#!/usr/bin/env python3
"""
Paper-Native Clinical PICO & Entity Parser for UnsolvedMedical v3.0.0.

Transforms raw peer-reviewed medical paper titles and metadata into:
  1. Complete, non-truncated, grammatically clean clinical topics (`clean_topic`)
  2. Paper-verified `condition_or_health_state` and `population` (eliminating cross-condition chimeras
     when a paper addresses a condition outside the 20 sub-domain defaults)
  3. Paper-specific `intervention_exposure_test_or_predictor` (`name`, `kind`, `details`)
  4. Paper-specific `comparator_or_reference`
  5. 100 natural clinical research question formulations (5 distinct structural variants x 20 question types)
     with distinct `statement`, concise `clean_statement`, and patient-accessible `plain_language_statement`.
"""

import html
import re

SUBTITLE_BOILERPLATE_RE = re.compile(
    r"\s*[:–—-]\s*(a |an |the )?(systematic review|meta-analysis|narrative review|scoping review|"
    r"literature review|umbrella review|comprehensive review|integrative review|minireview|mini-review|"
    r"review of|updated review|critical review|overview of|retrospective|prospective|multicenter|"
    r"multi-center|single-center|single center|randomized|randomised|phase [i1234v/]+|pilot study|"
    r"cohort study|cross-sectional|observational study|clinical trial|real-world|secondary analysis|"
    r"post-hoc|post hoc|sub-study|substudy|preliminary|comparative study|mendelian randomization|"
    r"network meta-analysis|pooled analysis|propensity score|outcomes from|results from|insights from|"
    r"findings from|lessons from|experience from|report from|evidence-based|consensus statement|"
    r"position paper|clinical practice guideline|expert consensus|multidisciplinary|"
    r"international delphi|delphi consensus|national survey|cross-sectional survey).*$",
    re.I,
)

PREFIX_BOILERPLATE_RE = re.compile(
    r"^(a |an |the )?(systematic review and meta-analysis of|systematic review of|meta-analysis of|"
    r"narrative review of|scoping review of|comprehensive review of|clinical overview of|overview of|"
    r"update on|updates in|current perspectives on|emerging role of|advances in|new insights into|"
    r"recent advances in|state of the art in|clinical management of|management of|current state of|"
    r"exploring the|understanding the|investigating the|evaluating the|assessing the|"
    r"reassessing the role of|reassessing|role of|the role of|development of a|development of|"
    r"predictive value of|prognostic value of|diagnostic value of|clinical utility of|"
    r"clinical significance of|significance of|expert consensus on the|expert consensus on|"
    r"consensus statement on|international consensus on|diagnosis and monitoring of|diagnosis and management of|"
    r"diagnosis and treatment of|prevention and treatment of|efficacy and safety of|effectiveness and safety of|"
    r"efficacy of|effectiveness of|impact of the|impact of|effect of|effects of|"
    r"influence of|the influence of|association between|association of|relationship between)\s+",
    re.I,
)

DANGLING_TAIL_RE = re.compile(
    r"\s+\b(a|an|the|in|of|for|with|without|and|or|by|to|from|on|at|among|between|after|before|"
    r"during|under|into|via|versus|vs|through|across|within|towards|toward|against|upon|using|"
    r"including|following|regarding|concerning|based|associated|related|compared|comparing|"
    r"as|such|whether|while|when|where|who|which|that|whose|undergoing|receiving|treated|"
    r"diagnosed|presenting|living|incorporating|combining|targeting|evaluating|assessing|"
    r"predicting|preventing|managing|early|late|acute|chronic|severe|moderate|mild|advanced|"
    r"metastatic|primary|secondary|novel|new|current|emerging|clinical|human|pediatric|adult|"
    r"older|elderly|high-risk|low-risk|refractory|relapsed|recurrent)\b[:;,\-–—.]*$",
    re.I,
)

# Non-distinctive modifier words that must NOT trigger a specific sub-domain disease match on their own
GENERIC_CONDITION_MODIFIERS = {
    "with", "without", "from", "after", "before", "during", "early", "stage", "late", "acute",
    "chronic", "severe", "moderate", "mild", "advanced", "metastatic", "unresectable", "resectable",
    "borderline", "locally", "localized", "high", "risk", "low", "relapsed", "relapsing", "refractory",
    "recurrent", "first", "second", "line", "complete", "remission", "positive", "negative", "wildtype",
    "proficient", "deficient", "dependent", "resistant", "progressing", "associated", "related",
    "induced", "mediated", "primary", "secondary", "adult", "adults", "children", "pediatric",
    "neonatal", "adolescent", "older", "elderly", "maternal", "pregnant", "postpartum", "patients",
    "patient", "care", "health", "management", "treatment", "therapy", "disease", "diseases",
    "syndrome", "syndromes", "disorder", "disorders", "condition", "conditions", "infection",
    "infections", "cancer", "carcinoma", "adenocarcinoma", "malignancy", "tumor", "tumors",
    "cell", "small", "large", "diffuse", "factor", "inhibitors", "inhibitor", "mutations", "driver",
    "pathway", "inhibition", "targetable", "neutralizing", "viii", "active", "grade", "serous",
    "chemoimmunotherapy", "blockade", "allogeneic", "hsct", "transplant", "transfusion",
    "long", "term", "short", "type", "types", "form", "forms", "rate", "rates", "systemic",
    "idiopathic", "hereditary", "familial", "congenital", "acquired", "uncomplicated", "complicated",
    "stanford", "persistent", "paroxysmal", "sustained", "protracted", "maintenance", "discontinuation",
    "withdrawal", "postoperative", "perioperative", "preoperative", "intensive", "critical",
    "critically", "emergency", "outpatient", "inpatient", "community", "hospital", "surgical",
    "medical", "clinical", "human", "cohort", "onset", "status", "loss", "pain", "failure", "injury",
}

# Broad umbrella disease nouns that require at least one accompanying qualifier token when present in base_cond_name
UMBRELLA_DISEASE_NOUNS = {
    "amyloidosis", "dissection", "aneurysm", "stenosis", "regurgitation", "insufficiency",
    "cardiomyopathy", "neuropathy", "nephropathy", "retinopathy", "hepatitis", "cirrhosis",
    "fibrosis", "arthritis", "vasculitis", "colitis", "epilepsy", "dementia", "depression",
    "anemia", "thrombocytopenia", "hypertension", "diabetes", "asthma", "stroke", "hemorrhage",
    "infarction", "thrombosis", "embolism", "leukemia", "lymphoma", "myeloma", "sarcoma",
    "melanoma", "glioma", "pneumonia", "meningitis", "encephalitis", "endocarditis", "myocarditis",
    "pancreatitis", "sepsis", "glaucoma", "uveitis", "dermatitis", "psoriasis", "alopecia",
    "lupus", "myositis", "osteoporosis", "osteoarthritis", "fracture", "fractures", "infertility",
    "dystrophy", "hemophilia", "thalassemia",
}

# Explicit comparison pattern: "<Arm A> versus/vs./compared with <Arm B>"
EXPLICIT_COMP_RE = re.compile(
    r"(?P<arm_a>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{3,75}?)\s+"
    r"(?:versus|vs\.?|compared with|compared to)\s+"
    r"(?P<arm_b>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{4,75}?)"
    r"(?:\s+(?:in|for|among|after|during|with|on|to)\b|$)",
    re.I,
)

