Prakriti migraine Ayurveda

Deha Prakriti assessment migraine cross sectional study MD thesis Ayurveda methodology

Prakriti body constitution Ayurveda assessment validation

migraine pathophysiology neurological diagnosis criteria

https://pmc.ncbi.nlm.nih.gov/articles/PMC12631390

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Prakriti body constitution Ayurveda disease susceptibility

migraine ICHD-3 prevalence India epidemiology

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      // ── TITLE PAGE ──────────────────────────────────────────────────────
      centerPara([bold('ASSESSMENT OF DEHA PRAKRITI IN PATIENTS OF', 28)], 80),
      centerPara([bold('MIGRAINE - A CROSS SECTIONAL STUDY', 28)], 240),

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      centerPara([normal('Synopsis submitted as partial fulfillment for the degree of', 24)], 80),
      emptyLine(),
      centerPara([bold('Ayurveda Vachaspati (MD Ayurveda)', 24)], 80),
      emptyLine(),
      centerPara([bold('Speciality - Rog Nidan Evum Vikriti Vigyan', 24)], 240),

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      centerPara([bold('Scholar', 24)], 40),
      centerPara([bold('[Scholar\'s Name]', 24)], 240),

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      centerPara([bold('[Guide\'s Name]', 24)], 40),
      centerPara([bold('[Guide\'s Qualification and Designation]', 24)], 240),

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      centerPara([bold('Swaminarayan University', 26)], 60),
      centerPara([bold('Faculty of Ayurveda', 26)], 60),
      centerPara([bold('Shree Swaminarayan Ayurvedic College', 26)], 60),
      centerPara([bold('Department of Rog Nidan Evum Vikriti Vigyan', 24)], 60),
      centerPara([bold('Kalol, Gandhinagar, Gujarat - 382 725', 24)], 80),

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      // ── 1. INTRODUCTION ─────────────────────────────────────────────────
      headingPara('1. Introduction'),

      justPara([
        bold('Background: ', 24),
        normal('Deha Prakriti is one of the most fundamental concepts in Ayurveda, representing the individual\'s unique psycho-somatic constitution determined at the time of conception. It is defined in classical texts as the state of predominance of one or more Doshas (Vata, Pitta, Kapha) in the body from birth to death. Charaka Samhita (Vimana Sthana 8/95-98), Ashtanga Hridayam (Sharira Sthana 3), and Sushruta Samhita (Sharira Sthana 4) provide elaborate descriptions of seven Prakriti types: Vata, Pitta, Kapha, Vata-Pitta, Vata-Kapha, Pitta-Kapha, and Sama Prakriti. Prakriti determines not only physical and physiological characteristics but also the individual\'s susceptibility to specific diseases, disease prognosis, and response to treatment.', 24)
      ]),

      justPara([
        bold('Migraine in Modern Context: ', 24),
        normal('Migraine is a chronic, episodic, neurovascular disorder characterized by recurrent attacks of moderate to severe unilateral headache, often accompanied by nausea, vomiting, photophobia, and phonophobia. According to the World Health Organization (WHO), migraine is ranked as the third most prevalent and the second most disabling neurological disorder globally. It affects approximately 14.7% of the world population (about 1 in 7 people), with a female-to-male ratio of 3:1, predominantly affecting individuals in the productive age group of 25-55 years. In India, the prevalence of migraine is reported at 25.4 per 1000 population.', 24)
      ]),

      justPara([
        bold('Ayurvedic Correlation: ', 24),
        normal('In Ayurvedic classics, Migraine closely correlates with ', 24),
        italic('Ardhavabhedaka ', 24),
        normal('(half-sided piercing headache), described in Madhava Nidana (Chapter 62), Charaka Samhita (Siddhi Sthana 9), and Ashtanga Hridayam (Uttara Tantra 23). The classical description of ', 24),
        italic('Ardhavabhedaka ', 24),
        normal('includes unilateral throbbing or piercing headache, pain in the temporal region, aggravation by exertion, and association with nausea - features that closely mirror modern ICHD-3 diagnostic criteria for migraine. The primary Doshas involved are Vata and Pitta, suggesting that individuals with Vata-Pitta Prakriti may have inherent susceptibility towards migraine.', 24)
      ]),

      justPara([
        bold('Rationale: ', 24),
        normal('The concept of Prakriti as a predictor of disease susceptibility (', 24),
        italic('Vyadhi Kshamatva', 24),
        normal(') is well established in Ayurvedic science. Understanding the predominant Deha Prakriti in migraine patients will help establish the Doshika basis of this disease, facilitating Prakriti-based preventive advice, individualized treatment planning, and early identification of at-risk individuals. Despite the clinical importance of this correlation, there is a paucity of observational studies specifically assessing Deha Prakriti in diagnosed migraine patients using validated tools.', 24)
      ]),

      justPara([
        bold('Research Scope and Limitations: ', 24),
        normal('This study is limited to patients attending the OPD/IPD of Shree Swaminarayan Ayurvedic College, Kalol, diagnosed with Migraine as per ICHD-3 criteria and ', 24),
        italic('Ardhavabhedaka', 24),
        normal(' as per classical Ayurvedic criteria. Being a cross-sectional design, temporal relationships and causality cannot be established. Prakriti assessment is based on a validated questionnaire tool which involves subjective reporting; hence examiner training and standardization will be maintained throughout the study.', 24)
      ]),

