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  VerticalAlign, PageNumber, Header, Footer, LevelFormat,
  UnderlineType, PageBreak
} = require('docx');
const fs = require('fs');

// ─── Helpers ────────────────────────────────────────────────────────────────

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// ─── Table helpers ─────────────────────────────────────────────────────────

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// ─── Cover Page ────────────────────────────────────────────────────────────

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      spacing: { before: 0, after: 200 },
      children: [new TextRun({
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        text: "Comparative Evaluation of Antimicrobial Therapy, Microbial\nEtiology, and Clinical Outcomes in Community-Acquired versus\nHospital-Acquired Pneumonia: A Retrospective Study",
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}

// ─── Synopsis Table ────────────────────────────────────────────────────────

function synopsisSection() {
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    heading1("1. STUDY SYNOPSIS"),
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        { text: "Item", header: true, width: 2500 },
        { text: "Details", header: true, width: 6860 }
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      { cells: [{ text: "Study Title", shade: true }, { text: "Comparative Evaluation of Antimicrobial Therapy, Microbial Etiology, and Clinical Outcomes in Community-Acquired versus Hospital-Acquired Pneumonia: A Retrospective Study" }]},
      { cells: [{ text: "Study Design", shade: true }, { text: "Retrospective observational comparative study" }]},
      { cells: [{ text: "Study Setting", shade: true }, { text: "[Tertiary care teaching hospital], [City]" }]},
      { cells: [{ text: "Study Duration", shade: true }, { text: "2 years (data collection: [Month Year] to [Month Year])" }]},
      { cells: [{ text: "Study Population", shade: true }, { text: "Adult patients (age >= 18 years) admitted with a confirmed diagnosis of CAP or HAP" }]},
      { cells: [{ text: "Sample Size", shade: true }, { text: "Minimum 100 per group (n = 200 total); calculated using OpenEpi formula" }]},
      { cells: [{ text: "Primary Objective", shade: true }, { text: "To compare antimicrobial therapy patterns and clinical outcomes between CAP and HAP patients" }]},
      { cells: [{ text: "Secondary Objective", shade: true }, { text: "To identify microbial etiology, resistance patterns, and guideline adherence in both groups" }]},
      { cells: [{ text: "Primary Outcome", shade: true }, { text: "Clinical cure rate, in-hospital mortality, length of stay (LOS)" }]},
      { cells: [{ text: "Data Collection", shade: true }, { text: "Medical records, culture reports, prescription charts, lab data" }]},
      { cells: [{ text: "Statistical Analysis", shade: true }, { text: "SPSS v26.0; chi-square, t-test/Mann-Whitney U, multivariate logistic regression" }]},
      { cells: [{ text: "Ethical Clearance", shade: true }, { text: "Will be obtained from Institutional Ethics Committee prior to data collection" }]},
    ]),
    emptyLine(), pageBreak()
  ];
}

// ─── Background ────────────────────────────────────────────────────────────

function backgroundSection() {
  return [
    heading1("2. INTRODUCTION AND BACKGROUND"),
    heading2("2.1 Overview of Pneumonia"),
    body("Pneumonia is one of the most common infectious diseases globally and remains a leading cause of morbidity and mortality, particularly in hospitalized patients. It is broadly classified into Community-Acquired Pneumonia (CAP) and Hospital-Acquired Pneumonia (HAP), each carrying distinct epidemiological, microbiological, and therapeutic profiles."),
    emptyLine(),
    heading2("2.2 Community-Acquired Pneumonia (CAP)"),
    body("CAP is defined as an acute infection of the pulmonary parenchyma that is acquired outside of a hospital or long-term care facility. Common causative organisms include Streptococcus pneumoniae, Haemophilus influenzae, Mycoplasma pneumoniae, Legionella pneumophila, and respiratory viruses. The IDSA/ATS 2019 guidelines recommend beta-lactam plus macrolide combination therapy or a respiratory fluoroquinolone for hospitalized non-ICU patients, and more aggressive regimens for severe or ICU-level CAP."),
    emptyLine(),
    heading2("2.3 Hospital-Acquired Pneumonia (HAP)"),
    body("HAP is defined as pneumonia occurring 48 hours or more after hospital admission, not incubating at the time of admission. It is predominantly caused by gram-negative bacilli such as Pseudomonas aeruginosa, Klebsiella pneumoniae, Acinetobacter baumannii, and gram-positive organisms like MRSA. HAP carries a significantly higher mortality (20-50%) and requires broad-spectrum empiric therapy guided by local antibiograms and risk factors for multidrug-resistant (MDR) organisms."),
    emptyLine(),
    heading2("2.4 Rationale for the Study"),
    body("Despite well-established international guidelines (IDSA/ATS for CAP; IDSA 2016 for HAP/VAP), real-world adherence to these guidelines varies widely. Local microbiological patterns, antibiotic resistance trends, and clinical outcomes differ significantly between institutions and geographic regions. Comparative data on CAP vs. HAP antimicrobial prescribing, microbial etiology, and outcomes from tertiary care settings are limited, and generating such institutional evidence is vital for local stewardship interventions."),
    body("A 2026 multicenter retrospective cohort study (Nasr R et al., Antibiotics) highlighted significant gaps in empirical CAP management compliance with national and international guidelines in hospital settings, reinforcing the need for local-level studies. Furthermore, a 2026 systematic review (Ablakimova N et al., J Hosp Infect) demonstrated that targeted AMS interventions in HAP significantly reduce mortality and antibiotic exposure."),
    emptyLine(), pageBreak()
  ];
}

// ─── Objectives ────────────────────────────────────────────────────────────

function objectivesSection() {
  return [
    heading1("3. OBJECTIVES"),
    heading2("3.1 Primary Objectives"),
    bulletItem("To compare the antimicrobial therapy patterns (drug selection, duration, route, de-escalation) in CAP vs. HAP patients."),
    bulletItem("To compare clinical outcomes (clinical cure, in-hospital mortality, length of stay) between CAP and HAP groups."),
    emptyLine(),
    heading2("3.2 Secondary Objectives"),
    bulletItem("To identify the microbial etiology and antimicrobial susceptibility patterns (antibiogram) in culture-positive CAP and HAP cases."),
    bulletItem("To evaluate adherence to IDSA/ATS guidelines for CAP and IDSA 2016 guidelines for HAP in the study population."),
    bulletItem("To identify risk factors associated with poor clinical outcomes (mortality, prolonged LOS, treatment failure) in both groups."),
    bulletItem("To assess the rate and predictors of 30-day readmission following discharge."),
    emptyLine(), pageBreak()
  ];
}

// ─── Methodology ───────────────────────────────────────────────────────────

function methodologySection() {
  return [
    heading1("4. METHODOLOGY"),
    heading2("4.1 Study Design"),
    body("Retrospective observational comparative study."),
    emptyLine(),
    heading2("4.2 Study Setting"),
    body("The study will be conducted at [Name of Tertiary Care Teaching Hospital], [City]. This is a [X]-bed tertiary care center with dedicated medical, pulmonology, and ICU wards. Patient records, microbiology laboratory data, and pharmacy prescription records will be accessed through the hospital information system (HIS)."),
    emptyLine(),
    heading2("4.3 Study Duration"),
    body("Total study duration: 2 years."),
    bulletItem("Retrospective data collection period: [Month Year] to [Month Year] (e.g., January 2023 - December 2024)."),
    bulletItem("Data extraction, analysis, and manuscript preparation: [Month Year] to [Month Year]."),
    emptyLine(),
    heading2("4.4 Study Population"),
    heading2("4.4.1 Inclusion Criteria"),
    bulletItem("Adult patients aged >= 18 years."),
    bulletItem("Admitted to the hospital with a confirmed diagnosis of CAP or HAP based on clinical, radiological, and/or microbiological criteria."),
    bulletItem("Patients who received at least one dose of antimicrobial therapy during hospitalization."),
    bulletItem("Patients with a minimum hospital stay of 48 hours."),
    emptyLine(),
    heading2("4.4.2 Exclusion Criteria"),
    bulletItem("Patients aged < 18 years."),
    bulletItem("Ventilator-associated pneumonia (VAP) - will be analyzed separately if sample permits."),
    bulletItem("Immunocompromised patients (HIV/AIDS, organ transplant recipients, those on chronic immunosuppressive therapy)."),
    bulletItem("Patients with aspiration pneumonia or viral pneumonia (COVID-19) as the primary diagnosis."),
    bulletItem("Incomplete medical records (missing culture data or antimicrobial prescription details)."),
    bulletItem("Patients transferred from another hospital (for HAP classification purposes)."),
    emptyLine(),
    heading2("4.5 Sample Size Calculation"),
    body("The sample size will be calculated using the OpenEpi Sample Size Calculator for two proportions based on the following assumptions:"),
    bulletItem("Expected mortality in CAP: 8-10% (based on published literature)."),
    bulletItem("Expected mortality in HAP: 25-30%."),
    bulletItem("Alpha (alpha): 0.05 (two-tailed); Power (1-beta): 80%."),
    bulletItem("Estimated minimum sample size: ~100 patients per group (n = 200 total)."),
    body("A 10-15% increase will be added to account for incomplete records, yielding a target of 110-120 patients per group."),
    emptyLine(),
    heading2("4.6 Data Collection"),
    heading2("4.6.1 Data Source"),
    body("Data will be collected from:"),
    bulletItem("In-patient medical case records (paper or electronic)."),
    bulletItem("Microbiology laboratory reports (culture and sensitivity)."),
    bulletItem("Pharmacy prescription and medication administration records."),
    bulletItem("Radiology reports (chest X-ray / CT chest)."),
    bulletItem("Discharge summaries and mortality registers."),
    emptyLine(),
    heading2("4.6.2 Data Collection Tool"),
    body("A structured, pre-validated Case Record Form (CRF) will be used to extract data. The CRF will be reviewed by at least two investigators before use. The following domains will be captured:"),
    emptyLine(),
    makeTable([
      { isHeaderRow: true, cells: [
        { text: "Domain", header: true, width: 2200 },
        { text: "Variables Collected", header: true, width: 7160 }
      ]},
      { cells: [{ text: "Demographic Data", shade: true }, { text: "Age, gender, weight, BMI, ward/ICU admission, smoking history, alcohol use" }]},
      { cells: [{ text: "Clinical Parameters", shade: true }, { text: "Diagnosis (CAP/HAP), disease severity (PSI/PORT score for CAP; CPIS score for HAP), comorbidities (COPD, DM, CKD, CHF, malignancy), vital signs at admission, oxygen saturation" }]},
      { cells: [{ text: "Laboratory Data", shade: true }, { text: "CBC, CRP, procalcitonin, serum creatinine, liver function tests, blood culture, sputum culture, BAL culture (if available), urine legionella antigen" }]},
      { cells: [{ text: "Microbiological Data", shade: true }, { text: "Culture specimen type, pathogen identified, antimicrobial susceptibility (MIC/zone diameter), MDR status" }]},
      { cells: [{ text: "Antimicrobial Therapy", shade: true }, { text: "Empiric regimen (drug name, dose, route, frequency, duration), de-escalation (yes/no), IV-to-oral switch, total antibiotic days (DOT), time to first antibiotic dose" }]},
      { cells: [{ text: "Guideline Adherence", shade: true }, { text: "Concordance with IDSA/ATS guidelines for CAP; IDSA 2016 for HAP (yes/no/partial)" }]},
      { cells: [{ text: "Clinical Outcomes", shade: true }, { text: "Clinical cure, treatment failure, in-hospital mortality, ICU transfer, LOS, 30-day readmission" }]},
    ]),
    emptyLine(), pageBreak()
  ];
}