# "Role/Efficacy/Safety/Value/Impact of <Intervention/Factor> in/for/on <Condition/Outcome>"
OF_PATTERN_RE = re.compile(
    r"^(?:the\s+)?(?:role|efficacy|effectiveness|safety|impact|effects?|influence|value|utility|feasibility|"
    r"performance|accuracy|use|application|addition|combination|integration|implementation|"
    r"optimization|evaluation|assessment|association|relationship|correlation|"
    r"predictive value|prognostic value|diagnostic value|diagnostic accuracy|clinical utility|"
    r"clinical significance|significance|therapeutic potential|mechanisms?|pathogenesis|determinants|predictors|biomarkers|"
    r"reassessing the role|development|genetics)\s+of\s+(?:a\s+|an\s+|the\s+)?"
    r"(?P<focus>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{5,90}?)"
    r"(?:\s+(?:in|for|among|on|to guide|after|during|with)\s+(?P<context>[A-Za-z0-9].+))?$",
    re.I,
)

# "<Intervention/Biomarker> for/in the treatment/management/diagnosis/prediction/prevention of <Condition>"
FOR_ACTION_RE = re.compile(
    r"^(?P<focus>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{5,85}?)\s+"
    r"(?:for|in|to guide)\s+(?:the\s+)?(?:treatment|management|prevention|diagnosis|early detection|"
    r"prediction|prognosis|risk stratification|monitoring|rehabilitation|mitigation|control|adjuvant|neoadjuvant)\s*(?:of\s+)?"
    r"(?P<context>[A-Za-z0-9].+)$",
    re.I,
)

# "<Intervention/Exposure> and <Outcome/Condition> in <Population>"
AND_IN_RE = re.compile(
    r"^(?P<focus>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{5,75}?)\s+and\s+"
    r"(?P<outcome>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{4,70}?)\s+"
    r"(?:in|among|after|during)\s+(?P<context>[A-Za-z0-9].+)$",
    re.I,
)

# Participial/Gerund lead: "Targeting/Predicting/De-escalating <X> in <Y>"
GERUND_RE = re.compile(
    r"^(?:targeting|inhibiting|modulating|predicting|stratifying|monitoring|optimizing|"
    r"de-escalating|reassessing|mapping|decoding|unraveling|evaluating|comparing|enhancing|"
    r"preventing|overcoming|identifying|quantifying|characterizing)\s+(?:the\s+|a\s+|an\s+)?"
    r"(?P<focus>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{5,85}?)"
    r"(?:\s+(?:in|for|among|after|during|with|to)\s+(?P<context>[A-Za-z0-9].+))?$",
    re.I,
)

# Extract condition phrase after "in patients with <X>", "in <X>", "of <X>", "for <X>"
COND_PREP_RE = re.compile(
    r"\b(?:in patients with|among patients with|in adults with|in children with|in women with|in men with|in individuals with|"
    r"in the management of|in the treatment of|for the treatment of|in|among)\s+"
    r"(?P<cond>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{6,95})$",
    re.I,
)


def _balance_parens(text: str) -> str:
    t = text.strip()
    while t.startswith("(") and t.endswith(")") and t[1:-1].count("(") == t[1:-1].count(")"):
        t = t[1:-1].strip()
    if t.count("(") > t.count(")"):
        last_open = t.rfind("(")
        if len(t) - last_open <= 15:
            t = t + ")"
        else:
            t = t[:last_open].strip()
    elif t.count(")") > t.count("("):
        t = t.replace(")", "").strip()
    return t


def clean_complete_topic(raw_title: str) -> str:
    """
    Extract a complete, self-contained clinical topic phrase from a peer-reviewed paper title
    without mid-phrase truncation or dangling prepositions/adjectives.
    """
    t = html.unescape(raw_title or "")
    t = re.sub(r"<[^>]+>", "", t).strip()
    t = re.sub(r"\s+", " ", t).rstrip(".:;?-–— ")
    t = SUBTITLE_BOILERPLATE_RE.sub("", t).strip()

    if ":" in t:
        p0, p1 = [p.strip() for p in t.split(":", 1)]
        if p0.lower() in {"research review", "clinical review", "special report", "consensus statement", "clinical practice guideline", "original article", "review article"} and len(p1) >= 24:
            t = p1
        elif len(p0) >= 28:
            t = p0
        elif len(p1) >= 28 and not SUBTITLE_BOILERPLATE_RE.search(": " + p1):
            t = f"{p0} ({p1})" if len(p0) + len(p1) < 120 else p1

    t = re.sub(
        r"^(a |an |the )?(systematic review and meta-analysis of|systematic review of|meta-analysis of|"
        r"narrative review of|scoping review of|comprehensive review of|clinical overview of|overview of|"
        r"update on|updates in|current perspectives on)\s+",
        "",
        t,
        flags=re.I,
    ).strip()

    if len(t) > 215:
        clause_break = re.search(r"[,;–—]\s+", t[110:])
        if clause_break:
            t = t[: 110 + clause_break.start()].strip()
        else:
            t = t[:210].rsplit(" ", 1)[0].strip()

    t = _balance_parens(t)
    t = re.sub(r"[:;,\-–—/]+\s*$", "", t).strip()
    while True:
        new_t = DANGLING_TAIL_RE.sub("", t).strip()
        new_t = re.sub(r"[:;,\-–—/]+\s*$", "", new_t).strip()
        if new_t == t or len(new_t) < 22:
            break
        t = new_t

    t = _balance_parens(t)
    if t and t[0].islower():
        t = t[0].upper() + t[1:]
    return t


def _clean_extracted_entity(phrase: str) -> str:
    p = phrase.strip(" ,:;.-–—")
    p = PREFIX_BOILERPLATE_RE.sub("", p).strip(" ,:;.-–—")
    p = re.sub(r"\s+\b(patients|individuals|adults|children|subjects|cases)\s*$", "", p, flags=re.I).strip()
    while True:
        np = DANGLING_TAIL_RE.sub("", p).strip(" ,:;.-–—")
        if np == p or len(np) < 8:
            break
        p = np
    p = _balance_parens(p)
    if p and p[0].islower():
        p = p[0].upper() + p[1:]
    return p


def _distinctive_condition_words(cond_name: str) -> list[str]:
    return [
        w.lower()
        for w in re.findall(r"[A-Za-z0-9]{3,}", cond_name)
        if len(w) >= 4 and w.lower() not in GENERIC_CONDITION_MODIFIERS
    ]


def _extract_condition_from_paper(clean_topic: str, cat_display_name: str) -> str | None:
    """Extract a paper-native disease/condition phrase from clean_topic when it differs from the sub-domain default."""
    trimmed_topic = re.sub(r"\s+in the (?:era|context|setting|wake|presence) of\s+[A-Za-z0-9\s,\-/+()]+$", "", clean_topic, flags=re.I).strip()
    m_with = re.search(
        r"\b(?:children and young people|children and adolescents|adolescents and adults|older adults|pregnant women|postpartum women|children|adolescents|adults|women|men|patients|individuals|infants|neonates)\s+with\s+"
        r"(?P<cond>[A-Za-z0-9][A-Za-z0-9\s,\-/+()]{6,90})$",
        trimmed_topic,
        flags=re.I,
    )
    if m_with:
        c = _clean_extracted_entity(m_with.group("cond"))
        if 8 <= len(c) <= 90:
            return c
    m = COND_PREP_RE.search(trimmed_topic)
    if m:
        c = _clean_extracted_entity(m.group("cond"))
        if 8 <= len(c) <= 90 and c.lower() not in {"clinical practice", "routine care", "primary care", "the united states", "europe", "china", "japan", "turkey"}:
            return c
    m_of = re.search(
        r"\b(?:genetics|pathogenesis|diagnosis|management|treatment|epidemiology|prognosis|classification|biomarkers|monitoring)\s+of\s+"
        r"([A-Za-z0-9][A-Za-z0-9\s,\-/+()]{6,85})$",
        trimmed_topic,
        flags=re.I,
    )
    if m_of:
        c = _clean_extracted_entity(m_of.group(1))
        if 8 <= len(c) <= 90:
            return c
    return None