      // ── 2. REVIEW OF PREVIOUS RESEARCH ──────────────────────────────────
      headingPara('2. Review of Previous Research Works'),

      justPara([bold('A. Ayurvedic Literary Review', 24)]),

      bulletPara([
        bold('Charaka Samhita (Vimana Sthana 8/95-98): ', 22),
        normal('Acharya Charaka describes the seven types of Deha Prakriti and their characteristic physical, physiological, and psychological features in detail. He emphasizes that Prakriti-based prediction of disease susceptibility is a cornerstone of Ayurvedic preventive medicine.', 22)
      ]),

      bulletPara([
        bold('Ashtanga Hridayam (Sharira Sthana 3 - Prakriti Vichaya): ', 22),
        normal('Acharya Vagbhata elaborates on Prakriti determination from the foetal stage, including Doshika predominance at the time of conception (Shukra-Shonita Samyoga), season (Rutu), uterine environment (Kshetra), nutrition (Ambu), and genetic factors (Beeja). He describes the distinctive signs and symptoms of each Prakriti type.', 22)
      ]),

      bulletPara([
        bold('Madhava Nidana (Chapter 62 - Shiroroga Nidana): ', 22),
        normal('Acharya Madhavakara classifies head disorders and describes ', 22),
        italic('Ardhavabhedaka ', 22),
        normal('as a distinct disease with involvement of Vata and Pitta Doshas. The cardinal feature is severe half-sided headache with stabbing or piercing quality, occurring in episodes.', 22)
      ]),

      bulletPara([
        bold('Charaka Samhita (Siddhi Sthana 9): ', 22),
        normal('The treatment principles for Shiroroga including Ardhavabhedaka are described with emphasis on Vatanulomana and Pittashamana therapy, further confirming the Vata-Pitta dominance in this condition.', 22)
      ]),

      justPara([bold('B. Modern Research Studies on Prakriti', 24)]),

      bulletPara([
        bold('ITRA, Jamnagar: ', 22),
        normal('Several studies conducted at IPGT & RA, Gujarat Ayurved University, Jamnagar have validated Prakriti assessment questionnaires. Studies by Vd. Thakkar J. et al. (AYU Journal) demonstrated significant correlations between Prakriti and physiological parameters including skin hydration, metabolic rate, and bowel habits.', 22)
      ]),

      bulletPara([
        bold('NIA, Jaipur: ', 22),
        normal('The National Institute of Ayurveda, Jaipur, in collaboration with CCRAS, has developed and validated standardized Prakriti Assessment Questionnaires (PAQ) used widely in academic and clinical research. Studies have documented the reliability and construct validity of the CCRAS PAQ tool.', 22)
      ]),

      bulletPara([
        bold('CSIR-IGIB, New Delhi (Prasher B. et al., 2008): ', 22),
        normal('This landmark genomic study published in Journal of Translational Medicine (PMID: 18782426) demonstrated significant differences in whole genome expression and biochemical parameters across Vata, Pitta, and Kapha Prakriti types, providing molecular evidence for the biological basis of Prakriti classification.', 22)
      ]),

      bulletPara([
        bold('BHU, Varanasi: ', 22),
        normal('Studies from the Institute of Medical Sciences, BHU have assessed Prakriti in various disease conditions including metabolic disorders, cardiovascular diseases, and psychological conditions, demonstrating the clinical utility of Prakriti-based disease prediction.', 22)
      ]),

      justPara([bold('C. Studies on Migraine / Ardhavabhedaka', 24)]),

      bulletPara([
        bold('Chowdhury D. et al. (J Headache Pain, 2024, PMID: 38943062): ', 22),
        normal('A large population-based cross-sectional study from Delhi-NCR reported headache prevalence with demographic associations in the Indian population, highlighting the significant burden of migraine as a public health concern.', 22)
      ]),

      bulletPara([
        bold('PMC Review on Ayurveda for Migraine (PMC9638656, 2022): ', 22),
        normal('A narrative review of clinical evidence on Ayurvedic management of migraine confirmed the beneficial role of Ayurvedic approaches. The review noted lack of studies correlating Prakriti with migraine as a significant research gap.', 22)
      ]),

      bulletPara([
        bold('PMC Review on Prakriti Assessment Tools (PMC12631390, 2025): ', 22),
        normal('A systematic critical review of Prakriti Assessment Tools (PATs) noted that most tools were validated using observational cross-sectional designs. It recommended that future studies use PATs in clinical disease populations to establish clinical correlations and disease predictability.', 22)
      ]),

      // ── 3. NEED OF STUDY ────────────────────────────────────────────────
      headingPara('3. Relevance of Present Study / Need of the Study'),

      bulletPara([normal('Migraine is a significantly disabling neurological condition with high prevalence in India (approximately 25 per 1000 population), particularly affecting women in the reproductive age group. Despite its burden, it remains under-diagnosed and under-treated in primary care settings.', 22)]),

      bulletPara([normal('Ayurveda offers a unique framework for understanding disease through individual constitutional analysis (Deha Prakriti). Identifying the predominant Prakriti in migraine patients can help establish the Doshika basis, support early identification of susceptible individuals, guide Prakriti-specific preventive advice, and personalize treatment.', 22)]),

      bulletPara([normal('Classical texts identify Ardhavabhedaka (correlate of migraine) as primarily a Vata-Pitta disorder, but there is no standardized, validated observational study from this institution or region that systematically assesses Deha Prakriti using a validated questionnaire in a defined group of migraine patients.', 22)]),

      bulletPara([normal('Rog Nidan evum Vikriti Vigyan, as a subject, emphasizes understanding the pathological basis of disease through Ayurvedic diagnostic parameters. Prakriti-disease correlation studies are a core mandate of this department, making this study academically and clinically relevant.', 22)]),

      bulletPara([normal('This study will generate local epidemiological data on Prakriti distribution in migraine patients from the Gandhinagar-Kalol region of Gujarat, contributing to the evidence base for Ayurvedic personalized medicine.', 22)]),

      // ── 4. RESEARCH QUESTION ─────────────────────────────────────────────
      headingPara('4. Research Question'),

      justPara([normal('What is the distribution of Deha Prakriti among patients diagnosed with Migraine (Ardhavabhedaka), and is there a statistically significant predominance of any particular Prakriti type - especially Vata-Pitta Prakriti - in this patient population?', 24)]),