// ─── Definitions ───────────────────────────────────────────────────────────

function definitionsSection() {
  return [
    heading1("5. OPERATIONAL DEFINITIONS"),
    emptyLine(),
    makeTable([
      { isHeaderRow: true, cells: [
        { text: "Term", header: true, width: 2500 },
        { text: "Operational Definition", header: true, width: 6860 }
      ]},
      { cells: [{ text: "CAP", shade: true }, { text: "Acute lower respiratory tract infection acquired outside of a hospital, manifested by fever, cough, purulent sputum, and new infiltrate on chest radiograph within 48 hours of admission." }]},
      { cells: [{ text: "HAP", shade: true }, { text: "Pneumonia occurring >= 48 hours after hospital admission, not incubating at the time of admission, with new or worsening infiltrate on CXR/CT with clinical signs of infection." }]},
      { cells: [{ text: "Clinical Cure", shade: true }, { text: "Resolution of fever, improved respiratory parameters, radiological improvement, and no need for antibiotic change at the end of therapy." }]},
      { cells: [{ text: "Treatment Failure", shade: true }, { text: "Persistence or worsening of clinical, laboratory, or radiological signs after 72 hours of appropriate antibiotic therapy, requiring antibiotic change or escalation." }]},
      { cells: [{ text: "MDR Organism", shade: true }, { text: "Non-susceptibility to at least one agent in >= 3 antimicrobial categories, as per ECDC/CDC 2012 consensus definition." }]},
      { cells: [{ text: "Guideline Concordance", shade: true }, { text: "Selection of antimicrobial regimen consistent with IDSA/ATS 2019 guidelines (CAP) or IDSA 2016 HAP/VAP guidelines based on severity and risk factors." }]},
      { cells: [{ text: "De-escalation", shade: true }, { text: "Change from broad-spectrum empiric therapy to a narrower-spectrum agent based on culture results or clinical improvement." }]},
      { cells: [{ text: "LOS", shade: true }, { text: "Total number of days from hospital admission to discharge or death." }]},
    ]),
    emptyLine(), pageBreak()
  ];
}

// ─── Statistical Analysis ──────────────────────────────────────────────────

function statisticsSection() {
  return [
    heading1("6. STATISTICAL ANALYSIS"),
    body("All data will be entered and analyzed using IBM SPSS Statistics version 26.0 (or equivalent). Statistical significance will be set at p < 0.05."),
    emptyLine(),
    heading2("6.1 Descriptive Statistics"),
    bulletItem("Continuous variables: Mean +/- SD (normally distributed) or Median with IQR (non-normal distribution)."),
    bulletItem("Categorical variables: Frequency and percentage."),
    emptyLine(),
    heading2("6.2 Comparative Analysis"),
    bulletItem("For continuous variables between CAP and HAP groups: Independent samples t-test (normal) or Mann-Whitney U test (non-normal)."),
    bulletItem("For categorical variables: Chi-square test or Fisher's exact test (for cell counts < 5)."),
    emptyLine(),
    heading2("6.3 Multivariate Analysis"),
    bulletItem("Binary logistic regression will be performed to identify independent predictors of in-hospital mortality and treatment failure after adjusting for confounders (age, comorbidities, disease severity score, MDR organism, guideline adherence)."),
    bulletItem("Results will be expressed as adjusted Odds Ratio (aOR) with 95% Confidence Intervals (CI)."),
    emptyLine(),
    heading2("6.4 Survival Analysis"),
    bulletItem("Kaplan-Meier survival curves will be plotted to compare time-to-clinical-cure and time-to-mortality between CAP and HAP groups."),
    bulletItem("Log-rank test will be used to assess statistical significance between survival curves."),
    emptyLine(), pageBreak()
  ];
}

// ─── Outcomes ─────────────────────────────────────────────────────────────

function outcomesSection() {
  return [
    heading1("7. OUTCOME MEASURES"),
    heading2("7.1 Primary Outcomes"),
    bulletItem("Clinical cure rate (%) in CAP vs. HAP."),
    bulletItem("In-hospital mortality rate (%) in CAP vs. HAP."),
    bulletItem("Mean / median length of hospital stay (days) in CAP vs. HAP."),
    emptyLine(),
    heading2("7.2 Secondary Outcomes"),
    bulletItem("Microbiological profile and prevalence of MDR organisms in each group."),
    bulletItem("Rate of guideline-concordant empiric antibiotic prescribing in each group."),
    bulletItem("Rate of antibiotic de-escalation following culture results."),
    bulletItem("Total days of antibiotic therapy (DOT per 1000 patient-days)."),
    bulletItem("Time to first antibiotic dose from diagnosis."),
    bulletItem("30-day readmission rate."),
    bulletItem("ICU transfer rate and ICU LOS."),
    emptyLine(), pageBreak()
  ];
}

// ─── Ethical Considerations ────────────────────────────────────────────────

function ethicsSection() {
  return [
    heading1("8. ETHICAL CONSIDERATIONS"),
    body("The study will be conducted in accordance with the principles of the Declaration of Helsinki (revised 2013) and Good Clinical Practice (GCP) guidelines."),
    emptyLine(),
    labelValue("Ethics Committee", "[Institutional Ethics Committee Name, Institution], [City]"),
    labelValue("Consent", "As this is a retrospective study involving review of existing medical records, individual informed consent from patients will be waived. Approval will be obtained from the Institutional Ethics Committee (IEC) / Institutional Review Board (IRB) before commencement of data collection."),
    labelValue("Confidentiality", "All patient data will be de-identified and coded before analysis. Personal identifiers (name, address, contact number) will not be recorded in the CRF or the database. Data will be stored in a password-protected system accessible only to the research team."),
    labelValue("Data Security", "Physical CRFs will be stored in a locked cabinet accessible only to the PI. Electronic data will be stored in an encrypted, password-protected folder on a secure institutional server."),
    labelValue("Conflict of Interest", "No funding from pharmaceutical companies. No conflict of interest declared."),
    emptyLine(), pageBreak()
  ];
}

// ─── References ────────────────────────────────────────────────────────────

function referencesSection() {
  const refs = [
    "Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis. 2007;44(Suppl 2):S27-72.",
    "Kalil AC, Metersky ML, Klompas M, et al. Management of Adults With Hospital-acquired and Ventilator-associated Pneumonia: 2016 Clinical Practice Guidelines by the IDSA and ATS. Clin Infect Dis. 2016;63(5):e61-e111.",
    "Nasr R, Rahal EA, Haddad C, et al. Assessment of Compliance with National and International Guidelines in the Empirical Management of Community-Acquired Pneumonia (CAP) in Lebanese Hospitals: A Multicenter Retrospective Cohort Study. Antibiotics (Basel). 2026 May 30. PMID: 42353675.",
    "Ablakimova N, Rachina S, Strelkova D, et al. Antimicrobial stewardship interventions in adults with hospital-acquired pneumonia: a systematic review and meta-analysis. J Hosp Infect. 2026 Mar. PMID: 41534745.",
    "Ablakimova N, Rachina S, Silva HR, et al. Antimicrobial stewardship interventions in hospitalized adults with community-acquired pneumonia: a systematic review and meta-analysis. Eur J Clin Microbiol Infect Dis. 2025 Jul. PMID: 40202602.",
    "Odeyemi YE, Tekin A, Schanz CC, et al. Comparative Effectiveness of Azithromycin Versus Doxycycline in Hospitalized Patients With Community-Acquired Pneumonia Treated With Beta-Lactams. Clin Infect Dis. 2026 Apr 30. PMID: 40378193.",
    "Deshpande A, Klompas M, Guo N, et al. Intravenous to Oral Antibiotic Switch Therapy Among Patients Hospitalized With Community-Acquired Pneumonia. Clin Infect Dis. 2023. PMID: 37011018.",
    "Magill SS, Edwards JR, Bamberg W, et al. Multistate Point-Prevalence Survey of Health Care-Associated Infections. N Engl J Med. 2014;370(13):1198-1208.",
    "World Health Organization (WHO). Antimicrobial Resistance: Global Report on Surveillance. Geneva: WHO; 2014.",
    "Torres A, Cilloniz C, Niederman MS, et al. Pneumonia. Nat Rev Dis Primers. 2021;7(1):25.",
  ];
  return [
    heading1("9. REFERENCES"),
    ...refs.map((ref, i) =>
      new Paragraph({
        spacing: { before: 80, after: 80, line: 320 },
        children: [new TextRun({ text: `${i + 1}. ${ref}`, size: 20, font: "Arial" })]
      })
    ),
    emptyLine(), pageBreak()
  ];
}

// ─── Annexure - CRF ────────────────────────────────────────────────────────

function annexureCRF() {
  return [
    heading1("ANNEXURE I: CASE RECORD FORM (CRF)"),
    new Paragraph({
      spacing: { before: 100, after: 100 },
      children: [new TextRun({ text: "CASE RECORD FORM - CAP vs. HAP Comparative Study", bold: true, size: 24, font: "Arial" })]
    }),
    emptyLine(),
    labelValue("CRF Number", "____________"),
    labelValue("Date of Data Entry", "____________"),
    labelValue("Data Entered by", "____________"),
    emptyLine(),

    heading2("SECTION A: Patient Demographics"),
    makeTable([
      { cells: [{ text: "Patient ID (Coded)", shade: true, width: 3000 }, { text: "", width: 6360 }]},
      { cells: [{ text: "Age (years)", shade: true }, { text: "" }]},
      { cells: [{ text: "Gender", shade: true }, { text: "Male / Female / Other" }]},
      { cells: [{ text: "Weight (kg) / BMI", shade: true }, { text: "" }]},
      { cells: [{ text: "Admission Date", shade: true }, { text: "" }]},
      { cells: [{ text: "Discharge/Death Date", shade: true }, { text: "" }]},
      { cells: [{ text: "Ward", shade: true }, { text: "Medical / Pulmonology / ICU / Other: ____________" }]},
      { cells: [{ text: "Pneumonia Type", shade: true }, { text: "CAP / HAP" }]},
      { cells: [{ text: "Smoking History", shade: true }, { text: "Yes / No / Ex-smoker" }]},
    ]),
    emptyLine(),

    heading2("SECTION B: Comorbidities"),
    makeTable([
      { isHeaderRow: true, cells: [{ text: "Comorbidity", header: true, width: 5000 }, { text: "Yes / No", header: true, width: 4360 }]},
      { cells: [{ text: "Diabetes Mellitus", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Chronic Obstructive Pulmonary Disease (COPD)", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Chronic Kidney Disease (CKD)", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Congestive Heart Failure (CHF)", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Malignancy", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Hypertension", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Liver Disease", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Prior hospitalization (< 90 days)", shade: false }, { text: "Yes / No" }]},
      { cells: [{ text: "Prior antibiotic use (< 30 days)", shade: false }, { text: "Yes / No" }]},
    ]),
    emptyLine(),