def _strip_redundant_population_tail(topic_text: str, cond_name: str) -> str:
    """
    Strip trailing ' in <disease/patients>' from a paper topic when it is embedded inside a
    sentence that already explicitly states 'In <population> with <condition>'.
    """
    trimmed_topic = re.sub(r"\s+in the (?:era|context|setting) of\s+[A-Za-z0-9\s,\-/+()]+$", "", topic_text, flags=re.I).strip()
    m_on_of = re.search(
        r"\s+(?:on|in|among|for)\s+(?:the\s+[a-z\s]{3,25}\s+of\s+)?(?:children|adolescents|adults|women|men|patients|individuals|infants|neonates)[A-Za-z0-9,\-\s/+()]{4,95}$",
        trimmed_topic,
        flags=re.I,
    )
    if m_on_of:
        trimmed = trimmed_topic[: m_on_of.start()].strip()
        if len(trimmed) >= 14:
            return _clean_extracted_entity(trimmed)
    cond_words = set(_distinctive_condition_words(cond_name))
    m = re.search(r"\s+(?:in|among)\s+([A-Za-z0-9,\-\s/+()]{8,85})$", trimmed_topic, flags=re.I)
    if m:
        tail = m.group(1).lower()
        if any(cw in tail for cw in cond_words) or any(k in tail for k in ("patients", "cancer", "disease", "carcinoma", "lymphoma", "leukemia", "amyloidosis", "syndrome", "dissection", "children", "women", "adults")):
            trimmed = trimmed_topic[: m.start()].strip()
            if len(trimmed) >= 14:
                return _clean_extracted_entity(trimmed)
    return _clean_extracted_entity(trimmed_topic)


def select_coherent_outcomes(cat_id: int, raw_title: str, cond_name: str) -> tuple[str, str, str]:
    """
    Return domain-coherent (prim_out, safe_out, pro_out) phrases matched to the category and specific
    disease/sub-specialty so no unrelated sub-domain scales (e.g. endometriosis scales on PCOS, or dental
    scales on stroke rehabilitation) ever appear in a question statement.
    """
    tl = f"{raw_title} {cond_name}".lower()
    if cat_id == 1:
        if any(k in tl for k in ("thromboembol", "vte", "anticoagul", "thrombosis")):
            return (
                "recurrent venous thromboembolism and clinically relevant bleeding",
                "ISTH major bleeding and clinically relevant non-major bleeding",
                "anticoagulation treatment burden and health-related quality of life",
            )
        if any(k in tl for k in ("hemophilia", "haemophilia", "sickle cell", "thalassemia", "aplastic anemia", "hemoglobinuria", "pnh", "thrombocytopenic", "ttp", "itp", "von willebrand")):
            return (
                "annualized bleeding or crisis rate, hemoglobin stabilization, and event-free survival",
                "thromboembolic events, hemolysis or bleeding breakthroughs, and immunogenicity",
                "FACIT-Fatigue score, physical function, and transfusion or infusion burden",
            )
        return (
            "overall survival and progression-free or disease-free survival",
            "Grade >=3 treatment-related and immune-mediated adverse events",
            "EORTC QLQ-C30 health-related quality of life and symptomatic toxicity burden",
        )
    if cat_id == 2:
        if "aortic" in tl or "dissection" in tl or "aneurysm" in tl:
            return (
                "aortic-related mortality, stroke, and reintervention-free survival",
                "spinal cord ischemia, stroke, and major perioperative bleeding",
                "functional independence and health-related quality of life",
            )
        return (
            "cardiovascular death, myocardial infarction, and ischemic stroke",
            "ISTH major bleeding, intracranial hemorrhage, and arrhythmia or conduction disturbances",
            "Kansas City Cardiomyopathy Questionnaire (KCCQ) score and functional independence",
        )
    if cat_id == 3:
        if "epilep" in tl or "seizure" in tl:
            return (
                "sustained seizure freedom and >=50% seizure frequency reduction",
                "neuropsychiatric and cognitive adverse events and treatment discontinuation",
                "Quality of Life in Epilepsy (QOLIE-31) score and cognitive function",
            )
        return (
            "confirmed disability progression and longitudinal neurological function",
            "treatment-related neurotoxicity, serious infection, and infusion or procedural complications",
            "cognitive function, fatigue, and patient-reported neurological quality of life (Neuro-QoL)",
        )
    if cat_id == 4:
        return (
            "sustained symptomatic remission and relapse prevention",
            "suicidal ideation or behavior, treatment-emergent adverse events, and withdrawal symptoms",
            "psychosocial functioning, social participation, and patient-reported mental health quality of life",
        )
    if cat_id == 5:
        return (
            "28-day and 90-day all-cause mortality and microbiological or clinical cure",
            "organ toxicity and treatment-emergent antimicrobial resistance selection",
            "time to symptom resolution, hospital-free days, and treatment completion",
        )
    if cat_id == 6:
        if "sleep" in tl or "apnea" in tl:
            return (
                "apnea-hypopnea index reduction, nocturnal oxygenation, and cardiovascular event rate",
                "treatment intolerance, mask or device complications, and daytime residual sedation",
                "Epworth Sleepiness Scale score, sleep quality, and daytime functional alertness",
            )
        return (
            "annualized severe exacerbation rate and lung function trajectory (FEV1 or FVC)",
            "pneumonia, airway infection, and treatment-related systemic adverse events",
            "St George's Respiratory Questionnaire (SGRQ) score and dyspnea symptom burden",
        )
    if cat_id == 7:
        return (
            "glycemic and cardiometabolic control, major adverse cardiovascular events, and organ preservation",
            "severe hypoglycemia, lean body mass loss, and gastrointestinal or hepatobiliary adverse events",
            "metabolic health-related quality of life, physical function, and treatment satisfaction",
        )
    if cat_id == 8:
        if any(k in tl for k in ("liver", "hepat", "cirrhosis", "masld", "nafld", "nash", "biliary", "cholang")):
            return (
                "liver-related event-free survival, histologic fibrosis regression, and decompensation rate",
                "hepatic decompensation, variceal bleeding, and serious infection",
                "Chronic Liver Disease Questionnaire (CLDQ) score and hospital-free days",
            )
        return (
            "steroid-free clinical and endoscopic or transmural remission",
            "serious opportunistic infection, gastrointestinal bleeding, and bowel perforation",
            "digestive symptom burden, IBD-Disk disability score, and quality of life",
        )
    if cat_id == 9:
        return (
            "sustained eGFR preservation, progression to kidney failure, and renal or patient survival",
            "hyperkalemia, acute kidney injury, volume overload, and serious infection",
            "Kidney Disease Quality of Life (KDQOL-36) score and symptom burden",
        )
    if cat_id == 10:
        return (
            "sustained steroid-free clinical remission and prevention of organ damage accrual",
            "serious opportunistic infection, thromboembolic events, and treatment-related toxicity",
            "HAQ-DI physical function, FACIT-Fatigue score, and cumulative glucocorticoid toxicity",
        )
    if cat_id == 11:
        if any(k in tl for k in ("psoriasis", "dermatitis", "eczema", "hidradenitis", "alopecia", "vitiligo", "skin", "cutaneous", "pemphig", "urticaria", "acne", "melasma", "wound", "ulcer")):
            return (
                "validated skin clearance or lesion resolution and durable disease control",
                "mucocutaneous or systemic infection and treatment-related adverse events",
                "Dermatology Life Quality Index (DLQI), pruritus or pain intensity, and patient satisfaction",
            )
        return (
            "pain intensity reduction, functional joint survival, and revision-free durability",
            "periprosthetic infection or fracture, thromboembolism, and procedural complications",
            "PROMIS pain interference, physical function, and return to independent mobility",
        )
    if cat_id == 12:
        if any(k in tl for k in ("polycystic", "pcos", "ovary", "ovarian", "infertility", "fertility", "ivf", "menopaus", "endometriosis", "fibroid", "adenomyosis", "contracept", "menstrual", "gynecol", "pelvic")):
            return (
                "reproductive, endocrine, and cardiometabolic health outcomes",
                "treatment-related thromboembolic, metabolic, and gynecologic adverse events",
                "validated condition-specific quality of life, symptom severity, and reproductive well-being",
            )
        return (
            "severe maternal morbidity and perinatal survival without severe morbidity",
            "preeclampsia, fetal growth restriction, neonatal complications, and maternal hemorrhage",
            "maternal functional recovery, postpartum depression (EPDS), and patient-reported birth experience",
        )
    if cat_id == 13:
        if any(k in tl for k in ("neonat", "preterm", "infant", "necrotizing", "bronchopulmonary", "hypoxic-ischemic")):
            return (
                "survival without neurodevelopmental impairment and major neonatal morbidity",
                "sepsis, necrotizing enterocolitis, and growth suppression",
                "neurodevelopmental trajectory and family caregiver burden",
            )
        return (
            "pediatric disease control, age-appropriate growth, and long-term organ function",
            "treatment-related toxicity, infection, and developmental or endocrine adverse effects",
            "Pediatric Quality of Life Inventory (PedsQL) score and family caregiver burden",
        )
    if cat_id == 14:
        if any(k in tl for k in ("alzheimer", "dementia", "amyloid", "cognitive", "lewy", "frontotemporal")):
            return (
                "CDR-SB cognitive and functional trajectory and days alive and independent at home",
                "amyloid-related imaging abnormalities (ARIA), intracerebral hemorrhage, and falls",
                "neuropsychiatric symptom burden, Zarit caregiver burden score, and quality of life",
            )
        return (
            "days alive and independent at home, functional preservation, and survival",
            "falls, delirium, polypharmacy-related adverse drug events, and emergency hospitalization",
            "symptom burden, Zarit caregiver burden score, and goal-concordant care",
        )
    if cat_id == 15:
        return (
            "30-day and 90-day all-cause mortality and organ support-free days",
            "major perioperative or critical care complications, organ ischemia, and reintervention",
            "EQ-5D-5L functional recovery, 6-minute walk distance, and return to independent living",
        )
    if cat_id == 16:
        return (
            "diagnostic accuracy, time to definitive diagnosis, and downstream clinical outcome impact",
            "false-positive invasive biopsy cascades, overdiagnosis, and diagnostic delay",
            "diagnostic yield, clinician decision confidence, and patient decisional regret",
        )
    if cat_id == 17:
        return (
            "all-cause and cause-specific mortality and incident disease rate",
            "overdiagnosis, false-positive interventions, and preventive regimen adverse events",
            "health equity gap reduction across socioeconomic strata and quality-adjusted life years",
        )
    if cat_id == 18:
        return (
            "30-day mortality, preventable adverse events, and guideline-concordant care delivery",
            "unintended care delays, missed diagnoses, and clinician workload burden",
            "patient-reported care coordination, equity disparity reduction, and implementation fidelity",
        )
    if cat_id == 19:
        if any(k in tl for k in ("retinal", "macular", "glaucoma", "myopia", "visual", "ophthalm", "ocular", "cornea", "uveitis", "cataract", "optic")):
            return (
                "best-corrected visual acuity (BCVA) and structural retinal or optic nerve preservation",
                "intraocular inflammation, endophthalmitis, and ocular hypertension",
                "National Eye Institute Visual Function Questionnaire (NEI VFQ-25) score and visual independence",
            )
        if any(k in tl for k in ("dental", "periodont", "caries", "implant", "oral", "orthodont", "endodont", "maxillofacial", "tooth", "teeth")):
            return (
                "tooth or implant survival, clinical attachment gain, and oral disease resolution",
                "peri-implantitis, alveolar bone loss, and postoperative infection",
                "Oral Health Impact Profile (OHIP-14) score, masticatory function, and patient comfort",
            )
        if any(k in tl for k in ("hearing", "cochlear", "tinnitus", "vestibular", "speech", "aphasia", "dysphagia", "auditory", "deaf")):
            return (
                "speech-in-noise recognition, communication recovery, and swallowing safety",
                "device failure, aspiration pneumonia, and vestibular dysfunction",
                "Tinnitus Functional Index, communication participation, and WHODAS 2.0 score",
            )
        return (
            "validated motor and functional recovery (Fugl-Meyer, ARAT, or FIM)",
            "musculoskeletal injury, falls, and autonomic or cardiovascular instability",
            "WHODAS 2.0 community participation, independent mobility, and quality of life",
        )
    return (
        "event-free survival, organ-specific disease stabilization, and validated functional response",
        "treatment-related immunogenicity, hepatotoxicity, and severe multisystem adverse events",
        "time to definitive diagnosis, functional independence, and patient or caregiver quality of life",
    )