      // ── 5. HYPOTHESES ────────────────────────────────────────────────────
      headingPara('5. Null Hypothesis (H\u2080)'),

      justPara([normal('There is no statistically significant association between Deha Prakriti and the occurrence of Migraine (Ardhavabhedaka). The distribution of Prakriti types in patients with migraine does not differ significantly from the expected distribution in the general population.', 24)]),

      headingPara('Alternative Hypothesis (H\u2081)'),

      justPara([normal('Vata-Pitta Prakriti is significantly predominant among patients diagnosed with Migraine (Ardhavabhedaka) as compared to other Prakriti types, indicating a statistically significant association between Vata-Pitta constitution and migraine susceptibility.', 24)]),

      // ── 6. AIMS AND OBJECTIVES ───────────────────────────────────────────
      headingPara('6. Aims and Objectives'),

      justPara([bold('Aim:', 24)]),
      justPara([normal('To assess and document Deha Prakriti in patients of Migraine attending the OPD/IPD of Shree Swaminarayan Ayurvedic College, Kalol, and to study its correlation with the clinical features and disability burden of migraine.', 24)]),

      emptyLine(),
      justPara([bold('Objectives:', 24)]),

      bulletPara([bold('Primary Objective: ', 22), normal('To assess Deha Prakriti using a validated Prakriti Assessment Questionnaire (CCRAS PAQ) in patients diagnosed with Migraine (as per ICHD-3 criteria).', 22)]),

      bulletPara([bold('Secondary Objectives:', 22)]),
      bulletPara([normal('To study the distribution and predominance of Prakriti types (Vata, Pitta, Kapha, Vata-Pitta, Vata-Kapha, Pitta-Kapha, Sama) among migraine patients.', 22)], 1),
      bulletPara([normal('To correlate Deha Prakriti with clinical features of migraine: frequency of attacks per month, duration of each attack, pain severity (VAS score), laterality, presence of aura, and associated symptoms.', 22)], 1),
      bulletPara([normal('To correlate Deha Prakriti with migraine-related disability as assessed by MIDAS (Migraine Disability Assessment Score).', 22)], 1),
      bulletPara([normal('To study the demographic distribution (age, sex, occupation) of migraine patients in relation to their Prakriti.', 22)], 1),
      bulletPara([normal('To assess the Nidana Panchaka (Nidana, Purvarupa, Rupa, Upashaya-Anupashaya, Samprapti) of Ardhavabhedaka in study patients from an Ayurvedic perspective.', 22)], 1),

      // ── 7. EXPECTED OUTCOMES ─────────────────────────────────────────────
      headingPara('7. Expected Outcomes'),

      justPara([bold('Primary Outcome:', 24)]),
      bulletPara([normal('Identification of the predominant Deha Prakriti type among patients of Migraine. It is hypothesized that Vata-Pitta Prakriti will be the most prevalent constitutional type in this patient group, consistent with the classical Ayurvedic description of Ardhavabhedaka as a Vata-Pitta disorder.', 22)]),

      emptyLine(),
      justPara([bold('Secondary Outcomes:', 24)]),
      bulletPara([normal('Establishment of a statistically significant correlation between specific Prakriti types and the frequency, severity, duration, and disability burden of migraine attacks.', 22)]),
      bulletPara([normal('Generation of a Nidana Panchaka profile for Ardhavabhedaka patients from this geographic region, useful for future clinical and epidemiological research.', 22)]),
      bulletPara([normal('Development of a standardized observational data set from SSAC, Kalol, useful as reference for future interventional studies on Prakriti-based management of migraine.', 22)]),
      bulletPara([normal('Identification of demographic risk factors associated with migraine in relation to Prakriti, enabling targeted preventive counseling.', 22)]),

      // ── 8. STUDY DESIGN ──────────────────────────────────────────────────
      headingPara('8. Study Design'),

      buildStudyDesignTable(),
      emptyLine(),

      // ── 9. ETHICAL CONSIDERATIONS ────────────────────────────────────────
      headingPara('9. Ethical Considerations'),

      justPara([
        bold('IEC Approval: ', 24),
        normal('The clinical study will be started only after getting the clearance from IEC (Institutional Ethics Committee), SSAC, Kalol, Gandhinagar. All protocols will strictly adhere to ICMR 2017 Ethical Guidelines for Biomedical and Health Research involving Human Participants.', 24)
      ]),

      justPara([
        bold('Written Informed Consent: ', 24),
        normal('Written Informed Consent of all the patients will be taken prior to their registration in the present study. The consent form will be available in English, Hindi, and Gujarati. Patients will be clearly explained the purpose, procedure, risks, benefits, and their right to withdraw at any time without affecting their treatment.', 24)
      ]),

      justPara([
        bold('CTRI Registration: ', 24),
        normal('The present clinical study will be registered in CTRI (Clinical Trials Registry, India) before commencing data collection. The CTRI registration number will be incorporated in the final thesis.', 24)
      ]),

      justPara([
        bold('Confidentiality: ', 24),
        normal('All patient data will be anonymized and stored securely. Personal identifiers will not be used in any publication or report arising from this study.', 24)
      ]),