    heading2("SECTION C: Disease Severity Scores"),
    makeTable([
      { cells: [{ text: "PSI / PORT Score (CAP)", shade: true, width: 3500 }, { text: "Class I / II / III / IV / V  |  Score: ___", width: 5860 }]},
      { cells: [{ text: "CURB-65 Score (CAP)", shade: true }, { text: "Score: ___" }]},
      { cells: [{ text: "CPIS Score (HAP)", shade: true }, { text: "Score: ___" }]},
      { cells: [{ text: "qSOFA / SOFA Score", shade: true }, { text: "Score: ___" }]},
    ]),
    emptyLine(),

    heading2("SECTION D: Microbiological Data"),
    makeTable([
      { cells: [{ text: "Culture Sent (Yes/No)", shade: true, width: 3500 }, { text: "", width: 5860 }]},
      { cells: [{ text: "Specimen Type", shade: true }, { text: "Blood / Sputum / BAL / Tracheal aspirate / Other" }]},
      { cells: [{ text: "Culture Result", shade: true }, { text: "Positive / Negative / Contaminated" }]},
      { cells: [{ text: "Organism Identified", shade: true }, { text: "" }]},
      { cells: [{ text: "MDR Status", shade: true }, { text: "MDR / Non-MDR / XDR / PDR" }]},
      { cells: [{ text: "Sensitive to (list drugs)", shade: true }, { text: "" }]},
      { cells: [{ text: "Resistant to (list drugs)", shade: true }, { text: "" }]},
    ]),
    emptyLine(),

    heading2("SECTION E: Antimicrobial Therapy"),
    makeTable([
      { isHeaderRow: true, cells: [
        { text: "#", header: true, width: 400 },
        { text: "Drug Name", header: true, width: 1800 },
        { text: "Dose", header: true, width: 1200 },
        { text: "Route", header: true, width: 1000 },
        { text: "Frequency", header: true, width: 1200 },
        { text: "Duration (days)", header: true, width: 1500 },
        { text: "Empiric / Definitive", header: true, width: 2260 }
      ]},
      { cells: [{ text: "1" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }]},
      { cells: [{ text: "2" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }]},
      { cells: [{ text: "3" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }]},
      { cells: [{ text: "4" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }]},
    ]),
    emptyLine(),
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      { cells: [{ text: "De-escalation Performed", shade: true }, { text: "Yes / No  (If yes, on Day: ___)" }]},
      { cells: [{ text: "IV-to-Oral Switch", shade: true }, { text: "Yes / No  (If yes, on Day: ___)" }]},
      { cells: [{ text: "Total Antibiotic Duration (DOT)", shade: true }, { text: "___ days" }]},
      { cells: [{ text: "Time to First Antibiotic Dose", shade: true }, { text: "___ hours from diagnosis" }]},
    ]),
    emptyLine(),

    heading2("SECTION F: Clinical Outcomes"),
    makeTable([
      { cells: [{ text: "Clinical Outcome", shade: true, width: 3500 }, { text: "Cured / Treatment Failure / Died / Transferred", width: 5860 }]},
      { cells: [{ text: "In-hospital Mortality", shade: true }, { text: "Yes / No" }]},
      { cells: [{ text: "Total Length of Stay (LOS)", shade: true }, { text: "___ days" }]},
      { cells: [{ text: "ICU Admission Required", shade: true }, { text: "Yes / No  |  ICU LOS: ___ days" }]},
      { cells: [{ text: "30-day Readmission", shade: true }, { text: "Yes / No" }]},
      { cells: [{ text: "Adverse Drug Reaction (ADR)", shade: true }, { text: "Yes / No  |  If Yes, describe: ____________" }]},
    ]),
    emptyLine()
  ];
}

// ─── Timeline ─────────────────────────────────────────────────────────────

function timelineSection() {
  return [
    heading1("10. STUDY TIMELINE (GANTT CHART)"),
    emptyLine(),
    makeTable([
      { isHeaderRow: true, cells: [
        { text: "Activity", header: true, width: 3200 },
        { text: "Month 1-2", header: true, width: 840 },
        { text: "Month 3-4", header: true, width: 840 },
        { text: "Month 5-8", header: true, width: 840 },
        { text: "Month 9-12", header: true, width: 840 },
        { text: "Month 13-16", header: true, width: 940 },
        { text: "Month 17-20", header: true, width: 940 },
        { text: "Month 21-24", header: true, width: 920 }
      ]},
      { cells: [
        { text: "Protocol preparation & IEC submission" }, { text: "X" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }
      ]},
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      ]},
      { cells: [
        { text: "Data entry and cleaning" }, { text: "" }, { text: "" }, { text: "" }, { text: "X" }, { text: "X" }, { text: "" }, { text: "" }
      ]},
      { cells: [
        { text: "Statistical analysis" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "X" }, { text: "" }, { text: "" }
      ]},
      { cells: [
        { text: "Results interpretation & discussion" }, { text: "" }, { text: "" }, { text: "" }, { text: "" }, { text: "X" }, { text: "X" }, { text: "" }
      ]},
      { cells: [
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      ]},
      { cells: [
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      ]},
    ]),
    emptyLine(), pageBreak()
  ];
}

// ─── Budget ───────────────────────────────────────────────────────────────

function budgetSection() {
  return [
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    emptyLine(),
    makeTable([
      { isHeaderRow: true, cells: [
        { text: "Item", header: true, width: 4500 },
        { text: "Estimated Cost (INR)", header: true, width: 4860 }
      ]},
      { cells: [{ text: "Stationery and printing (CRFs, consent forms, data sheets)" }, { text: "INR 2,000 - 5,000" }]},
      { cells: [{ text: "Data management and statistical software license" }, { text: "INR 0 (SPSS - institutional license) / INR 5,000 (if required)" }]},
      { cells: [{ text: "Publication / open access fee" }, { text: "INR 10,000 - 50,000 (depending on journal)" }]},
      { cells: [{ text: "Miscellaneous (travel for record review, communication)" }, { text: "INR 2,000 - 5,000" }]},
      { cells: [{ text: "Total", shade: true }, { text: "~INR 14,000 - 65,000" }]},
    ]),
    body("Note: This is an investigator-initiated study. No external funding is sought. All costs will be borne by the investigators."),
    emptyLine(), pageBreak()
  ];
}

// ─── Declaration ──────────────────────────────────────────────────────────

function declarationSection() {
  return [
    heading1("12. INVESTIGATOR DECLARATION"),
    body("We, the undersigned investigators, hereby declare that:"),
    bulletItem("This protocol has been designed with scientific rigor and ethical principles."),
    bulletItem("The study will be conducted in full compliance with the Declaration of Helsinki (2013), ICMR National Ethical Guidelines for Biomedical Research (2017), and Good Clinical Practice (GCP) guidelines."),
    bulletItem("Patient confidentiality will be maintained at all times."),
    bulletItem("No data manipulation or falsification will be performed."),
    bulletItem("Any protocol amendments will be communicated to the IEC/IRB prior to implementation."),
    emptyLine(), emptyLine(),
    makeTable([
      { isHeaderRow: true, cells: [
        { text: "Role", header: true, width: 2000 },
        { text: "Name", header: true, width: 2500 },
        { text: "Designation", header: true, width: 2500 },
        { text: "Signature & Date", header: true, width: 2360 }
      ]},
      { cells: [{ text: "Principal Investigator" }, { text: "" }, { text: "PharmD Candidate" }, { text: "" }]},
      { cells: [{ text: "Guide / Supervisor" }, { text: "" }, { text: "" }, { text: "" }]},
      { cells: [{ text: "Co-Investigator" }, { text: "" }, { text: "" }, { text: "" }]},
      { cells: [{ text: "Head of Department" }, { text: "" }, { text: "" }, { text: "" }]},
    ]),
    emptyLine()
  ];
}

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// ─── Table helpers ─────────────────────────────────────────────────────────

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// ─── Cover ────────────────────────────────────────────────────────────────

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    gap(), gap(), gap(),
    new Paragraph({
      alignment: AlignmentType.CENTER,
      spacing: { before: 0, after: 160 },
      children: [new TextRun({
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    }),
    gap(), gap(),
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      [cell("Field", { hdr: true, w: 3200 }), cell("Details", { hdr: true, w: 6160 })],
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      [cell("Study Design", { shade: true }), cell("Retrospective observational comparative study")],
      [cell("Principal Investigator", { shade: true }), cell("[Name], PharmD (Candidate)")],
      [cell("Statistician / Analyst", { shade: true }), cell("[Name], [Designation]")],
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}

// ─── Version History ───────────────────────────────────────────────────────

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    gap(), pb()
  ];
}

// ─── Study Overview ────────────────────────────────────────────────────────

function studyOverview() {
  return [
    h1("2. STUDY OVERVIEW"),
    h2("2.1 Study Objectives"),
    h3("Primary Objectives"),
    bullet("To compare antimicrobial therapy patterns (drug selection, duration, route, de-escalation) in CAP vs. HAP patients admitted to a tertiary care hospital."),
    bullet("To compare clinical outcomes (clinical cure rate, in-hospital mortality, length of hospital stay) between CAP and HAP groups."),
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    bullet("To describe the microbial etiology and antimicrobial susceptibility patterns in culture-positive CAP and HAP cases."),
    bullet("To evaluate adherence to IDSA/ATS 2019 guidelines (CAP) and IDSA 2016 HAP/VAP guidelines (HAP)."),
    bullet("To identify independent risk factors for in-hospital mortality and treatment failure in both groups."),
    bullet("To assess 30-day readmission rate and ICU transfer rate."),
    gap(),
    h2("2.2 Study Design and Population"),
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    lv("Setting", "[Tertiary care teaching hospital], [City]"),
    lv("Population", "Adult inpatients (age >= 18 years) with confirmed CAP or HAP"),
    lv("Data Period", "[Month Year] to [Month Year]"),
    lv("Target Sample", "Minimum 100 patients per group; total n >= 200"),
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      [cell("Primary", { shade: true }), cell("In-hospital mortality"), cell("Dichotomous"), cell("Categorical")],
      [cell("Primary", { shade: true }), cell("Length of hospital stay (LOS)"), cell("Continuous"), cell("Days")],
      [cell("Secondary", { shade: true }), cell("Guideline adherence rate"), cell("Dichotomous/Ordinal"), cell("Categorical")],
      [cell("Secondary", { shade: true }), cell("Rate of antibiotic de-escalation"), cell("Dichotomous"), cell("Categorical")],
      [cell("Secondary", { shade: true }), cell("Total antibiotic duration (DOT)"), cell("Continuous"), cell("Days")],
      [cell("Secondary", { shade: true }), cell("MDR organism prevalence"), cell("Dichotomous"), cell("Categorical")],
      [cell("Secondary", { shade: true }), cell("30-day readmission rate"), cell("Dichotomous"), cell("Categorical")],
      [cell("Secondary", { shade: true }), cell("ICU transfer rate"), cell("Dichotomous"), cell("Categorical")],
      [cell("Secondary", { shade: true }), cell("Time to first antibiotic dose"), cell("Continuous"), cell("Hours")],
    ]),
    gap(), pb()
  ];
}