def _check_subdomain_disease_match(raw_title: str, base_cond_name: str) -> bool:
    """
    Verify whether `raw_title` genuinely addresses `base_cond_name` using whole-word token matching,
    subtype conflict checks (`type a` vs `type b`, `type 1` vs `type 2`), and qualifier checks for umbrella nouns.
    """
    tl = raw_title.lower()
    bcl = base_cond_name.lower()
    if ("type a" in bcl and "type b" in tl) or ("type b" in bcl and "type a" in tl):
        return False
    if ("type 1" in bcl and "type 2" in tl) or ("type 2" in bcl and "type 1" in tl):
        return False

    title_tokens = set(re.findall(r"[a-z0-9]+", tl))
    dist_words = _distinctive_condition_words(base_cond_name)
    if not dist_words:
        return True

    qualifiers = [w for w in dist_words if w not in UMBRELLA_DISEASE_NOUNS]
    umbrellas = [w for w in dist_words if w in UMBRELLA_DISEASE_NOUNS]

    if qualifiers and umbrellas:
        return any(q in title_tokens for q in qualifiers) and any(u in title_tokens for u in umbrellas)
    return any(dw in title_tokens for dw in dist_words)


def extract_paper_pico(
    raw_title: str,
    clean_topic: str,
    qtype: str,
    cond_tuple: tuple,
    int_tuple: tuple,
    outcomes_list: list[dict],
    lower_fn,
    cat_display_name: str = "Clinical medicine",
    cat_id: int = 1,
) -> dict:
    """
    Extract paper-specific PICO elements (`cond_name`, `int_name`, `int_details`, `comp_name`, `pop_desc`,
    `stage_sev`, `prio_sub`, `focus_clean`, `prim_out`, `safe_out`, `pro_out`) from the paper title and
    harmonize with the sub-domain clinical baseline.
    Guarantees zero cross-disease chimeras and zero mismatched outcome scales.
    """
    base_cond_name, onto_ids, base_stage, phenotype, base_pop, age_stages, inc_feat, base_prio_sub = cond_tuple
    _, base_int_name, base_int_details, base_comp_name, horizon, settings, _ = int_tuple

    tl = raw_title.lower()
    matches_subdomain_disease = _check_subdomain_disease_match(raw_title, base_cond_name)