      // ── 10. SELECTION CRITERIA ───────────────────────────────────────────
      headingPara('10. Selection Criteria of Patients'),

      justPara([boldUnderline('Diagnostic Criteria:', 24)]),
      bulletPara([
        bold('Modern Diagnosis - ICHD-3 Criteria (2018): ', 22),
        normal('At least 5 attacks fulfilling criteria for Migraine Without Aura: headache lasting 4-72 hours (untreated), with at least 2 of 4 characteristics (unilateral, pulsating, moderate to severe intensity, aggravated by routine activity) AND at least 1 associated symptom (nausea/vomiting OR photophobia AND phonophobia).', 22)
      ]),
      bulletPara([
        bold('Ayurvedic Diagnosis - Ardhavabhedaka: ', 22),
        normal('Based on classical criteria from Madhava Nidana Chapter 62: unilateral or half-sided headache, stabbing or piercing in quality (Ardhavabhedaka Vedana), episodic in nature, associated with nausea, aggravation by Vata-Pittaprakopaka Nidana. Nidana Panchaka will be documented for each patient.', 22)
      ]),

      emptyLine(),
      justPara([boldUnderline('Inclusion Criteria:', 24)]),
      bulletPara([normal('Patients clinically diagnosed with Migraine as per ICHD-3 criteria (minimum 5 lifetime attacks).', 22)]),
      bulletPara([normal('Age between 18 to 60 years.', 22)]),
      bulletPara([normal('Both male and female patients.', 22)]),
      bulletPara([normal('Patients attending OPD/IPD of SSAC, Kalol.', 22)]),
      bulletPara([normal('Patients willing to give written informed consent.', 22)]),
      bulletPara([normal('Patients able to understand and respond to the Prakriti Assessment Questionnaire (in Hindi or Gujarati).', 22)]),

      emptyLine(),
      justPara([boldUnderline('Exclusion Criteria:', 24)]),
      bulletPara([normal('Secondary headache disorders (headache attributable to intracranial pathology, hypertension, infections, trauma, or systemic illness).', 22)]),
      bulletPara([normal('Patients with chronic daily headache (>15 headache days/month for >3 months), including medication overuse headache.', 22)]),
      bulletPara([normal('Known neurological disorders: epilepsy, stroke, space-occupying lesion, meningitis.', 22)]),
      bulletPara([normal('Pregnant and lactating women.', 22)]),
      bulletPara([normal('Patients on long-term corticosteroids, immunosuppressants, or hormonal therapy (may alter Prakriti assessment).', 22)]),
      bulletPara([normal('Major psychiatric illness (Schizophrenia, Bipolar disorder, Severe depression) that may affect questionnaire reliability.', 22)]),
      bulletPara([normal('Patients who have undergone major surgery or have serious systemic illness (malignancy, renal failure, hepatic failure, severe cardiac disease) within last 6 months.', 22)]),
      bulletPara([normal('Age below 18 or above 60 years.', 22)]),
      bulletPara([normal('Patients not willing to give consent.', 22)]),

      // ── 11. ASSESSMENT TOOLS ─────────────────────────────────────────────
      headingPara('11. Assessment Parameters and Criteria'),

      justPara([boldUnderline('A. Prakriti Assessment:', 24)]),
      justPara([normal('Deha Prakriti will be assessed using the CCRAS (Central Council for Research in Ayurvedic Sciences, Ministry of AYUSH, Government of India) validated Prakriti Assessment Questionnaire (PAQ). This tool evaluates:', 24)]),
      bulletPara([bold('Sharira Lakshanas (Physical traits): ', 22), normal('Body frame, skin texture, complexion, hair quality, nail texture, eye characteristics, teeth, voice quality.', 22)]),
      bulletPara([bold('Kriya Lakshanas (Physiological traits): ', 22), normal('Appetite (Agni), digestion, sweating pattern, sleep quality and duration, bowel habits, thirst, tolerance to heat and cold, physical endurance, gait.', 22)]),
      bulletPara([bold('Manasika Lakshanas (Psychological traits): ', 22), normal('Memory type (immediate/long-term), emotional temperament, decision-making, anxiety, adaptability, speech pattern.', 22)]),

      justPara([normal('Prakriti will be classified into 7 types. The classification will be based on the cumulative score of the PAQ. Inter-rater reliability will be assessed by a second trained examiner on 10% of randomly selected cases.', 24)]),

      emptyLine(),
      justPara([boldUnderline('B. Migraine Assessment:', 24)]),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [bold('Assessment Tool', 22)] })], borders: cellBorders(), shading: { type: ShadingType.SOLID, color: 'D9E1F2' } }),
            new TableCell({ children: [new Paragraph({ children: [bold('Parameter Assessed', 22)] })], borders: cellBorders(), shading: { type: ShadingType.SOLID, color: 'D9E1F2' } }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('ICHD-3 Criteria', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Diagnosis confirmation', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('VAS (Visual Analogue Scale)', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Headache pain intensity (0-10 scale)', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('MIDAS Score', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Migraine-related disability (Grade I-IV)', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Migraine Attack Diary', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Frequency, duration, triggers, aura, associated symptoms', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Nidana Panchaka Assessment', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Nidana, Purvarupa, Rupa, Upashaya-Anupashaya, Samprapti', 22)] })], borders: cellBorders() }),
          ]}),
        ]
      }),

      emptyLine(),

      // ── 12. DRUG SELECTION / PHARMACOGNOSY / PHARMA ──────────────────────
      headingPara('12. Drug/Procedure Selection'),
      justPara([normal('Not Applicable. This is an observational cross-sectional study. No drug, formulation, or therapeutic procedure will be administered to the study participants. The study involves only clinical assessment, questionnaire administration, and documentation.', 24)]),

      headingPara('Pharmacognostical Study'),
      justPara([normal('Not Applicable.', 24)]),

      headingPara('Pharmaceutical Study'),
      justPara([normal('Not Applicable.', 24)]),

      headingPara('Grouping and Posology'),
      justPara([normal('Not Applicable. There is one study group consisting of 100 patients diagnosed with Migraine. No grouping or drug posology is involved.', 24)]),

      headingPara('Follow-up'),
      justPara([normal('Not Applicable. This is a cross-sectional study. Patients will be assessed at a single time point (at the time of enrollment). No follow-up visits are scheduled.', 24)]),