// ─── Data Management ───────────────────────────────────────────────────────

function dataManagement() {
  return [
    h1("3. DATA MANAGEMENT"),
    h2("3.1 Data Sources"),
    bullet("In-patient medical records (paper or electronic health records, EHR)."),
    bullet("Microbiology laboratory register and culture sensitivity reports."),
    bullet("Pharmacy prescription and medication administration records (MAR)."),
    bullet("Radiology reports (chest X-ray / CT thorax)."),
    bullet("Discharge summaries and hospital mortality register."),
    gap(),
    h2("3.2 Data Entry and Storage"),
    body("Data will be entered into a structured Microsoft Excel spreadsheet (or REDCap, if available) using a double-entry method. The final clean database will be exported to SPSS v26.0 (.sav format) for analysis. All files will be stored in an encrypted, password-protected folder on an institutional server with restricted access."),
    gap(),
    h2("3.3 Coding Conventions"),
    gap(),
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      [cell("Variable", { hdr: true, w: 3000 }), cell("Coding Convention", { hdr: true, w: 6360 })],
      [cell("Pneumonia Group", { shade: true }), cell("1 = CAP; 2 = HAP")],
      [cell("Gender", { shade: true }), cell("1 = Male; 2 = Female; 3 = Other")],
      [cell("Clinical Outcome", { shade: true }), cell("1 = Cured; 2 = Treatment Failure; 3 = Died; 4 = Transferred")],
      [cell("In-hospital Mortality", { shade: true }), cell("0 = No; 1 = Yes")],
      [cell("All Yes/No Variables", { shade: true }), cell("0 = No; 1 = Yes")],
      [cell("Severity Scores", { shade: true }), cell("Entered as continuous numeric values (PSI, CURB-65, CPIS, SOFA)"),],
      [cell("Dates", { shade: true }), cell("DD/MM/YYYY format; LOS calculated as Discharge Date minus Admission Date")],
      [cell("MDR Status", { shade: true }), cell("0 = Non-MDR; 1 = MDR; 2 = XDR; 3 = PDR (per ECDC/CDC 2012 definition)")],
      [cell("Missing Data", { shade: true }), cell("Left blank in Excel; coded as system-missing in SPSS (not zero-filled)")],
    ]),
    gap(),
    h2("3.4 Missing Data Handling"),
    body("Missing data will be reported transparently for each variable. The following approach will be used:"),
    bullet("Variables with < 5% missing: Complete-case analysis (listwise deletion) will be acceptable."),
    bullet("Variables with 5-20% missing: Multiple Imputation (MI) using Predictive Mean Matching for continuous variables and Logistic Regression for binary variables (m = 5 imputed datasets, combined using Rubin's rules)."),
    bullet("Variables with > 20% missing: Excluded from multivariable models; reported as a study limitation."),
    bullet("Sensitivity analyses will be conducted comparing complete-case vs. imputed results for primary outcomes."),
    gap(),
    h2("3.5 Database Lock"),
    body("The database will be declared 'locked' only after:"),
    bullet("All CRFs have been entered and double-checked."),
    bullet("Range checks and logical inconsistency checks have been resolved."),
    bullet("The SAP has been finalized and signed off by the PI and statistician."),
    body("No analysis will commence before database lock."),
    gap(), pb()
  ];
}

// ─── Analysis Populations ─────────────────────────────────────────────────

function populations() {
  return [
    h1("4. ANALYSIS POPULATIONS"),
    gap(),
    tbl([
      [cell("Population", { hdr: true, w: 2200 }), cell("Definition", { hdr: true, w: 4500 }), cell("Used For", { hdr: true, w: 2660 })],
      [cell("Full Analysis Set (FAS)", { shade: true }), cell("All eligible patients meeting inclusion/exclusion criteria with at least one documented antibiotic dose. This is the primary analysis population."), cell("All primary and secondary analyses")],
      [cell("Culture-Positive Subset (CPS)", { shade: true }), cell("Patients within FAS who had at least one microbiological culture sent with a valid result (positive or negative). Excludes contaminated specimens."), cell("Microbial etiology, MDR prevalence, susceptibility analyses, guideline concordance sub-analysis")],
      [cell("Mortality Analysis Set (MAS)", { shade: true }), cell("All FAS patients with a recorded clinical outcome (cured, failed, died, or transferred). Patients with outcome data missing will be excluded and documented."), cell("Mortality, Kaplan-Meier, logistic regression")],
      [cell("ICU Subgroup", { shade: true }), cell("Patients requiring ICU admission at any point during index hospitalization."), cell("Exploratory ICU-specific subgroup analysis")],
    ]),
    gap(),
    note("The FAS is the pre-specified primary population. Any deviation from this (e.g., excluding a subset post-hoc) will be documented as a protocol deviation."),
    gap(), pb()
  ];
}

// ─── Descriptive Statistics ────────────────────────────────────────────────

function descriptiveStats() {
  return [
    h1("5. DESCRIPTIVE STATISTICS"),
    h2("5.1 Continuous Variables"),
    body("For each continuous variable, the following will be reported per group (CAP / HAP) and overall:"),
    gap(),
    tbl([
      [cell("Distribution", { hdr: true, w: 2500 }), cell("Test for Normality", { hdr: true, w: 2500 }), cell("Summary Statistic", { hdr: true, w: 4360 })],
      [cell("Normal (Gaussian)", { shade: true }), cell("Shapiro-Wilk test (n < 50 per group)\nKolmogorov-Smirnov (n >= 50)"), cell("Mean ± Standard Deviation (SD); 95% CI of mean")],
      [cell("Non-normal / Skewed", { shade: true }), cell("Same as above; p < 0.05 = non-normal"), cell("Median with Interquartile Range (IQR: Q1-Q3); range (min-max)")],
    ]),
    gap(),
    body("Histograms and Q-Q plots will be generated for all continuous primary outcome variables (LOS, DOT) to visually assess normality. Log-transformation will be applied to highly skewed variables (e.g., LOS, CRP) before parametric testing if required."),
    gap(),
    h2("5.2 Categorical Variables"),
    body("All categorical and binary variables will be reported as frequency (n) and percentage (%) per group and overall. Proportions will be reported with 95% confidence intervals using the Wilson score method."),
    gap(),
    h2("5.3 Baseline Characteristics Table (Table 1)"),
    body("A summary Table 1 will be generated presenting all demographic and clinical characteristics stratified by pneumonia type (CAP vs. HAP). The table will include the following domains:"),
    bullet("Demographics: Age (mean ± SD or median [IQR]), gender (%), BMI."),
    bullet("Comorbidities: DM, COPD, CKD, CHF, malignancy, hypertension (%)."),
    bullet("Disease severity scores: PSI class (CAP), CURB-65 (CAP), CPIS (HAP), SOFA (all)."),
    bullet("Admission vital signs: Temperature, heart rate, RR, SpO2, blood pressure."),
    bullet("Laboratory values at admission: WBC, CRP, procalcitonin, serum creatinine."),
    bullet("Microbiological culture sent (yes/no) and culture positivity rate (%)."),
    gap(),
    note("No formal hypothesis testing (p-values) will be reported in Table 1, as this is a retrospective observational study and baseline differences are not 'chance' occurrences. Standardized Mean Differences (SMD) will be reported instead to quantify imbalance, with |SMD| > 0.1 considered a meaningful imbalance."),
    gap(), pb()
  ];
}

// ─── Inferential Statistics ────────────────────────────────────────────────

function inferentialStats() {
  return [
    h1("6. INFERENTIAL STATISTICAL ANALYSES"),
    h2("6.1 Primary Comparative Analyses (CAP vs. HAP)"),
    body("All comparisons between CAP and HAP groups are pre-specified. Two-tailed tests will be used throughout. Alpha = 0.05."),
    gap(),
    tbl([
      [cell("Variable / Outcome", { hdr: true, w: 2800 }), cell("Variable Type", { hdr: true, w: 1800 }), cell("Statistical Test", { hdr: true, w: 2400 }), cell("Effect Size", { hdr: true, w: 2360 })],
      [cell("Clinical cure rate", { shade: true }), cell("Binary"), cell("Chi-square test (or Fisher's exact if any cell < 5)"), cell("Relative Risk (RR) + 95% CI")],
      [cell("In-hospital mortality", { shade: true }), cell("Binary"), cell("Chi-square test"), cell("RR + 95% CI; NNH/NNT")],
      [cell("Length of Stay (LOS)", { shade: true }), cell("Continuous"), cell("Independent samples t-test (normal) OR Mann-Whitney U (non-normal)"), cell("Cohen's d (normal); rank-biserial r (non-normal)")],
      [cell("Total antibiotic DOT", { shade: true }), cell("Continuous"), cell("Mann-Whitney U (expected skewed)"), cell("Rank-biserial r")],
      [cell("Time to 1st antibiotic (hrs)", { shade: true }), cell("Continuous"), cell("Mann-Whitney U"), cell("Rank-biserial r")],
      [cell("Guideline adherence", { shade: true }), cell("Binary"), cell("Chi-square test"), cell("RR + 95% CI")],
      [cell("De-escalation rate", { shade: true }), cell("Binary"), cell("Chi-square test"), cell("RR + 95% CI")],
      [cell("MDR organism prevalence", { shade: true }), cell("Binary"), cell("Chi-square or Fisher's exact"), cell("RR + 95% CI")],
      [cell("30-day readmission", { shade: true }), cell("Binary"), cell("Chi-square test"), cell("RR + 95% CI")],
      [cell("ICU transfer rate", { shade: true }), cell("Binary"), cell("Chi-square test"), cell("RR + 95% CI")],
    ]),
    gap(),
    note("All p-values will be reported to 3 decimal places. P < 0.001 will be reported as '< 0.001'. No rounding to p = 0.000."),
    gap(),
    h2("6.2 Multiple Comparisons"),
    body("For the primary outcomes (clinical cure, mortality, LOS), no Bonferroni correction is applied as these are distinct clinical endpoints rather than multiple tests on the same endpoint. For secondary sub-group analyses involving more than 3 comparisons on the same variable, Bonferroni correction will be applied, and corrected alpha will be reported."),
    gap(),
    h2("6.3 Antibiotic Class Frequency Analysis"),
    body("The frequency and proportion of each antibiotic class used empirically in CAP vs. HAP will be tabulated:"),
    bullet("Beta-lactams (aminopenicillins, antipseudomonal penicillins, 3rd/4th generation cephalosporins, carbapenems)."),
    bullet("Macrolides (azithromycin, clarithromycin)."),
    bullet("Fluoroquinolones (levofloxacin, moxifloxacin, ciprofloxacin)."),
    bullet("Aminoglycosides."),
    bullet("Glycopeptides (vancomycin, teicoplanin)."),
    bullet("Polymyxins (colistin, polymyxin B)."),
    bullet("Oxazolidinones (linezolid)."),
    bullet("Others (metronidazole, antifungals, antivirals as co-prescriptions)."),
    body("Combination therapy (two or more antibiotics for the same episode) vs. monotherapy will be compared between groups using chi-square test."),
    gap(), pb()
  ];
}