    if matches_subdomain_disease:
        cond_name = base_cond_name
        pop_desc = base_pop
        stage_sev = base_stage
        prio_sub = base_prio_sub
    else:
        # Paper addresses a specific condition in this medical category that differs from `base_cond_name`
        paper_cond = _extract_condition_from_paper(clean_topic, cat_display_name)
        if paper_cond:
            cond_name = paper_cond
            if any(p in paper_cond.lower() for p in ("children", "adolescents", "young people", "women", "adults", "patients", "infants", "neonates", "older adults")):
                pop_desc = paper_cond[0].upper() + paper_cond[1:]
            else:
                pop_desc = f"Patients with {lower_fn(paper_cond)}"
        else:
            cond_name = f"{clean_topic[:80].rsplit(' ', 1)[0]}" if len(clean_topic) > 80 else clean_topic
            pop_desc = f"Patients evaluated for {lower_fn(cond_name)} in {cat_display_name.lower()}"
        stage_sev = "Clinically characterized human cohort"
        prio_sub = ["high-risk clinical subgroups", "underrepresented age and comorbidity strata"]

    extracted_int = None
    extracted_comp = None

    # 1. Check explicit comparison in title ("X versus Y", "X compared with Y")
    m_comp = EXPLICIT_COMP_RE.search(clean_topic)
    if m_comp:
        a = _clean_extracted_entity(m_comp.group("arm_a"))
        b = _clean_extracted_entity(m_comp.group("arm_b"))
        if " of " in a.lower():
            a = _clean_extracted_entity(a.split(" of ")[-1])
        # Reconstruct shared head noun when `a` is a single modifier word (e.g., "hybrid versus total arch replacement")
        a_words = a.split()
        b_words = b.split()
        if len(a_words) == 1 and len(b_words) >= 2:
            a = f"{a} {' '.join(b_words[1:])}"
        if len(a) >= 6 and len(b) >= 6:
            extracted_int = a
            extracted_comp = b

    # 2. Check "Role/Value/Efficacy/Safety/Development of <Focus> in/for <Context>"
    if not extracted_int:
        m_of = OF_PATTERN_RE.match(clean_topic)
        if m_of:
            focus = _clean_extracted_entity(m_of.group("focus"))
            if 8 <= len(focus) <= 95:
                extracted_int = focus

    # 3. Check "<Focus> for/in the treatment/diagnosis/prediction of <Context>"
    if not extracted_int:
        m_for = FOR_ACTION_RE.match(clean_topic)
        if m_for:
            focus = _clean_extracted_entity(m_for.group("focus"))
            if 8 <= len(focus) <= 95:
                extracted_int = focus

    # 4. Check Gerund lead ("Targeting/Predicting/Stratifying <Focus> in <Context>")
    if not extracted_int:
        m_ger = GERUND_RE.match(clean_topic)
        if m_ger:
            focus = _clean_extracted_entity(m_ger.group("focus"))
            if 8 <= len(focus) <= 95:
                extracted_int = focus

    # 5. Check "<Focus> and <Outcome> in <Context>"
    if not extracted_int:
        m_and = AND_IN_RE.match(clean_topic)
        if m_and:
            focus = _clean_extracted_entity(m_and.group("focus"))
            if 8 <= len(focus) <= 85:
                extracted_int = focus

    # 6. Split before " in ", " among ", " for ", " after ", " during "
    if not extracted_int:
        m_prep = re.split(r"\s+(?:in|among|for|after|during|following|across)\s+", clean_topic, maxsplit=1, flags=re.I)
        if len(m_prep) == 2 and 10 <= len(m_prep[0].strip()) <= 85:
            cand_focus = _clean_extracted_entity(m_prep[0])
            if cand_focus.lower() != cond_name.lower() and len(cand_focus) >= 10:
                extracted_int = cand_focus

    # Guard against extracting the disease/condition name itself as `int_name` (e.g. from "Clinical Management of Acute GVHD")
    cond_tokens = set(_distinctive_condition_words(cond_name))
    if extracted_int:
        int_no_parens = re.sub(r"\([^)]*\)", "", extracted_int).strip()
        int_tokens = set(_distinctive_condition_words(int_no_parens))
        if not (int_tokens - cond_tokens) or int_no_parens.lower() in cond_name.lower():
            extracted_int = None

    # Construct final paper-native `int_name` and `int_details`
    if extracted_int:
        int_name = extracted_int
        int_details = f"Clinical and translational evaluation of {lower_fn(extracted_int)} in {lower_fn(cond_name)}"
    elif matches_subdomain_disease:
        int_name = base_int_name
        int_details = base_int_details
        if not extracted_comp:
            extracted_comp = base_comp_name
    else:
        stripped_topic = _strip_redundant_population_tail(clean_topic, cond_name)
        st_no_parens = re.sub(r"\([^)]*\)", "", stripped_topic).strip()
        int_tokens = set(_distinctive_condition_words(st_no_parens))
        if not (int_tokens - cond_tokens) or st_no_parens.lower() in cond_name.lower():
            int_name = f"Guideline-directed clinical management and biomarker stratification in {lower_fn(cond_name)}"
        else:
            int_name = _balance_parens(stripped_topic if len(stripped_topic) <= 90 else stripped_topic[:88].rsplit(" ", 1)[0])
        int_details = f"Evaluation of {lower_fn(int_name)} in {lower_fn(cond_name)}"

    # Concise, non-redundant focus phrase for embedding in sentences that already specify `pop_mid`
    focus_clean = _strip_redundant_population_tail(clean_topic, cond_name)
    fc_no_parens = re.sub(r"\([^)]*\)", "", focus_clean).strip()
    focus_tokens = set(_distinctive_condition_words(fc_no_parens))
    if len(focus_clean) < 14 or not (focus_tokens - cond_tokens) or fc_no_parens.lower() in cond_name.lower():
        focus_clean = int_name

    # Construct paper-native `comp_name` (avoiding the word "protocol" at the end so "protocol for" never occurs)
    if extracted_comp:
        comp_name = extracted_comp
    else:
        cond_short = lower_fn(cond_name)
        qtype_comparators = {
            "etiology": f"Unexposed or baseline reference risk cohort in {cond_short}",
            "mechanism": f"Canonical baseline pathway activity or treatment-sensitive phenotype in {cond_short}",
            "natural_history": f"Standard longitudinal clinical surveillance cohort in {cond_short}",
            "prevention": "Routine risk-factor modification or standard surveillance without targeted prophylaxis",
            "screening": "Symptom-prompted clinical evaluation or current guideline screening schedule",
            "diagnosis": "Conventional clinicopathologic, imaging, or laboratory reference standard",
            "classification": "Conventional clinicopathologic staging and consensus taxonomy",
            "prognosis": f"Standard clinical risk score without {lower_fn(int_name)} stratification",
            "treatment_effectiveness": f"Standard-of-care therapy or active control regimen in {cond_short}",
            "comparative_effectiveness": f"Current guideline-recommended standard regimen in {cond_short}",
            "treatment_strategy": f"Standard fixed-duration or unselected dosing regimen in {cond_short}",
            "safety": "Alternative active comparator or standard dose-monitoring regimen",
            "rehabilitation": "Usual physical and functional care without structured rehabilitation pathway",
            "supportive_palliative": "Usual symptom-directed care without integrated supportive pathway",
            "patient_experience": "Routine clinician-directed care without structured patient-reported decision tool",
            "implementation": "Usual guideline dissemination without multifaceted implementation strategy",
            "health_services": "Conventional specialty or hospital-centered care delivery model",
            "public_health": "Status-quo population health policy without targeted equity intervention",
            "measurement": "Legacy clinician-rated or unharmonized outcome assessment instrument",
            "methodology": "Conventional unadjusted analysis or traditional fixed-sample trial design",
        }
        comp_name = qtype_comparators.get(qtype, f"Standard-of-care management in {cond_short}")