      // ── 13. INVESTIGATIONS ────────────────────────────────────────────────
      headingPara('13. Investigations'),

      justPara([normal('The following investigations may be ordered, if clinically indicated, primarily to rule out secondary causes of headache (Exclusion Criteria) and are not study outcome measures:', 24)]),
      bulletPara([normal('Complete Blood Count (CBC) - to rule out anaemia or infection', 22)]),
      bulletPara([normal('Blood Pressure measurement', 22)]),
      bulletPara([normal('Random Blood Glucose - to rule out hypoglycaemia as a headache trigger', 22)]),
      bulletPara([normal('CT Scan / MRI Brain - if clinically indicated (red flag symptoms) to rule out secondary headache', 22)]),
      bulletPara([normal('Refractive error assessment (if visual aura or eye-strain suspected)', 22)]),

      justPara([normal('Note: These investigations are purely for clinical screening to confirm eligibility. No specific laboratory parameters are being measured as outcome indicators in this study.', 24)]),

      // ── 14. STATISTICAL ANALYSIS ──────────────────────────────────────────
      headingPara('14. Statistical Analysis'),

      justPara([normal('All data will be entered in Microsoft Excel and analyzed using SPSS Version 20.0 or R Software. The following statistical methods will be applied:', 24)]),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [bold('Analysis', 22)] })], borders: cellBorders(), shading: { type: ShadingType.SOLID, color: 'D9E1F2' } }),
            new TableCell({ children: [new Paragraph({ children: [bold('Statistical Method', 22)] })], borders: cellBorders(), shading: { type: ShadingType.SOLID, color: 'D9E1F2' } }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Descriptive statistics (age, sex, clinical features)', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Mean ± SD for continuous variables; Frequency and percentage for categorical variables', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Prakriti type distribution', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Frequency distribution table, Pie chart, Bar diagram', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Prakriti vs Sex', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Chi-square test (χ²)', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Prakriti vs Age group', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Kruskal-Wallis Test (non-parametric ANOVA)', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Prakriti vs MIDAS Score', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Kruskal-Wallis Test with post-hoc Dunn\'s Test', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Prakriti vs Attack Frequency / Duration / VAS', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Kruskal-Wallis Test', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Prakriti vs Triggers', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('Chi-square / Fisher\'s Exact Test', 22)] })], borders: cellBorders() }),
          ]}),
          new TableRow({ children: [
            new TableCell({ children: [new Paragraph({ children: [normal('Level of significance', 22)] })], borders: cellBorders() }),
            new TableCell({ children: [new Paragraph({ children: [normal('p < 0.05 (two-tailed)', 22)] })], borders: cellBorders() }),
          ]}),
        ]
      }),

      emptyLine(),
      justPara([italic('Sample Size Calculation: Using the formula n = Z²pq/d², with Z = 1.96, expected prevalence of Vata-Pitta Prakriti p = 0.60, q = 0.40, and allowable error d = 0.10, the minimum required sample size is n ≈ 92. To compensate for incomplete data and dropouts, the sample size has been set at 100 patients.', 22)]),

      // ── 15. COLLABORATION ─────────────────────────────────────────────────
      headingPara('15. Collaboration with Other Departments'),

      bulletPara([bold('Department of Rog Nidan Evum Vikriti Vigyan, SSAC, Kalol, Gandhinagar ', 22), normal('(Principal Department)', 22)]),
      bulletPara([bold('Department of Kayachikitsa, SSAC, Kalol, Gandhinagar ', 22), normal('- For cross-referral of migraine patients attending the Kayachikitsa OPD and confirmation of diagnosis', 22)]),
      bulletPara([bold('Department of Panchakarma, SSAC, Kalol, Gandhinagar ', 22), normal('- For cross-referral of Shiroroga patients and Prakriti-based clinical inputs', 22)]),
      bulletPara([bold('Pathology Laboratory, SSAC, Kalol, Gandhinagar ', 22), normal('- For any routine haematological investigations required for exclusion criteria', 22)]),
      bulletPara([bold('Department of Manas Roga (Psychiatry), SSAC, Kalol ', 22), normal('- For screening and exclusion of major psychiatric conditions', 22)]),

      // ── 16. ADR REPORTING ─────────────────────────────────────────────────
      headingPara('16. Reporting of Adverse Drug Reactions (ADR)'),

      justPara([normal('As this is a purely observational study with no drug or intervention, adverse drug reactions are not expected. However, if any unexpected adverse event or discomfort is experienced by a study participant during the assessment process, it will be promptly reported to the ADR cell (Pharmacovigilance cell) of SSAC, Kalol, Gandhinagar, and appropriate medical care will be provided. All participants will be informed of their right to withdraw from the study at any time without consequence to their treatment.', 24)]),

      // ── 17. REFERENCES ────────────────────────────────────────────────────
      headingPara('17. References'),

      justPara([bold('Classical References:', 24)]),
      bulletPara([normal('Agnivesha. Charaka Samhita (with Chakrapanidatta\'s Ayurveda Dipika commentary), edited by Yadavji Trikamji Acharya. Vimana Sthana 8/95-98. Reprint. Varanasi: Chaukhamba Sanskrit Pratishthana; 2016.', 22)]),
      bulletPara([normal('Vagbhata. Ashtanga Hridayam (with Arundatta\'s Sarvangasundara and Hemadri\'s commentary), edited by Anna Moreshwar Kunte. Sharira Sthana 3/83-112. Reprint. Varanasi: Krishnadas Academy; 2012.', 22)]),
      bulletPara([normal('Sushruta. Sushruta Samhita (with Dalhana\'s Nibandhasangraha commentary), edited by Yadavji Trikamji Acharya. Sharira Sthana 4/62-79. Varanasi: Chaukhamba Surbharati Prakashan; 2014.', 22)]),
      bulletPara([normal('Madhavakara. Madhava Nidana (Rogavinischaya) with Madhukosha commentary, edited by Yadavji Trikamji Acharya. Chapter 62 (Shiroroga). Varanasi: Chaukhamba Sanskrit Pratishthana; 2010.', 22)]),
      bulletPara([normal('Vagbhata. Ashtanga Hridayam. Uttara Tantra 23/1-8 (Shiroroga Pratishedha). Varanasi: Krishnadas Academy; 2012.', 22)]),