// ─── Multivariate ─────────────────────────────────────────────────────────

function multivariateSection() {
  return [
    h1("7. MULTIVARIABLE REGRESSION ANALYSES"),
    h2("7.1 Binary Logistic Regression: In-Hospital Mortality"),
    body("A binary logistic regression model will be constructed to identify independent predictors of in-hospital mortality (dependent variable: 0 = survived; 1 = died)."),
    gap(),
    h3("7.1.1 Candidate Predictor Variables"),
    bullet("Pneumonia type (CAP vs. HAP) — primary exposure variable."),
    bullet("Age (continuous, years)."),
    bullet("Gender."),
    bullet("Disease severity score (PSI Class for CAP; CPIS score for HAP; SOFA score for all)."),
    bullet("Number of comorbidities (Charlson Comorbidity Index, CCI)."),
    bullet("MDR organism identified (yes/no)."),
    bullet("Guideline-concordant empiric therapy (yes/no)."),
    bullet("De-escalation performed (yes/no)."),
    bullet("ICU admission (yes/no)."),
    bullet("Time to first antibiotic dose (hours)."),
    gap(),
    h3("7.1.2 Variable Selection Strategy"),
    body("Univariable logistic regression will first be performed for each candidate predictor. Variables with p < 0.20 in univariable analysis will be entered into the multivariable model (liberal threshold to avoid excluding clinically important variables). Final model building will use:"),
    bullet("Backward elimination method (likelihood ratio criterion, p-removal = 0.10)."),
    bullet("Clinically important variables (age, severity score, pneumonia type) will be retained regardless of statistical significance."),
    gap(),
    h3("7.1.3 Model Diagnostics"),
    bullet("Hosmer-Lemeshow goodness-of-fit test (p > 0.05 = acceptable fit)."),
    bullet("Nagelkerke R2 reported as a measure of explained variance."),
    bullet("Area Under the ROC Curve (AUC-ROC) with 95% CI to assess discriminative ability."),
    bullet("Cook's Distance and DFBeta to identify influential observations."),
    bullet("Variance Inflation Factor (VIF) to assess multicollinearity (VIF > 5 = problematic)."),
    gap(),
    h3("7.1.4 Results Reporting"),
    body("Adjusted Odds Ratios (aOR) with 95% Confidence Intervals and p-values will be reported for each predictor retained in the final model. Unadjusted ORs from univariable analysis will also be presented for comparison."),
    gap(),
    h2("7.2 Binary Logistic Regression: Treatment Failure"),
    body("A second binary logistic regression model will be built for treatment failure (dependent variable: 0 = cured; 1 = treatment failure) using the same predictor variable pool and selection strategy as Section 7.1."),
    gap(),
    h2("7.3 Linear Regression: Length of Stay (LOS)"),
    body("If LOS is approximately normally distributed (or successfully log-transformed), a multivariable linear regression will assess independent predictors of LOS. If LOS remains severely non-normal, negative binomial regression or a Tobit regression will be used instead (will be decided after examining LOS distribution at data lock)."),
    bullet("Dependent variable: Total LOS (days) or log-transformed LOS."),
    bullet("Predictors: Same pool as Section 7.1."),
    bullet("Results: Regression coefficients (beta) with 95% CI; R2 and adjusted R2."),
    gap(),
    h2("7.4 Confounding Assessment"),
    body("Pneumonia type (CAP vs. HAP) is the primary exposure. Potential confounders identified a priori include:"),
    bullet("Age and sex (demographic confounders)."),
    bullet("Comorbidity burden (Charlson Comorbidity Index)."),
    bullet("Disease severity at admission (PSI/CPIS/SOFA scores)."),
    bullet("Prior antibiotic use within 30 days (selection pressure)."),
    bullet("Prior hospitalization within 90 days."),
    body("Propensity Score Analysis (PSA) will be performed as a sensitivity analysis (see Section 10) to account for non-random group assignment."),
    gap(), pb()
  ];
}

// ─── Survival Analysis ─────────────────────────────────────────────────────

function survivalSection() {
  return [
    h1("8. SURVIVAL AND TIME-TO-EVENT ANALYSES"),
    h2("8.1 Time-to-Clinical-Cure Analysis"),
    bullet("Event: Clinical cure (resolution of fever, improved respiratory parameters, no antibiotic change needed)."),
    bullet("Time origin: Date of antibiotic initiation."),
    bullet("Censoring: Patients who die, are transferred, or are discharged without a cure assessment will be censored at the date of censoring."),
    bullet("Method: Kaplan-Meier survival curves stratified by pneumonia type (CAP vs. HAP)."),
    bullet("Test: Log-rank test to compare curves; Wilcoxon (Breslow) test will also be reported for early differences."),
    bullet("Median time to clinical cure with 95% CI (Greenwood's formula) will be reported for each group."),
    gap(),
    h2("8.2 In-Hospital Survival (Time-to-Death) Analysis"),
    bullet("Event: In-hospital death (all-cause)."),
    bullet("Time origin: Date of hospital admission."),
    bullet("Censoring: Survivors censored at discharge date."),
    bullet("Method: Kaplan-Meier curves stratified by CAP vs. HAP."),
    bullet("Test: Log-rank test."),
    gap(),
    h2("8.3 Cox Proportional Hazards Regression"),
    body("If sample size is sufficient (minimum 10 events per predictor variable), a multivariable Cox proportional hazards model will be fit for time-to-death, incorporating the same predictor pool as Section 7.1."),
    bullet("Results reported as Hazard Ratios (HR) with 95% CI."),
    bullet("Proportional hazards assumption will be assessed using Schoenfeld residuals (scaled) and log(-log) plots."),
    bullet("If the proportional hazards assumption is violated for any variable, time-varying covariates or restricted mean survival time (RMST) analysis will be used."),
    gap(), pb()
  ];
}

// ─── Subgroup Analyses ─────────────────────────────────────────────────────

function subgroupSection() {
  return [
    h1("9. PRE-SPECIFIED SUBGROUP ANALYSES"),
    body("The following subgroup analyses are pre-specified. They are exploratory and will be interpreted with caution given the reduced statistical power. Interaction tests (effect modification) will be performed for each."),
    gap(),
    tbl([
      [cell("Subgroup", { hdr: true, w: 2500 }), cell("Stratification Variable", { hdr: true, w: 2500 }), cell("Outcome Assessed", { hdr: true, w: 2500 }), cell("Statistical Test", { hdr: true, w: 1860 })],
      [cell("ICU vs. non-ICU admitted"), cell("ICU admission (yes/no)"), cell("Mortality, LOS, DOT"), cell("Chi-sq; Mann-Whitney")],
      [cell("MDR vs. non-MDR infections"), cell("MDR organism (yes/no)"), cell("Mortality, treatment failure, LOS"), cell("Chi-sq; Mann-Whitney")],
      [cell("Guideline concordant vs. non-concordant prescribing"), cell("Guideline adherence (yes/no)"), cell("Clinical cure, mortality"), cell("Chi-sq; RR")],
      [cell("Severe vs. non-severe CAP (PSI Class IV-V vs. I-III)"), cell("PSI Class"), cell("Mortality, LOS"), cell("Chi-sq; Mann-Whitney")],
      [cell("Elderly (>= 65 years) vs. non-elderly"), cell("Age group"), cell("Mortality, LOS, DOT"), cell("Chi-sq; Mann-Whitney")],
      [cell("De-escalation performed vs. not"), cell("De-escalation (yes/no)"), cell("LOS, 30-day readmission"), cell("Chi-sq; Mann-Whitney")],
    ]),
    gap(),
    note("Subgroup analyses will not be the basis for primary conclusions. Interaction p-values (Breslow-Day or Mantel-Haenszel) will be reported. Results will be presented as Forest plots where feasible."),
    gap(), pb()
  ];
}

// ─── Sensitivity Analyses ─────────────────────────────────────────────────

function sensitivitySection() {
  return [
    h1("10. SENSITIVITY ANALYSES"),
    body("The following sensitivity analyses are pre-specified to test the robustness of the primary findings:"),
    gap(),
    h2("10.1 Complete-Case vs. Multiple Imputation"),
    body("Primary outcome analyses (mortality, clinical cure, LOS) will be re-run on the complete-case dataset (excluding all records with any missing covariate) and compared to results from the multiply imputed dataset. If results differ materially (aOR difference > 10%), the imputed analysis will be the primary report and the complete-case analysis reported as a sensitivity analysis."),
    gap(),
    h2("10.2 Propensity Score Analysis (PSA)"),
    body("To account for the non-randomized, observational nature of CAP vs. HAP group assignment, a propensity score for 'having HAP' will be estimated using logistic regression, including age, sex, CCI score, prior hospitalization, prior antibiotic use, and ward of admission as predictors."),
    bullet("Propensity score matching (1:1 nearest-neighbor matching, caliper = 0.2 SD of logit of PS) will be attempted."),
    bullet("Balance after matching will be assessed by SMD (target |SMD| < 0.1)."),
    bullet("Primary outcomes will be re-analyzed in the matched cohort and compared to unmatched results."),
    bullet("If matching reduces the sample by > 30%, Inverse Probability of Treatment Weighting (IPTW) will be used instead."),
    gap(),
    h2("10.3 Excluding Transfers and Readmissions"),
    body("The primary analysis will be repeated after excluding patients who were transferred from another facility (potential misclassification of HAP) to test whether findings are driven by this group."),
    gap(),
    h2("10.4 Alternate Outcome Definition for Clinical Cure"),
    body("Clinical cure will be re-assessed using a stricter definition (requiring documented radiological improvement in addition to clinical improvement) in a sensitivity analysis."),
    gap(), pb()
  ];
}

// ─── Output Tables Plan ────────────────────────────────────────────────────

function outputTablesSection() {
  return [
    h1("11. PLANNED OUTPUT TABLES AND FIGURES"),
    h2("11.1 Tables"),
    gap(),
    tbl([
      [cell("Table No.", { hdr: true, w: 1000 }), cell("Title", { hdr: true, w: 5500 }), cell("Section in Manuscript", { hdr: true, w: 2860 })],
      [cell("Table 1", { shade: true }), cell("Baseline demographics and clinical characteristics of CAP vs. HAP patients"), cell("Results")],
      [cell("Table 2", { shade: true }), cell("Microbial etiology and antimicrobial susceptibility patterns in culture-positive cases"), cell("Results")],
      [cell("Table 3", { shade: true }), cell("Empiric antimicrobial therapy regimens: drug classes, combinations, route, and duration"), cell("Results")],
      [cell("Table 4", { shade: true }), cell("Guideline adherence analysis: IDSA/ATS 2019 (CAP) and IDSA 2016 (HAP)"), cell("Results")],
      [cell("Table 5", { shade: true }), cell("Clinical outcomes comparison: clinical cure, in-hospital mortality, LOS, DOT, readmission"), cell("Results")],
      [cell("Table 6", { shade: true }), cell("Univariable logistic regression for in-hospital mortality"), cell("Results")],
      [cell("Table 7", { shade: true }), cell("Multivariable logistic regression: independent predictors of in-hospital mortality"), cell("Results")],
      [cell("Table 8", { shade: true }), cell("Multivariable logistic regression: independent predictors of treatment failure"), cell("Results")],
      [cell("Table S1", { shade: true }), cell("Sensitivity analysis: complete-case vs. multiple imputation results"), cell("Supplement")],
      [cell("Table S2", { shade: true }), cell("Propensity score matched cohort analysis"), cell("Supplement")],
    ]),
    gap(),
    h2("11.2 Figures"),
    gap(),
    tbl([
      [cell("Figure No.", { hdr: true, w: 1000 }), cell("Title", { hdr: true, w: 5500 }), cell("Type", { hdr: true, w: 2860 })],
      [cell("Figure 1", { shade: true }), cell("STROBE flow diagram of patient inclusion/exclusion"), cell("Flowchart")],
      [cell("Figure 2", { shade: true }), cell("Distribution of microbial pathogens in CAP vs. HAP (culture-positive cases)"), cell("Stacked bar chart")],
      [cell("Figure 3", { shade: true }), cell("Antibiotic class utilization pattern in CAP vs. HAP"), cell("Grouped bar chart")],
      [cell("Figure 4", { shade: true }), cell("Kaplan-Meier survival curve: time-to-clinical-cure in CAP vs. HAP"), cell("K-M curve")],
      [cell("Figure 5", { shade: true }), cell("Kaplan-Meier survival curve: in-hospital survival (time-to-death) in CAP vs. HAP"), cell("K-M curve")],
      [cell("Figure 6", { shade: true }), cell("Forest plot: subgroup analysis of in-hospital mortality by key stratifying variables"), cell("Forest plot")],
      [cell("Figure 7", { shade: true }), cell("AUC-ROC curve for the final logistic regression model for mortality"), cell("ROC curve")],
    ]),
    gap(), pb()
  ];
}