    # Refine population and stage if paper title specifies a distinct clinical cohort modifier
    if "metastatic" in tl and "metastatic" not in stage_sev.lower():
        stage_sev = f"Metastatic or advanced stage ({stage_sev})"
    elif ("relapsed" in tl or "refractory" in tl) and "relapsed" not in stage_sev.lower():
        stage_sev = f"Relapsed or refractory stage ({stage_sev})"
    elif ("early-stage" in tl or "early stage" in tl) and "early" not in stage_sev.lower():
        stage_sev = f"Early-stage disease ({stage_sev})"
    elif ("pediatric" in tl or "children" in tl or "neonat" in tl) and "pediatric" not in pop_desc.lower() and "children" not in pop_desc.lower():
        if pop_desc.lower().startswith("adults "):
            pop_desc = "Children and adolescents " + pop_desc[7:]
        elif pop_desc.lower().startswith("patients "):
            pop_desc = "Pediatric and adolescent patients " + pop_desc[9:]
        else:
            pop_desc = f"Children and adolescents with {lower_fn(cond_name)}"
    elif ("elderly" in tl or "older adult" in tl or "geriatric" in tl) and "older" not in pop_desc.lower():
        if pop_desc.lower().startswith("adults "):
            pop_desc = "Older adults " + pop_desc[7:]
        elif pop_desc.lower().startswith("patients "):
            pop_desc = "Older adults and geriatric patients " + pop_desc[9:]
        else:
            pop_desc = f"Older adults with {lower_fn(cond_name)}"

    prim_out, safe_out, pro_out = select_coherent_outcomes(cat_id, raw_title, cond_name)

    return {
        "cond_name": cond_name,
        "int_name": int_name,
        "int_details": int_details,
        "comp_name": comp_name,
        "pop_desc": pop_desc,
        "stage_sev": stage_sev,
        "prio_sub": prio_sub,
        "focus_clean": focus_clean,
        "prim_out": prim_out,
        "safe_out": safe_out,
        "pro_out": pro_out,
    }


def build_natural_statements(
    prob_num: int,
    qtype: str,
    clean_topic: str,
    focus_clean: str,
    cond_name: str,
    pop_desc: str,
    stage_sev: str,
    int_name: str,
    comp_name: str,
    prim_out: str,
    safe_out: str,
    pro_out: str,
    horizon: str,
    settings: list[str],
    prio_sub: list[str],
    lower_fn,
) -> tuple[str, str, str, str]:
    """
    Return `(title, statement, clean_statement, plain_language_statement)` using 100 natural
    clinical question templates (5 variants per question_type x 20 question_types) with zero
    awkward double-splicing.
    """
    variant = prob_num % 5
    focus_mid = lower_fn(focus_clean)
    cond_mid = lower_fn(cond_name)
    pop_mid = lower_fn(re.sub(r"\s*\([^)]{10,}\)", "", pop_desc).strip())
    int_mid = lower_fn(int_name)
    comp_mid = lower_fn(re.sub(r"\s*\([^)]{10,}\)", "", comp_name).strip())
    prio_mid = ", ".join(lower_fn(p) for p in prio_sub[:2])
    setting_mid = ", ".join(s.replace("_", " ") for s in settings[:2])

    cond_sig_words = _distinctive_condition_words(cond_name)
    q_label = qtype.replace("_", " ").title()
    if any(w in clean_topic.lower() for w in cond_sig_words) or cond_name.lower() in clean_topic.lower():
        title = f"{clean_topic} — Open {q_label} Question"
    else:
        title = f"{clean_topic} in {cond_name} ({q_label})"

    clean_statement = (
        f"In {pop_mid}, how does {int_mid} compare with {comp_mid} regarding {prim_out} over {horizon}?"
    )