      emptyLine(),
      justPara([bold('Modern References (Vancouver Format):', 24)]),
      bulletPara([normal('Headache Classification Committee of the International Headache Society (IHS). The International Classification of Headache Disorders, 3rd edition. Cephalalgia. 2018;38(1):1-211.', 22)]),
      bulletPara([normal('Prasher B, Negi S, Aggarwal S, et al. Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda. J Transl Med. 2008;6:48. PMID: 18782426.', 22)]),
      bulletPara([normal('Rotti H, Guruprasad KP, Nayak J, et al. Immunophenotyping of normal individuals classified on the basis of human dosha prakriti. J Ayurveda Integr Med. 2014;5(1):43-9. PMID: 24812475.', 22)]),
      bulletPara([normal('Tiwari P, Kutum R, Sethi T, et al. Recapitulation of Ayurveda constitution types by machine learning of phenotypic traits. PLoS One. 2017;12(10):e0185380. PMID: 28981546.', 22)]),
      bulletPara([normal('Chowdhury D, Krishnan A, Duggal A, et al. Headache prevalence and demographic associations in the Delhi and National Capital Region of India: estimates from a cross-sectional nationwide population-based study. J Headache Pain. 2024;25(1):91. PMID: 38943062.', 22)]),
      bulletPara([normal('Datta S, Bhattacharyya D, Mahadevan B, et al. Ayurveda for management of migraine: A narrative review of clinical evidence. J Ayurveda Integr Med. 2022;13(4):100637. PMID (PMC9638656).', 22)]),
      bulletPara([normal('Kumar A, Bhat GS, Gunasekaran DM, et al. The Treatment Profile of Migraine in India: A Glimpse of the Real World Scenario. Neurol India. 2025;73(5). PMID: 40946284.', 22)]),
      bulletPara([normal('CCRAS (Central Council for Research in Ayurvedic Sciences). Prakriti Assessment Questionnaire. Ministry of AYUSH, Government of India. New Delhi; 2016.', 22)]),
      bulletPara([normal('Indian Council of Medical Research (ICMR). National Ethical Guidelines for Biomedical and Health Research Involving Human Participants. New Delhi: ICMR; 2017.', 22)]),
      bulletPara([normal('Prakriti Assessment Tools - A Critical Review. PMC12631390. J Ayurveda Integr Med. 2025.', 22)]),

      // ── 18. GANTT CHART ───────────────────────────────────────────────────
      headingPara('18. Plan of Study / Tentative Timeline (Gantt Chart)'),

      justPara([italic('Timeline: July 2025 to June 2027 (Final Thesis Submission)', 22)]),
      emptyLine(),

      buildGanttTable(),
      emptyLine(),

      // ── 19. DECLARATION ───────────────────────────────────────────────────
      headingPara('Declaration'),

      justPara([normal('The study will be completed within the stipulated time limit. All research will be conducted in accordance with the ICMR 2017 Ethical Guidelines for Biomedical and Health Research. The data collected will be used solely for academic purposes.', 24)]),

      emptyLine(),
      emptyLine(),
      emptyLine(),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
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Packer.toBuffer(doc).then(buffer => {
  fs.writeFileSync('/home/daytona/workspace/synopsis-prakriti-migraine/SSAC_Synopsis_Prakriti_Migraine.docx', buffer);
  console.log('SUCCESS: Synopsis written successfully.');
}).catch(err => {
  console.error('ERROR:', err);
  process.exit(1);
});

cd /home/daytona/workspace/synopsis-prakriti-migraine && node synopsis.js 2>&1

python3 /home/daytona/skills/docx/scripts/office/validate.py /home/daytona/works…

cd /home/daytona/workspace/synopsis-prakriti-migraine && pandoc --track-changes=…

tail -80 /home/daytona/workspace/synopsis-prakriti-migraine/verify_output.md

python -m markitdown "/home/daytona/workspace/attachments/98cf7472-e0e4-46f4-b5b…

cd /home/daytona/skills/pptx && python scripts/thumbnail.py "/home/daytona/works…

cp /home/daytona/skills/pptx/thumbnails-1.jpg /home/daytona/workspace/synopsis-p…

cd /home/daytona/skills/pptx && python scripts/office/unpack.py "/home/daytona/w…

mkdir -p /home/daytona/workspace/synopsis-prakriti-migraine/template_unpacked &&…

timeout 30 unzip -l "/home/daytona/workspace/attachments/98cf7472-e0e4-46f4-b5bf…

mkdir -p /home/daytona/workspace/synopsis-prakriti-migraine/template_unpacked &&…

mkdir -p /home/daytona/workspace/synopsis-prakriti-migraine/tpl2 && cd /home/day…

cd /home/daytona/workspace/synopsis-prakriti-migraine/tpl2 && timeout 30 unzip -…

~/synopsis-prakriti-migraine/build_ppt.js

const pptxgen = require("pptxgenjs");
const pres = new pptxgen();
pres.layout = 'LAYOUT_16x9';
pres.title = 'Assessment of Deha Prakriti in Patients of Migraine';

// ── DESIGN CONSTANTS (matching template exactly) ────────────────────────────
const RED    = 'FF0000';
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const DKBLUE = '1F3864';
const WHITE  = 'FFFFFF';
const BGWHITE = 'FFFFFF';
const FONT  = 'Times New Roman';