// ─── Software ─────────────────────────────────────────────────────────────

function softwareSection() {
  return [
    h1("12. SOFTWARE AND TOOLS"),
    gap(),
    tbl([
      [cell("Software", { hdr: true, w: 2500 }), cell("Version", { hdr: true, w: 1500 }), cell("Purpose", { hdr: true, w: 5360 })],
      [cell("IBM SPSS Statistics", { shade: true }), cell("v26.0"), cell("Primary analysis: descriptive stats, chi-square, Mann-Whitney, t-test, logistic regression, ROC curves")],
      [cell("SPSS Survival Module", { shade: true }), cell("v26.0"), cell("Kaplan-Meier, log-rank test, Cox regression")],
      [cell("OpenEpi"), cell("Online (v3.01)"), cell("Sample size calculation, 95% CIs for proportions")],
      [cell("Microsoft Excel"), cell("2019/365"), cell("Data entry, double-entry verification, data cleaning")],
      [cell("GraphPad Prism (optional)"), cell("v9.0+"), cell("Forest plots, K-M curves, ROC curves (publication quality)")],
      [cell("R (optional)"), cell("v4.3+"), cell("Multiple imputation (mice package), propensity score analysis (MatchIt package)")],
    ]),
    gap(),
    note("If R is used for sensitivity analyses, all R code will be archived alongside the dataset and made available on request to support reproducibility."),
    gap(), pb()
  ];
}

// ─── Reporting Standards ──────────────────────────────────────────────────

function reportingSection() {
  return [
    h1("13. REPORTING STANDARDS"),
    h2("13.1 Manuscript Reporting"),
    body("This study will be reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for observational studies. The STROBE checklist will be completed and submitted as a supplementary document with the manuscript."),
    gap(),
    h2("13.2 STROBE Checklist Key Items for This Study"),
    bullet("Title and Abstract: Clearly identify study as a retrospective observational comparative study."),
    bullet("Introduction: State specific objectives with reference to established hypotheses."),
    bullet("Methods: Describe study setting, participants, variables, data sources, bias, statistical methods fully."),
    bullet("Results: Report numbers at each stage (STROBE flow diagram), unadjusted and adjusted estimates."),
    bullet("Discussion: Summarise key results, discuss limitations, generalizability, and bias."),
    gap(),
    h2("13.3 Post-Hoc Analyses"),
    body("Any analysis not pre-specified in this SAP that is conducted after data collection will be clearly labelled as 'post-hoc exploratory analysis' in the Results section and in any associated manuscript. Such analyses will not be used to support primary conclusions."),
    gap(),
    h2("13.4 Presentation of Results"),
    bullet("Binary outcomes: Reported as n (%), RR, OR with 95% CI and p-value."),
    bullet("Continuous outcomes: Mean +/- SD or Median [IQR] with test statistic and p-value."),
    bullet("Regression results: Unadjusted and adjusted ORs with 95% CI and p-values in separate columns."),
    bullet("All p-values two-tailed; alpha = 0.05."),
    bullet("Exact p-values reported (not merely '< 0.05' or 'NS')."),
    gap(), pb()
  ];
}

// ─── Limitations ──────────────────────────────────────────────────────────

function limitationsSection() {
  return [
    h1("14. ANTICIPATED STATISTICAL LIMITATIONS"),
    bullet("Retrospective design limits causal inference. Unmeasured confounders (e.g., severity nuances, prior outpatient antibiotics not documented) may exist."),
    bullet("Single-center data limits generalizability. Local antibiograms and prescribing patterns may not reflect regional or national trends."),
    bullet("Culture positivity is typically 30-50% in CAP and 50-70% in HAP; a substantial proportion of microbiological analyses will be restricted to the culture-positive subset, reducing power for those analyses."),
    bullet("Retrospective ICD-10 coding may misclassify some CAP/HAP cases. A manual chart review validation of a random 10% sample will be performed to estimate coding error rate."),
    bullet("Survival analysis censoring assumptions (non-informative censoring) may be violated if patients are discharged due to deterioration rather than recovery."),
    bullet("Sample size was estimated for the primary outcome (mortality); secondary outcomes may be underpowered."),
    gap(), pb()
  ];
}

// ─── Sign-off ─────────────────────────────────────────────────────────────

function signoffSection() {
  return [
    h1("15. SAP SIGN-OFF"),
    body("This Statistical Analysis Plan has been reviewed and approved by all listed investigators. No modifications to the analyses described herein will be made after the database is locked without formal documentation as a SAP amendment."),
    gap(), gap(),
    tbl([
      [cell("Role", { hdr: true, w: 2200 }), cell("Name", { hdr: true, w: 2500 }), cell("Designation", { hdr: true, w: 2500 }), cell("Signature & Date", { hdr: true, w: 2160 })],
      [cell("Principal Investigator"), cell(""), cell("PharmD Candidate"), cell("")],
      [cell("Guide / Supervisor"), cell(""), cell(""), cell("")],
      [cell("Statistician / Analyst"), cell(""), cell(""), cell("")],
      [cell("Co-Investigator"), cell(""), cell(""), cell("")],
    ]),
    gap(), gap(),
    new Paragraph({
      alignment: AlignmentType.CENTER,
      spacing: { before: 120, after: 120 },
      children: [new TextRun({
        text: "This document is LOCKED from the date of the last signature above.\nAny post-lock amendments require a new version entry in Section 1 (Version History).",
        size: 20, font: "Arial", italics: true, color: "C53030", bold: true
      })]
    })
  ];
}

// ─── Assemble Document ────────────────────────────────────────────────────

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const pres = new pptxgen();
pres.layout = "LAYOUT_WIDE"; // 13.3" x 7.5"
pres.title = "CAP vs HAP Comparative Study - Protocol Approval";
pres.author = "PharmD Research Team";

// ─── Design System ───────────────────────────────────────────────────────
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// ─── Helpers ─────────────────────────────────────────────────────────────

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// ────────────────────────────────────────────────────────────────────────
// SLIDE 1 — TITLE SLIDE
// ────────────────────────────────────────────────────────────────────────
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// ────────────────────────────────────────────────────────────────────────
// SLIDE 2 — PRESENTATION OUTLINE
// ────────────────────────────────────────────────────────────────────────
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    ["02", "Study Objectives",              "What we aim to answer"],
    ["03", "Study Design & Population",     "How the study is structured"],
    ["04", "Data Collection & Variables",   "What data will be captured"],
    ["05", "Methodology & Definitions",     "Case definitions and criteria"],
    ["06", "Statistical Analysis Plan",     "How the data will be analyzed"],
    ["07", "Ethical Considerations",        "Compliance and patient protection"],
    ["08", "Timeline & Budget",             "Feasibility and resource plan"],
    ["09", "Expected Outcomes",             "Significance and deliverables"],
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// ────────────────────────────────────────────────────────────────────────
// SLIDE 3 — BACKGROUND & RATIONALE
// ────────────────────────────────────────────────────────────────────────
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  slideHeader(sl, "Background & Rationale", "The burden of pneumonia and the evidence gap");

  // Left column — stats boxes
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    ["#1", "Cause of infection-related\nmortality worldwide", C.navy],
    ["20-50%", "Mortality rate in\nHospital-Acquired Pneumonia", C.blue],
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    ["Local antibiograms and resistance patterns", "differ significantly from global data; institution-specific prescribing trends must be characterized."],
    ["Guideline adherence gaps", "have been reported globally (Nasr et al., Antibiotics 2026; Ablakimova et al., J Hosp Infect 2026)."],
    ["Pharmacist-led AMS interventions", "require a clear local baseline — this study provides exactly that."],
    ["No comparable study", "from this institution comparing CAP vs. HAP therapy, etiology, and outcomes currently exists."],
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// ────────────────────────────────────────────────────────────────────────
// SLIDE 4 — STUDY OBJECTIVES
// ────────────────────────────────────────────────────────────────────────
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  slideHeader(sl, "Study Objectives", "What this study aims to answer");

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    "Identify independent risk factors for in-hospital mortality and treatment failure",
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// ────────────────────────────────────────────────────────────────────────
// SLIDE 5 — STUDY DESIGN & POPULATION
// ────────────────────────────────────────────────────────────────────────
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  slideHeader(sl, "Study Design & Population", "How the study is structured");

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    "Hospital stay >= 48 hours",
    "Complete relevant medical and prescription records",
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    "Immunocompromised patients (HIV, transplant, chronic immunosuppressants)",
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    "Incomplete medical or prescription records",
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// ────────────────────────────────────────────────────────────────────────
// SLIDE 6 — DATA COLLECTION FRAMEWORK
// ────────────────────────────────────────────────────────────────────────
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    { title: "Disease Severity", color: C.blue, items: ["PSI / PORT (CAP)", "CURB-65 (CAP)", "CPIS / SOFA (HAP)"] },
    { title: "Microbiology", color: C.teal, items: ["Culture type & result", "Pathogen identification", "MDR / XDR status"] },
    { title: "Antimicrobial Rx", color: "7B5EA7", items: ["Drug, dose, route, DOT", "Empiric vs. definitive", "IV-to-oral switch"] },
    { title: "Guideline Adherence", color: C.gold, items: ["IDSA/ATS 2019 (CAP)", "IDSA 2016 (HAP/VAP)", "Concordance: Y/N/Partial"] },
    { title: "Clinical Outcomes", color: C.red, items: ["Cure / Failure / Death", "LOS, ICU LOS", "30-day readmission"] },
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      sl.addText(item, { x: x + 0.42, y: y + 0.56 + j * 0.7, w: 3.55, h: 0.58, fontSize: 11.5, fontFace: FONT, color: C.text });
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// ────────────────────────────────────────────────────────────────────────
// SLIDE 7 — OPERATIONAL DEFINITIONS
// ────────────────────────────────────────────────────────────────────────
{
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  slideHeader(sl, "Key Operational Definitions", "Standardized definitions applied uniformly across data collection");

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    ["HAP", "Pneumonia occurring >= 48 hours after hospital admission; not incubating at time of admission; new/worsening infiltrate + clinical signs.", C.blue],
    ["Clinical Cure", "Resolution of fever, improved respiratory parameters, radiological improvement, no antibiotic change at end of therapy.", C.teal],
    ["Treatment Failure", "Persistence or worsening of clinical, lab, or radiological signs after 72 hours of appropriate therapy requiring antibiotic escalation.", "7B5EA7"],
    ["MDR Organism", "Non-susceptibility to >= 1 agent in >= 3 antimicrobial categories (ECDC/CDC 2012 consensus definition).", C.gold],
    ["Guideline Concordance", "Empiric regimen consistent with IDSA/ATS 2019 (CAP) or IDSA 2016 (HAP) based on patient severity and risk factors.", C.teal],
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  });
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 8 — STATISTICAL ANALYSIS PLAN OVERVIEW
// ────────────────────────────────────────────────────────────────────────
{
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  slideHeader(sl, "Statistical Analysis Plan (SAP)", "Pre-specified analyses — finalized before data collection");