    templates = {
        "comparative_effectiveness": [
            f"In {pop_mid}, does {focus_mid} improve {prim_out} and reduce {safe_out} over {horizon} compared with {comp_mid}?",
            f"Among {pop_mid}, what is the head-to-head comparative effectiveness of {focus_mid} versus {comp_mid} for achieving superior {prim_out} over {horizon}?",
            f"For {pop_mid} managed in {setting_mid} settings, does {focus_mid} provide a net clinical advantage over {comp_mid} on {prim_out} and {safe_out} through {horizon}?",
            f"When treating {pop_mid} (including {prio_mid}), is {focus_mid} superior or non-inferior to {comp_mid} with respect to {prim_out} at {horizon}?",
            f"Across diverse clinical cohorts of {pop_mid}, how does {focus_mid} compare against {comp_mid} in balancing {prim_out} against {safe_out} over {horizon}?",
        ],
        "treatment_effectiveness": [
            f"Among {pop_mid} ({lower_fn(stage_sev)}), what is the confirmatory clinical efficacy of {focus_mid} compared with {comp_mid} on {prim_out} over {horizon}?",
            f"In {pop_mid}, does therapeutic intervention with {focus_mid} produce durable improvements in {prim_out} over {horizon} relative to {comp_mid}?",
            f"For {pop_mid}, can {focus_mid} significantly improve {prim_out} without unacceptable {safe_out} over {horizon} compared with {comp_mid}?",
            f"What is the magnitude and durability of treatment benefit from {focus_mid} versus {comp_mid} on {prim_out} over {horizon} in {pop_mid}?",
            f"In randomized evaluation of {pop_mid}, does {focus_mid} achieve clinically meaningful gains in {prim_out} and {pro_out} over {horizon} compared with {comp_mid}?",
        ],
        "treatment_strategy": [
            f"For {pop_mid} in {setting_mid} settings, what is the optimal sequencing, dosing threshold, or treatment duration of {focus_mid} versus {comp_mid} over {horizon}?",
            f"In {pop_mid}, does a biomarker- or response-adapted strategy for {focus_mid} outperform {comp_mid} on {prim_out} and {safe_out} over {horizon}?",
            f"Among {pop_mid}, when can therapy be safely de-escalated, switched, or intensified using {focus_mid} compared with {comp_mid} over a {horizon} horizon?",
            f"What is the optimal clinical algorithm for initiating and sequencing {focus_mid} relative to {comp_mid} to maximize {prim_out} over {horizon} in {pop_mid}?",
            f"In {pop_mid}, does dynamic treatment adaptation guided by {focus_mid} improve {prim_out} over {horizon} compared with {comp_mid}?",
        ],
        "diagnosis": [
            f"In {pop_mid} presenting for clinical evaluation, what is the diagnostic accuracy and clinical utility of {focus_mid} compared with {comp_mid} for improving {prim_out} over {horizon}?",
            f"Among {pop_mid}, does integrating {focus_mid} into the diagnostic pathway outperform {comp_mid} in sensitivity, specificity, and downstream {prim_out} over {horizon}?",
            f"For {pop_mid} in {setting_mid} care, can {focus_mid} reduce diagnostic delay and misclassification compared with {comp_mid} while improving {prim_out} over {horizon}?",
            f"What are the externally validated diagnostic performance characteristics of {focus_mid} versus {comp_mid} in {pop_mid}, and does testing improve {prim_out} over {horizon}?",
            f"In {pop_mid}, does diagnostic triage with {focus_mid} provide superior clinical net benefit over {comp_mid} across {horizon}?",
        ],
        "screening": [
            f"In asymptomatic or at-risk {pop_mid}, does structured screening via {focus_mid} compared with {comp_mid} improve early detection and {prim_out} without excess {safe_out} over {horizon}?",
            f"Among {pop_mid} (including {prio_mid}), what is the net balance of benefits, false-positive burden, and overdiagnosis when screening with {focus_mid} versus {comp_mid} over {horizon}?",
            f"For risk-stratified {pop_mid}, does longitudinal surveillance using {focus_mid} reduce late-stage presentation and improve {prim_out} over {horizon} compared with {comp_mid}?",
            f"What screening interval and positivity threshold for {focus_mid} optimize {prim_out} and minimize {safe_out} compared with {comp_mid} in {pop_mid} over {horizon}?",
            f"In population and clinic-based cohorts of {pop_mid}, does early detection through {focus_mid} translate into improved {prim_out} over {horizon} relative to {comp_mid}?",
        ],
        "classification": [
            f"In {pop_mid}, does biological endotyping or phenotypic classification via {focus_mid} outperform {comp_mid} for predicting {prim_out} and guiding therapy over {horizon}?",
            f"Among {pop_mid}, can a reproducible subphenotype taxonomy based on {focus_mid} resolve clinical heterogeneity and improve {prim_out} stratification over {horizon} versus {comp_mid}?",
            f"For {pop_mid}, do disease subtypes defined by {focus_mid} exhibit distinct treatment responses and {prim_out} trajectories over {horizon} compared with {comp_mid}?",
            f"Does integrating multi-modal classification from {focus_mid} refine risk categories beyond {comp_mid} for {prim_out} over {horizon} in {pop_mid}?",
            f"In {pop_mid}, how accurately do diagnostic and molecular criteria derived from {focus_mid} partition patients into actionable strata for {prim_out} over {horizon} versus {comp_mid}?",
        ],
        "prognosis": [
            f"Among {pop_mid}, what is the externally validated prognostic discrimination, calibration, and decision utility of {focus_mid} versus {comp_mid} for stratifying {prim_out} over {horizon}?",
            f"In {pop_mid}, does prognostic modeling incorporating {focus_mid} provide incremental predictive value over {comp_mid} for {prim_out} through {horizon}?",
            f"Across independent cohorts of {pop_mid} (including {prio_mid}), how reliably does {focus_mid} predict long-term {prim_out} and {safe_out} over {horizon} compared with {comp_mid}?",
            f"For {pop_mid}, can baseline and serial assessment of {focus_mid} accurately stratify individual risk of {prim_out} over {horizon} relative to {comp_mid}?",
            f"What is the transportability and clinical net benefit of risk prediction using {focus_mid} compared with {comp_mid} for {prim_out} over {horizon} in {pop_mid}?",
        ],
        "natural_history": [
            f"Across longitudinal cohorts of {pop_mid}, what is the natural trajectory, progression rate, and determinant profile of {prim_out} over {horizon} in relation to {focus_mid} versus {comp_mid}?",
            f"In {pop_mid}, how does the long-term clinical course of {prim_out} evolve over {horizon} when stratified by {focus_mid} compared with {comp_mid}?",
            f"Among {pop_mid}, what are the transition probabilities between clinical states and cumulative incidence of {prim_out} over {horizon} associated with {focus_mid}?",
            f"In unselected prospective follow-up of {pop_mid}, what factors modify longitudinal progression to {prim_out} over {horizon} under {focus_mid} versus {comp_mid}?",
            f"How do baseline phenotypic features and {focus_mid} shape the multi-year natural history of {prim_out} over {horizon} in {pop_mid}?",
        ],
        "etiology": [
            f"In {pop_mid}, what is the causal contribution of {focus_mid}—and its interaction with host susceptibility—to disease development and {prim_out} over {horizon} compared with {comp_mid}?",
            f"Among {pop_mid}, does exposure or predisposition characterized by {focus_mid} independently increase disease incidence and {prim_out} over {horizon} after accounting for confounding?",
            f"Through what causal pathways and dose-response relationships does {focus_mid} drive disease onset and {prim_out} over {horizon} in {pop_mid} relative to {comp_mid}?",
            f"In longitudinal etiologic studies of {pop_mid}, what fraction of disease risk and {prim_out} over {horizon} is attributable to {focus_mid} versus {comp_mid}?",
            f"Using triangulated human causal inference in {pop_mid}, is {focus_mid} a modifiable causal driver of {prim_out} over {horizon}?",
        ],
        "mechanism": [
            f"In human tissues and clinical cohorts of {pop_mid}, what cellular and molecular pathways link {focus_mid} to {prim_out} over {horizon}, and is this axis causally rate-limiting?",
            f"Among {pop_mid}, how does mechanistic perturbation of {focus_mid} alter downstream pathobiology and clinical {prim_out} over {horizon} compared with {comp_mid}?",
            f"In {pop_mid}, what are the primary immunologic, metabolic, or signaling drivers of treatment resistance and disease progression mediated by {focus_mid} over {horizon}?",
            f"Does target engagement of the biological pathway underlying {focus_mid} reverse pathological remodeling and improve {prim_out} over {horizon} in {pop_mid}?",
            f"In translational human studies of {pop_mid}, how do host-microenvironment or genetic interactions involving {focus_mid} govern {prim_out} over {horizon}?",
        ],
        "prevention": [
            f"In at-risk {pop_mid}, does primary or secondary prevention with {focus_mid} compared with {comp_mid} reduce disease incidence and improve {prim_out} over {horizon}?",
            f"Among {pop_mid} (including {prio_mid}), what is the preventive efficacy and number needed to treat of {focus_mid} versus {comp_mid} for averting {prim_out} over {horizon}?",
            f"For high-risk {pop_mid}, does targeted prophylaxis or risk reduction via {focus_mid} durably lower disease incidence and {prim_out} over {horizon} without excess {safe_out}?",
            f"In {pop_mid}, what is the optimal timing and risk threshold for initiating preventive {focus_mid} compared with {comp_mid} to prevent {prim_out} over {horizon}?",
            f"Across community and clinical cohorts of {pop_mid}, does sustained preventive intervention with {focus_mid} reduce long-term {prim_out} over {horizon} relative to {comp_mid}?",
        ],
        "safety": [