// Slide dimensions: 10" x 5.625"
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// ── HELPERS ─────────────────────────────────────────────────────────────────

// Red top border bar (like all content slides have red heading)
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// ════════════════════════════════════════════════════════════════════════════
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// ════════════════════════════════════════════════════════════════════════════
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    { text: 'Chronic episodic neurovascular disorder — 3rd most prevalent disease globally; affects ~14.7% world population; Female:Male = 3:1; peak age 25-55 yrs. Prevalence in India: ~25.2 per 1000 population.', options: { breakLine: true } },
    { text: ' ', options: { breakLine: true, fontSize: 5 } },
    { text: 'Ayurvedic Correlation: ', options: { bold: true } },
    { text: 'Migraine correlates with ', options: {} },
    { text: 'Ardhavabhedaka', options: { italic: true } },
    { text: ' (Madhava Nidana Ch.62; Charaka Samhita, Siddhi Sthana 9; AH Uttara Tantra 23) — unilateral throbbing/piercing headache, episodic, with nausea/vomiting and aggravation by exertion. Primary Doshas: Vata + Pitta.', options: { breakLine: true } },
    { text: ' ', options: { breakLine: true, fontSize: 5 } },
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// ════════════════════════════════════════════════════════════════════════════
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    bl('Prasher B. et al. (2008, J Transl Med) — Genomic correlates of Prakriti types; established biological basis [PMID: 18782426]'),
    bl('Chowdhury D. et al. (2024, J Headache Pain) — Headache prevalence & demographics in India [PMID: 38943062]'),
    bl('PMC Review (2022, J Ayurveda Integr Med) — Ayurveda for migraine management; noted gap in Prakriti-migraine studies'),
    bl('PMC Review on PATs (2025) — Validated Prakriti assessment tools; cross-sectional design recommended'),
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 4 — NEED OF STUDY & RESEARCH QUESTION
// ════════════════════════════════════════════════════════════════════════════
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    bl('Ayurveda uniquely identifies disease via Prakriti (constitutional analysis) — foundational mandate of Rog Nidan Evum Vikriti Vigyan.'),
    bl('Classical texts link Ardhavabhedaka to Vata-Pitta Prakriti, but no validated observational study has confirmed this from this region.'),
    bl('Findings will enable Prakriti-based preventive advice and personalized treatment for migraine patients.'),
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 5 — HYPOTHESIS, AIM & OBJECTIVES
// ════════════════════════════════════════════════════════════════════════════
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    bl('2°  Correlate Prakriti with: attack frequency, duration, VAS score, aura, triggers, associated symptoms.'),
    bl('2°  Correlate Prakriti with MIDAS score (migraine disability) and demographic data (age, sex, occupation).'),
    bl('2°  Document Nidana Panchaka of Ardhavabhedaka from Ayurvedic perspective in study patients.'),
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 6 — STUDY DESIGN
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 7 — SELECTION CRITERIA
// ════════════════════════════════════════════════════════════════════════════
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  s.addText('ICHD-3: ≥5 attacks lasting 4-72 hrs; unilateral + pulsating + moderate-severe + aggravated by activity; with nausea/vomiting OR photophobia + phonophobia.  |  Ardhavabhedaka: unilateral episodic piercing headache, Vata-Pittaprakopaka Nidana (Madhava Nidana Ch.62).', {
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    bl('Age 18-60 yrs, either sex'),
    bl('Migraine diagnosed per ICHD-3 (≥5 attacks)'),
    bl('Attending OPD/IPD of SSAC, Kalol'),
    bl('Willing to give written informed consent'),
    bl('Able to respond to PAQ in Hindi/Gujarati'),
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    bl('Secondary headache (HTN, tumor, trauma, infection)'),
    bl('Chronic daily headache / Medication overuse headache'),
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    bl('Long-term corticosteroids / hormonal therapy'),
    bl('Major psychiatric illness'),
    bl('Serious systemic illness (malignancy, organ failure)'),
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 8 — CRITERIA FOR ASSESSMENT
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    { text: 'Sharira Lakshanas: ', options: { bold: true } },
    { text: 'Body frame, skin, hair, eyes, nails, voice      ', options: {} },
    { text: 'Kriya Lakshanas: ', options: { bold: true } },
    { text: 'Agni, digestion, sleep, bowel habits, sweat, endurance', options: { breakLine: true } },
    { text: 'Manasika Lakshanas: ', options: { bold: true } },
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      { text: 'MIDAS Score', options: { fontSize: 13, fontFace: FONT } },
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 9 — STATISTICAL ANALYSIS & ETHICAL CONSIDERATIONS
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 10 — TIMELINE (GANTT)
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// ════════════════════════════════════════════════════════════════════════════
// SLIDE 11 — THANK YOU
// ════════════════════════════════════════════════════════════════════════════
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// ── WRITE FILE ────────────────────────────────────────────────────────────────
pres.writeFile({ fileName: '/home/daytona/workspace/synopsis-prakriti-migraine/Synopsis_Prakriti_Migraine_Presentation.pptx' })
  .then(() => console.log('SUCCESS: PPT created.'))
  .catch(e => { console.error('ERROR:', e); process.exit(1); });

cd /home/daytona/workspace/synopsis-prakriti-migraine && node build_ppt.js 2>&1

ls /home/daytona/workspace/synopsis-prakriti-migraine/

~/synopsis-prakriti-migraine/crf.js

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const fs = require('fs');

// ─── STYLE CONSTANTS ─────────────────────────────────────────────────────────
const FONT  = 'Times New Roman';
const SFONT = 'Calibri';