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  // 4 analysis blocks
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      title: "Descriptive Analysis", color: C.navy,
      lines: ["Continuous: Mean±SD or Median [IQR]", "Categorical: n (%); 95% Wilson CI", "Normality: Shapiro-Wilk / K-S test", "Table 1: SMD (not p-values)"]
    },
    {
      title: "Comparative Analysis", color: C.blue,
      lines: ["Binary: Chi-square / Fisher's exact", "Continuous: t-test / Mann-Whitney U", "Effect sizes: RR, Cohen's d, r", "Alpha = 0.05, two-tailed"]
    },
    {
      title: "Multivariable Regression", color: C.teal,
      lines: ["Binary logistic: Mortality + Tx failure", "Linear regression / Neg-binomial: LOS", "Backward elimination (p-remove = 0.10)", "AUC-ROC, H-L test, VIF, Cook's D"]
    },
    {
      title: "Survival & Sensitivity", color: "7B5EA7",
      lines: ["Kaplan-Meier: time-to-cure + mortality", "Cox PH regression (HR with 95% CI)", "Sensitivity: MI vs complete-case", "Propensity Score Matching (PSM)"]
    },
  ];
  blocks.forEach((b, i) => {
    const x = 0.35 + i * 3.25;
    addCard(sl, x, 2.1, 3.0, 4.5, C.white, b.color);
    addBand(sl, b.color, x, 2.1, 3.0, 0.5);
    sl.addText(b.title, { x: x + 0.08, y: 2.12, w: 2.85, h: 0.44, fontSize: 12, fontFace: FONT, bold: true, color: C.white, align: "center" });
    b.lines.forEach((line, j) => {
      sl.addShape(pres.ShapeType.ellipse, { x: x + 0.22, y: 2.77 + j * 0.9, w: 0.13, h: 0.13, fill: { color: b.color }, line: { color: b.color, width: 0 } });
      sl.addText(line, { x: x + 0.42, y: 2.68 + j * 0.9, w: 2.45, h: 0.8, fontSize: 10.5, fontFace: FONT, color: C.text, wrap: true });
    });
  });

  // Bottom note
  sl.addText("SAP is LOCKED before database closure. Post-hoc analyses will be clearly labelled as 'exploratory' in all publications.", {
    x: 0.35, y: 6.78, w: 12.6, h: 0.38, fontSize: 10, fontFace: FONT, color: C.red, bold: true, align: "center"
  });
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 9 — SAMPLE SIZE JUSTIFICATION
// ────────────────────────────────────────────────────────────────────────
{
  const sl = pres.addSlide();
  slideHeader(sl, "Sample Size Justification", "Power calculations and feasibility");

  // Main calculation box
  addCard(sl, 0.35, 1.28, 8.0, 4.5, C.ltblue, C.blue);
  addBand(sl, C.navy, 0.35, 1.28, 8.0, 0.5);
  sl.addText("Sample Size Calculation (OpenEpi — Two Proportions)", {
    x: 0.45, y: 1.3, w: 7.8, h: 0.44, fontSize: 13, fontFace: FONT, bold: true, color: C.white
  });

  const params = [
    ["Mortality in CAP (literature estimate)", "~8-10%"],
    ["Mortality in HAP (literature estimate)", "~25-30%"],
    ["Level of significance (alpha)", "0.05 (two-tailed)"],
    ["Statistical power (1-beta)", "80%"],
    ["Calculated minimum sample (per group)", "~90-100 patients"],
    ["Inflation factor (15% for missing data)", "+15 patients/group"],
    ["Final target sample size (per group)", "110-120 patients"],
    ["TOTAL study sample", "~220-240 patients"],
  ];
  params.forEach(([label, val], i) => {
    const y = 1.95 + i * 0.46;
    const bg = i % 2 === 0 ? "DBEAFE" : C.ltblue;
    sl.addShape(pres.ShapeType.rect, { x: 0.42, y, w: 7.85, h: 0.44, fill: { color: bg }, line: { color: bg, width: 0 } });
    sl.addText(label, { x: 0.52, y: y + 0.04, w: 5.9, h: 0.36, fontSize: 11, fontFace: FONT, color: C.text });
    sl.addText(val, { x: 6.5, y: y + 0.04, w: 1.65, h: 0.36, fontSize: 11.5, fontFace: FONT, bold: true, color: i >= 6 ? C.navy : C.blue, align: "right" });
  });

  // Feasibility note
  addCard(sl, 8.6, 1.28, 4.45, 4.5, C.white, C.teal);
  addBand(sl, C.teal, 8.6, 1.28, 4.45, 0.5);
  sl.addText("Feasibility Assessment", { x: 8.7, y: 1.3, w: 4.2, h: 0.44, fontSize: 13, fontFace: FONT, bold: true, color: C.white });
  const feasibility = [
    ["Annual admissions (est.)", "300-500 CAP/HAP cases/year"],
    ["Data availability", "Retrospective records: 2 years"],
    ["Culture positive rate", "~40-60% (estimated)"],
    ["Missing data rate", "< 15% expected"],
    ["Ethics approval", "IEC submission planned"],
    ["Data access", "Approved by HOD"],
  ];
  feasibility.forEach(([lbl, val], i) => {
    sl.addText(lbl + ":", { x: 8.7, y: 1.98 + i * 0.68, w: 4.2, h: 0.3, fontSize: 10.5, fontFace: FONT, bold: true, color: C.blue });
    sl.addText(val, { x: 8.7, y: 2.25 + i * 0.68, w: 4.2, h: 0.32, fontSize: 11, fontFace: FONT, color: C.text });
  });

  sl.addText("This sample is achievable within the 2-year retrospective data window at the study site.", {
    x: 0.35, y: 5.97, w: 12.6, h: 0.38, fontSize: 10.5, fontFace: FONT, color: C.subtext, italic: true, align: "center"
  });
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 10 — ETHICAL CONSIDERATIONS
// ────────────────────────────────────────────────────────────────────────
{
  const sl = pres.addSlide();
  slideHeader(sl, "Ethical Considerations", "Compliance with Declaration of Helsinki and ICMR guidelines");

  const ethics = [
    {
      icon: "IEC", title: "Ethics Committee Approval",
      text: "Formal approval from the Institutional Ethics Committee (IEC) / IRB will be obtained BEFORE any data extraction. Protocol will be submitted with this document.",
      color: C.navy
    },
    {
      icon: "CON", title: "Informed Consent Waiver",
      text: "As a retrospective records-based study, individual patient consent is waived. Justification will be submitted to the IEC per ICMR 2017 guidelines.",
      color: C.blue
    },
    {
      icon: "CFD", title: "Confidentiality & Anonymization",
      text: "All patient data will be de-identified using coded IDs before entry into the analysis database. No personal identifiers will be recorded.",
      color: C.teal
    },
    {
      icon: "STR", title: "Data Security",
      text: "Data stored in encrypted, password-protected institutional servers accessible only to the PI and co-investigators. Physical CRFs in locked cabinet.",
      color: "7B5EA7"
    },
    {
      icon: "COI", title: "Conflict of Interest",
      text: "This is an investigator-initiated study. No pharmaceutical company funding or sponsorship. No conflicts of interest declared by any investigator.",
      color: C.gold
    },
    {
      icon: "REG", title: "Regulatory Compliance",
      text: "Conducted per Declaration of Helsinki (2013 revision), ICMR National Ethical Guidelines for Biomedical Research (2017), and GCP guidelines.",
      color: C.teal
    },
  ];

  ethics.forEach((e, i) => {
    const col = i % 2;
    const row = Math.floor(i / 2);
    const x = col === 0 ? 0.35 : 6.85;
    const y = 1.28 + row * 2.04;
    addCard(sl, x, y, 6.2, 1.85, C.white, e.color);
    addBand(sl, e.color, x, y, 1.0, 1.85);
    sl.addText(e.icon, { x: x, y: y + 0.68, w: 1.0, h: 0.5, fontSize: 11, fontFace: FONT, bold: true, color: C.white, align: "center", charSpacing: 0.5 });
    sl.addText(e.title, { x: x + 1.1, y: y + 0.1, w: 4.95, h: 0.38, fontSize: 12.5, fontFace: FONT, bold: true, color: e.color });
    sl.addText(e.text, { x: x + 1.1, y: y + 0.5, w: 4.95, h: 1.25, fontSize: 10.5, fontFace: FONT, color: C.text, wrap: true, lineSpacingMultiple: 1.25 });
  });
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 11 — TIMELINE
// ────────────────────────────────────────────────────────────────────────
{
  const sl = pres.addSlide();
  slideHeader(sl, "Study Timeline", "24-month project plan");

  const phases = [
    { label: "Protocol & IEC Submission",   months: "Months 1-2",   color: C.navy,  pct: 10 },
    { label: "IEC Approval & Tool Finalization", months: "Months 2-4", color: C.blue, pct: 20 },
    { label: "Retrospective Data Collection",   months: "Months 5-12",  color: C.teal,  pct: 45 },
    { label: "Data Entry & Cleaning",          months: "Months 10-14", color: "7B5EA7", pct: 56 },
    { label: "Statistical Analysis",           months: "Months 14-16", color: C.gold,  pct: 66 },
    { label: "Results & Manuscript Writing",   months: "Months 16-21", color: "E07B39", pct: 79 },
    { label: "Peer Review & Submission",       months: "Months 21-24", color: C.red,   pct: 92 },
  ];

  const BAR_X = 0.4;
  const BAR_W = 12.5;
  const BAR_Y_START = 1.5;
  const BAR_H = 0.62;
  const BAR_GAP = 0.74;

  // Timeline ruler
  addBand(sl, C.ltblue, BAR_X, 1.32, BAR_W, 0.18);
  for (let m = 0; m <= 24; m += 4) {
    const x = BAR_X + (m / 24) * BAR_W;
    sl.addShape(pres.ShapeType.line, { x, y: 1.3, w: 0, h: 0.2, line: { color: C.blue, width: 1 } });
    sl.addText(`M${m}`, { x: x - 0.15, y: 1.1, w: 0.35, h: 0.22, fontSize: 8, fontFace: FONT, color: C.subtext, align: "center" });
  }

  phases.forEach((p, i) => {
    const y = BAR_Y_START + i * BAR_GAP;
    // Label
    sl.addText(p.label, { x: 0.4, y: y + 0.1, w: 3.9, h: 0.42, fontSize: 11, fontFace: FONT, color: C.text, align: "right", bold: false });
    // Gantt bar track
    sl.addShape(pres.ShapeType.rect, { x: 4.45, y: y + 0.1, w: 8.4, h: 0.42, fill: { color: "E2E8F0" }, line: { color: "E2E8F0", width: 0 } });
    // Gantt bar fill — approximate from pct
    const startFrac = (p.pct - (p.pct > 55 ? (p.pct > 65 ? (p.pct > 75 ? 30 : 20) : 10) : 0)) / 100;
    const widths = [10, 17, 30, 22, 10, 22, 12]; // approximate spans
    const startPcts = [0, 8, 16, 38, 54, 62, 79];
    const sw = (startPcts[i] / 100) * 8.4;
    const bw = (widths[i] / 100) * 8.4;
    sl.addShape(pres.ShapeType.roundRect, {
      x: 4.45 + sw, y: y + 0.1, w: Math.max(bw, 0.3), h: 0.42,
      fill: { color: p.color }, line: { color: p.color, width: 0 }, rectRadius: 0.05
    });
    sl.addText(p.months, {
      x: 4.45 + sw, y: y + 0.16, w: Math.max(bw, 0.3), h: 0.3,
      fontSize: 8.5, fontFace: FONT, color: C.white, bold: true, align: "center"
    });
  });

  sl.addText("Total study duration: 24 months  |  Manuscript submission targeted: Month 24", {
    x: 0.35, y: 7.1, w: 12.6, h: 0.28, fontSize: 9.5, fontFace: FONT, color: C.subtext, align: "center", italic: true
  });
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 12 — EXPECTED OUTCOMES & SIGNIFICANCE
// ────────────────────────────────────────────────────────────────────────
{
  const sl = pres.addSlide();
  slideHeader(sl, "Expected Outcomes & Significance", "Contributions to clinical practice and antimicrobial stewardship");