            f"Among {pop_mid} exposed to {focus_mid} versus {comp_mid}, what is the comparative incidence, severity, and reversibility of {safe_out} relative to {prim_out} benefit over {horizon}?",
            f"In {pop_mid} (especially {prio_mid}), what patient-level risk factors and monitoring thresholds predict severe {safe_out} during {focus_mid} over {horizon}?",
            f"For {pop_mid} receiving treatment in {setting_mid} settings, how does the long-term safety and pharmacovigilance profile of {focus_mid} compare with {comp_mid} over {horizon}?",
            f"What is the causal risk-benefit trade-off between gains in {prim_out} and cumulative {safe_out} over {horizon} when using {focus_mid} versus {comp_mid} in {pop_mid}?",
            f"In {pop_mid}, what mitigation or dose-modification strategy best prevents treatment-limiting {safe_out} from {focus_mid} while preserving {prim_out} over {horizon}?",
        ],
        "rehabilitation": [
            f"In {pop_mid}, does structured rehabilitation incorporating {focus_mid} improve functional recovery and {prim_out} over {horizon} compared with {comp_mid}?",
            f"Among {pop_mid}, what intensity, timing, and modality of {focus_mid} maximize long-term functional independence and {pro_out} over {horizon} relative to {comp_mid}?",
            f"For {pop_mid} in {setting_mid} rehabilitation pathways, does individualized therapy with {focus_mid} produce durable gains in {prim_out} over {horizon} versus {comp_mid}?",
            f"In {pop_mid}, how does combining neuroplastic or physical conditioning via {focus_mid} compare against {comp_mid} in restoring mobility, function, and {prim_out} over {horizon}?",
            f"Across heterogeneous recovery profiles in {pop_mid}, which subgroups derive clinically meaningful functional benefit from {focus_mid} over {horizon} compared with {comp_mid}?",
        ],
        "supportive_palliative": [
            f"For {pop_mid} experiencing symptom burden, does integrated supportive or palliative care via {focus_mid} improve {pro_out} and {prim_out} over {horizon} compared with {comp_mid}?",
            f"In {pop_mid}, what is the comparative effectiveness of early, structured {focus_mid} versus {comp_mid} for relieving refractory symptoms and improving {pro_out} over {horizon}?",
            f"Among {pop_mid} and their caregivers, does a multidisciplinary supportive pathway centered on {focus_mid} reduce acute care utilization and improve {pro_out} over {horizon}?",
            f"In managing complex symptom clusters in {pop_mid}, how does {focus_mid} compare against {comp_mid} with respect to symptom control, {safe_out}, and {pro_out} over {horizon}?",
            f"For {pop_mid} across {setting_mid} settings, does goal-concordant supportive care integrating {focus_mid} improve {pro_out} and {prim_out} over {horizon} relative to {comp_mid}?",
        ],
        "patient_experience": [
            f"Among {pop_mid}, how does care delivery incorporating {focus_mid} compare with {comp_mid} in improving patient-reported {pro_out} and decision quality over {horizon}?",
            f"In {pop_mid} (including {prio_mid}), what treatment attributes, lived-experience priorities, and trade-offs between {prim_out} and {safe_out} govern preference for {focus_mid} versus {comp_mid}?",
            f"For {pop_mid}, does structured shared decision-making and symptom monitoring around {focus_mid} reduce treatment regret and improve {pro_out} over {horizon} compared with {comp_mid}?",
            f"Across diverse cultural and socioeconomic groups of {pop_mid}, how does {focus_mid} impact treatment burden, quality of life, and {pro_out} over {horizon} relative to {comp_mid}?",
            f"In {pop_mid}, do patient-reported outcomes ({pro_out}) over {horizon} favor {focus_mid} or {comp_mid} when accounting for daily treatment burden and {safe_out}?",
        ],
        "implementation": [
            f"Across real-world {setting_mid} settings caring for {pop_mid}, which implementation strategies for {focus_mid} maximize guideline fidelity, equity across {prio_mid}, and {prim_out} over {horizon}?",
            f"In routine clinical practice for {pop_mid}, does a multifaceted implementation bundle for {focus_mid} outperform {comp_mid} in adoption, sustainment, and {prim_out} over {horizon}?",
            f"What health-system, clinician, and patient-level barriers limit real-world uptake of {focus_mid} in {pop_mid}, and do targeted implementation interventions improve {prim_out} over {horizon}?",
            f"Among {setting_mid} practices managing {pop_mid}, how does structured clinical pathway integration of {focus_mid} compare with {comp_mid} for achieving equitable {prim_out} over {horizon}?",
            f"In scaling evidence-based care for {pop_mid}, does audit-feedback and decision support for {focus_mid} close care gaps across {prio_mid} and improve {prim_out} over {horizon}?",
        ],
        "health_services": [
            f"In health systems managing {pop_mid}, how does organizing care delivery around {focus_mid} compare with {comp_mid} on {prim_out}, resource utilization, and care coordination over {horizon}?",
            f"For {pop_mid} treated across {setting_mid} settings, does a redesigned service model incorporating {focus_mid} reduce avoidable hospitalizations and improve {prim_out} over {horizon} versus {comp_mid}?",
            f"Among {pop_mid} (especially {prio_mid}), what is the cost-effectiveness, capacity impact, and clinical effect on {prim_out} of deploying {focus_mid} compared with {comp_mid} over {horizon}?",
            f"Does multidisciplinary team triage and longitudinal care navigation for {focus_mid} improve {prim_out} and reduce {safe_out} over {horizon} compared with {comp_mid} in {pop_mid}?",
            f"Across regional healthcare networks serving {pop_mid}, how does decentralized or integrated delivery of {focus_mid} compare against {comp_mid} for {prim_out} over {horizon}?",
        ],
        "public_health": [
            f"At the population level among {pop_mid} (including {prio_mid}), does scaling {focus_mid} compared with {comp_mid} reduce health disparities and improve population {prim_out} over {horizon}?",
            f"Across high-burden communities of {pop_mid}, what is the population-level effectiveness and equity impact of public health interventions based on {focus_mid} versus {comp_mid} over {horizon}?",
            f"In population surveillance of {pop_mid}, how do social determinants and policy implementation of {focus_mid} modify {prim_out} and disease burden over {horizon} compared with {comp_mid}?",
            f"For public health programs serving {pop_mid}, does community-wide deployment of {focus_mid} achieve sustainable improvements in {prim_out} over {horizon} relative to {comp_mid}?",
            f"Among underserved subpopulations ({prio_mid}) within {pop_mid}, can structural prevention and care linkage via {focus_mid} close outcome gaps in {prim_out} over {horizon}?",
        ],
        "measurement": [
            f"In clinical research and care for {pop_mid}, what is the construct validity, responsiveness, and minimal clinically important difference of measurement via {focus_mid} for {prim_out} over {horizon}?",
            f"Among {pop_mid}, is {focus_mid} a validated surrogate or core outcome measure capable of reliably predicting {prim_out} over {horizon} compared with {comp_mid}?",
            f"Across multi-center studies of {pop_mid}, how can assay or instrument standardization for {focus_mid} eliminate inter-laboratory variability and improve {prim_out} assessment over {horizon}?",
            f"For evaluating interventions in {pop_mid}, does quantitative longitudinal tracking of {focus_mid} capture clinically meaningful change in {prim_out} and {pro_out} over {horizon} better than {comp_mid}?",
            f"In {pop_mid} (including {prio_mid}), does outcome measurement via {focus_mid} demonstrate cross-population measurement invariance and prognostic validity for {prim_out} over {horizon}?",
        ],
        "methodology": [
            f"In clinical studies of {pop_mid} addressing {focus_mid}, which study design and causal-inference framework best resolves confounding, time-zero bias, and heterogeneity when comparing {int_mid} against {comp_mid} over {horizon}?",
            f"For evaluating {focus_mid} versus {comp_mid} in {pop_mid}, how should estimands, intercurrent events, and competing risks be specified to yield unbiased estimates of {prim_out} over {horizon}?",
            f"In synthesizing heterogeneous evidence on {focus_mid} in {pop_mid}, can individual participant data meta-analysis or target-trial emulation reconcile conflicting findings on {prim_out} over {horizon}?",
            f"What adaptive platform trial architecture or covariate-adjusted randomization scheme optimizes statistical power across {prio_mid} when testing {focus_mid} versus {comp_mid} over {horizon}?",
            f"When validating predictive or causal claims regarding {focus_mid} in {pop_mid}, what external transportability and bias-quantification standards are required to establish {prim_out} over {horizon}?",
        ],
    }

    statement = templates[qtype][variant]

    plain_variants = [
        f"For people with {cond_mid}, how does {int_mid} compare with {comp_mid} for improving {prim_out} and minimizing {safe_out} over {horizon}?",
        f"In patients affected by {cond_mid}, what is the clearest medical evidence on whether {int_mid} works better than {comp_mid} over {horizon}?",
        f"Can {int_mid} safely improve {prim_out} and quality of life ({pro_out}) over {horizon} compared with {comp_mid} for people with {cond_mid}?",
        f"Among individuals with {cond_mid} (including {prio_mid}), does {int_mid} offer meaningful long-term benefits over {comp_mid} across {horizon}?",
        f"What are the real-world benefits and risks of {int_mid} versus {comp_mid} over {horizon} for patients managing {cond_mid}?",
    ]
    plain_stmt = plain_variants[variant]

    return title, statement, clean_statement, plain_stmt