance in real patient care."
)