  // Left: what we expect to show
  addCard(sl, 0.35, 1.28, 5.95, 5.3, C.white, C.navy);
  addBand(sl, C.navy, 0.35, 1.28, 5.95, 0.5);
  sl.addText("ANTICIPATED FINDINGS", { x: 0.45, y: 1.3, w: 5.75, h: 0.42, fontSize: 13, fontFace: FONT, bold: true, color: C.white });
  const findings = [
    "HAP patients will show significantly higher in-hospital mortality and longer LOS compared to CAP",
    "MDR organisms will be more prevalent in HAP; Gram-negative bacilli (Pseudomonas, Klebsiella, Acinetobacter) will dominate",
    "Guideline adherence rates will be suboptimal (<70%) in both groups, especially for de-escalation practices",
    "Broad-spectrum carbapenems and glycopeptides will be over-used relative to culture-directed therapy",
    "De-escalation rates will be significantly lower in HAP, contributing to prolonged antibiotic exposure",
  ];
  findings.forEach((f, i) => {
    sl.addText(f, {
      x: 0.52, y: 1.95 + i * 0.93, w: 5.65, h: 0.82,
      fontSize: 11, fontFace: FONT, color: C.text, bullet: { type: "number", color: C.teal, startAt: i + 1 }, wrap: true
    });
  });

  // Right: significance & impact
  addCard(sl, 6.65, 1.28, 6.3, 5.3, C.white, C.teal);
  addBand(sl, C.teal, 6.65, 1.28, 6.3, 0.5);
  sl.addText("CLINICAL & ACADEMIC SIGNIFICANCE", { x: 6.75, y: 1.3, w: 6.1, h: 0.42, fontSize: 12, fontFace: FONT, bold: true, color: C.white });

  const impacts = [
    { label: "For AMS Programs", text: "Provides a local baseline for targeted antibiotic stewardship interventions" },
    { label: "For Prescribers", text: "Highlights gaps in guideline adherence and de-escalation practice" },
    { label: "For the Hospital", text: "Data to justify policy reforms: local antibiogram use, antibiotic restriction programs" },
    { label: "For Publications", text: "Targeted for indexed journals: IJCP, Pharmacotherapy, J Hosp Infect, AJHP" },
    { label: "For PharmD Practice", text: "Demonstrates the role of clinical pharmacists in infection management and outcomes" },
  ];
  impacts.forEach((imp, i) => {
    const y = 2.0 + i * 0.98;
    addCard(sl, 6.75, y, 6.1, 0.84, C.ltblue, C.line);
    sl.addText(imp.label, { x: 6.85, y: y + 0.05, w: 5.9, h: 0.32, fontSize: 10.5, fontFace: FONT, bold: true, color: C.navy });
    sl.addText(imp.text, { x: 6.85, y: y + 0.38, w: 5.9, h: 0.38, fontSize: 10.5, fontFace: FONT, color: C.text });
  });
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 13 — STUDY TEAM & BUDGET
// ────────────────────────────────────────────────────────────────────────
{
  const sl = pres.addSlide();
  slideHeader(sl, "Study Team & Budget", "Investigators and indicative resource requirements");

  // Team table
  addCard(sl, 0.35, 1.28, 7.5, 3.4, C.white, C.navy);
  addBand(sl, C.navy, 0.35, 1.28, 7.5, 0.48);
  sl.addText("STUDY TEAM", { x: 0.5, y: 1.3, w: 7.2, h: 0.4, fontSize: 13, fontFace: FONT, bold: true, color: C.white });
  sl.addTable([
    [
      { text: "Role", options: { bold: true, fill: { color: "1A3C5E" }, color: C.white, fontSize: 11, fontFace: FONT } },
      { text: "Name", options: { bold: true, fill: { color: "1A3C5E" }, color: C.white, fontSize: 11, fontFace: FONT } },
      { text: "Designation", options: { bold: true, fill: { color: "1A3C5E" }, color: C.white, fontSize: 11, fontFace: FONT } },
    ],
    ["Principal Investigator", "[Name]", "PharmD Candidate (5th Year)"],
    ["Guide / Supervisor", "[Name]", "[Designation, Dept.]"],
    ["Co-Investigator", "[Name]", "[Designation, Dept.]"],
    ["Statistician", "[Name]", "[Designation]"],
    ["Microbiologist Collaborator", "[Name]", "[Designation, Microbiology Dept.]"],
  ], {
    x: 0.42, y: 1.86, w: 7.3,
    border: { pt: 0.5, color: "CBD5E0" },
    fontSize: 11, fontFace: FONT, color: C.text,
    rowH: 0.44, fill: { color: "F7FAFC" }
  });

  // Budget table
  addCard(sl, 8.1, 1.28, 4.85, 3.4, C.white, C.gold);
  addBand(sl, C.gold, 8.1, 1.28, 4.85, 0.48);
  sl.addText("INDICATIVE BUDGET", { x: 8.2, y: 1.3, w: 4.6, h: 0.4, fontSize: 13, fontFace: FONT, bold: true, color: C.white });
  sl.addTable([
    [
      { text: "Item", options: { bold: true, fill: { color: "B7791F" }, color: C.white, fontSize: 10.5, fontFace: FONT } },
      { text: "Est. Cost", options: { bold: true, fill: { color: "B7791F" }, color: C.white, fontSize: 10.5, fontFace: FONT } },
    ],
    ["Stationery & printing", "INR 2,000-5,000"],
    ["Statistical software", "INR 0 (institutional)"],
    ["Publication / OA fee", "INR 10,000-50,000"],
    ["Miscellaneous", "INR 2,000-5,000"],
    [{ text: "TOTAL", options: { bold: true } }, { text: "~INR 14,000-65,000", options: { bold: true } }],
  ], {
    x: 8.18, y: 1.86, w: 4.7,
    border: { pt: 0.5, color: "CBD5E0" },
    fontSize: 11, fontFace: FONT, color: C.text,
    rowH: 0.44, fill: { color: "FFFBEB" }
  });

  // Sponsorship note
  addCard(sl, 0.35, 4.85, 12.6, 0.8, "FFF5F5", C.red);
  sl.addText("Funding Declaration: This is a fully INVESTIGATOR-INITIATED study. No external funding from pharmaceutical companies or device manufacturers. All costs will be borne by the investigators personally.", {
    x: 0.5, y: 4.96, w: 12.3, h: 0.6, fontSize: 11, fontFace: FONT, color: C.red, bold: true, align: "center"
  });

  // References
  addCard(sl, 0.35, 5.85, 12.6, 1.3, C.ltgray, C.line);
  sl.addText("Key References", { x: 0.5, y: 5.9, w: 12.3, h: 0.32, fontSize: 10, fontFace: FONT, bold: true, color: C.navy });
  sl.addText(
    "1. Mandell LA et al. IDSA/ATS CAP Guidelines. Clin Infect Dis. 2007.  |  2. Kalil AC et al. IDSA HAP/VAP Guidelines. Clin Infect Dis. 2016.  |  3. Nasr R et al. Antibiotics. 2026 (PMID: 42353675).\n4. Ablakimova N et al. J Hosp Infect. 2026 (PMID: 41534745).  |  5. Ablakimova N et al. Eur J Clin Microbiol Infect Dis. 2025 (PMID: 40202602).",
    { x: 0.5, y: 6.22, w: 12.3, h: 0.82, fontSize: 8.5, fontFace: FONT, color: C.subtext, lineSpacingMultiple: 1.4 }
  );
}

// ────────────────────────────────────────────────────────────────────────
// SLIDE 14 — CLOSING / THANK YOU
// ────────────────────────────────────────────────────────────────────────
{
  const sl = pres.addSlide();
  sl.background = { color: C.navy };

  addBand(sl, C.teal, 0, 0, 13.3, 0.18);
  addBand(sl, C.teal, 0, 7.32, 13.3, 0.18);

  // Centered thank you
  sl.addText("Thank You", {
    x: 1.5, y: 1.4, w: 10.3, h: 1.4,
    fontSize: 54, fontFace: FONT, bold: true, color: C.white, align: "center"
  });
  sl.addShape(pres.ShapeType.line, { x: 3.5, y: 2.9, w: 6.3, h: 0, line: { color: C.teal, width: 3 } });
  sl.addText("We invite the committee's questions, comments, and suggestions.", {
    x: 1.5, y: 3.1, w: 10.3, h: 0.6,
    fontSize: 17, fontFace: FONT, color: "9EC8E8", align: "center", italic: true
  });

  // Contact info box
  sl.addShape(pres.ShapeType.roundRect, {
    x: 3.2, y: 3.95, w: 6.9, h: 2.2,
    fill: { color: "0D2B4E", transparency: 30 }, line: { color: C.teal, width: 1.5 }, rectRadius: 0.12
  });
  sl.addText([
    { text: "Principal Investigator: ", options: { bold: true, color: C.teal } },
    { text: "[Name], PharmD Candidate\n", options: { color: C.white } },
    { text: "Institution: ", options: { bold: true, color: C.teal } },
    { text: "[Name of College / Hospital]\n", options: { color: C.white } },
    { text: "Department: ", options: { bold: true, color: C.teal } },
    { text: "Clinical Pharmacy / Pharmacy Practice\n", options: { color: C.white } },
    { text: "Email: ", options: { bold: true, color: C.teal } },
    { text: "[email@institution.edu]", options: { color: C.white } },
  ], { x: 3.4, y: 4.1, w: 6.5, h: 1.9, fontSize: 13, fontFace: FONT, lineSpacingMultiple: 1.4 });

  // Protocol document note
  sl.addText("Companion Documents: Full Research Protocol (v1.0)  |  Statistical Analysis Plan (SAP v1.0)  |  Draft CRF  — available on request", {
    x: 1.0, y: 6.42, w: 11.3, h: 0.45,
    fontSize: 10.5, fontFace: FONT, color: "7BBDE0", align: "center", italic: true
  });
}

// ────────────────────────────────────────────────────────────────────────
// WRITE FILE
// ────────────────────────────────────────────────────────────────────────
pres.writeFile({ fileName: "/home/daytona/workspace/cap-hap-protocol/CAP_vs_HAP_Protocol_Presentation.pptx" })
  .then(() => console.log("SUCCESS: PPTX written."))
  .catch(err => { console.error("ERROR:", err); process.exit(1); });