// ─── BORDER HELPERS ──────────────────────────────────────────────────────────
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  left:   { style: BorderStyle.NONE, size: 0, color: 'FFFFFF' },
  right:  { style: BorderStyle.NONE, size: 0, color: 'FFFFFF' },
});
const bottomOnly = () => ({
  top:    { style: BorderStyle.NONE, size: 0, color: 'FFFFFF' },
  bottom: { style: BorderStyle.SINGLE, size: 6, color: '000000' },
  left:   { style: BorderStyle.NONE, size: 0, color: 'FFFFFF' },
  right:  { style: BorderStyle.NONE, size: 0, color: 'FFFFFF' },
});

// ─── TEXT HELPERS ─────────────────────────────────────────────────────────────
const r  = (t, opts={}) => new TextRun({ text: t, font: FONT, size: 20, ...opts });
const rb = (t, opts={}) => new TextRun({ text: t, font: FONT, size: 20, bold: true, ...opts });
const rs = (t, opts={}) => new TextRun({ text: t, font: SFONT, size: 18, ...opts });

// ─── PARAGRAPH HELPERS ───────────────────────────────────────────────────────
const P = (runs, opts={}) => new Paragraph({ children: Array.isArray(runs) ? runs : [runs], spacing: { after: 60 }, ...opts });
const PB = (text, opts={}) => new Paragraph({ children: [rb(text)], spacing: { after: 80 }, ...opts });
const empty = (n=1) => Array.from({length: n}, () => new Paragraph({ children: [r('')], spacing: { after: 40 } }));

// Section heading (dark blue filled, white text)
const sectionHeading = (text) => new Paragraph({
  children: [new TextRun({ text, font: FONT, size: 22, bold: true, color: 'FFFFFF' })],
  shading: { type: ShadingType.SOLID, color: '1F3864' },
  spacing: { before: 200, after: 80 },
  indent: { left: 0 }
});

// Sub-heading (red, bold, underlined)
const subHeading = (text) => new Paragraph({
  children: [new TextRun({ text, font: FONT, size: 20, bold: true, color: 'CC0000',
    underline: { type: UnderlineType.SINGLE } })],
  spacing: { before: 120, after: 60 },
});

// Label + blank line (fill-in field)
const field = (label, width = 60) => new Paragraph({
  children: [
    rb(label + ':  '),
    r('_'.repeat(width))
  ],
  spacing: { after: 80 },
});

// Label + options inline
const checkField = (label, options) => new Paragraph({
  children: [
    rb(label + ':  '),
    ...options.flatMap(o => [r('☐ ' + o + '   ')])
  ],
  spacing: { after: 80 },
});

// ─── TABLE HELPERS ────────────────────────────────────────────────────────────
const cell = (text, opts={}, shade=null) => new TableCell({
  children: [new Paragraph({
    children: [new TextRun({ text, font: FONT, size: 19, bold: opts.bold||false, color: opts.color||'000000' })],
    alignment: opts.align || AlignmentType.LEFT,
    spacing: { after: 40 }
  })],
  borders: opts.borders || singleBorder(),
  shading: shade ? { type: ShadingType.SOLID, color: shade } : undefined,
  width: opts.width ? { size: opts.width, type: WidthType.PERCENTAGE } : undefined,
  margins: { top: 80, bottom: 80, left: 100, right: 80 },
  verticalAlign: VerticalAlign.CENTER,
});

const cellH = (text, w) => cell(text, { bold: true, color: 'FFFFFF', align: AlignmentType.CENTER, width: w }, '1F3864');

// Blank answer cell
const blankCell = (w) => new TableCell({
  children: [new Paragraph({ children: [r('')], spacing: { after: 40 } })],
  borders: singleBorder(),
  width: { size: w, type: WidthType.PERCENTAGE },
  margins: { top: 80, bottom: 80, left: 100, right: 80 },
});

// Two-col label+blank row
const labelRow = (label, w1=35, w2=65) => new TableRow({ children: [
  cell(label, { bold: true, width: w1 }, 'F2F2F2'),
  blankCell(w2)
]});

// ─── MIDAS TABLE ─────────────────────────────────────────────────────────────
function midasTable() {
  const questions = [
    ['Q1', 'On how many days in the last 3 months did you miss work or school because of your headaches?'],
    ['Q2', 'On how many days in the last 3 months was your productivity at work or school reduced by half or more because of your headaches? (Do not count days in Q1)'],
    ['Q3', 'On how many days in the last 3 months did you not do household work because of your headaches?'],
    ['Q4', 'On how many days in the last 3 months was your productivity in household work reduced by half or more? (Do not count days in Q3)'],
    ['Q5', 'On how many days in the last 3 months did you miss family, social or leisure activities because of your headaches?'],
  ];
  const rows = [
    new TableRow({ children: [
      cellH('Q.No.', 8), cellH('Question', 72), cellH('Days', 20)
    ]}),
    ...questions.map(([q, text]) => new TableRow({ children: [
      cell(q, { align: AlignmentType.CENTER }, 'FFF9F9'),
      cell(text, {}, 'FFFFFF'),
      blankCell(20)
    ]})),
    new TableRow({ children: [
      cell('', {}, 'F2F2F2'),
      cell('TOTAL MIDAS SCORE (Q1+Q2+Q3+Q4+Q5)', { bold: true, align: AlignmentType.RIGHT }, 'FFE8E8'),
      blankCell(20)
    ]}),
  ];
  return new Table({ width: { size: 100, type: WidthType.PERCENTAGE }, rows });
}

// ─── VAS TABLE ────────────────────────────────────────────────────────────────
function vasTable() {
  const cols = ['0','1','2','3','4','5','6','7','8','9','10'];
  return new Table({
    width: { size: 100, type: WidthType.PERCENTAGE },
    rows: [
      new TableRow({ children: cols.map(n => new TableCell({
        children: [new Paragraph({ children: [new TextRun({ text: n, font: FONT, size: 22, bold: true, color: n==='0'?'006600':n==='5'?'FF6600':n==='10'?'CC0000':'000000' })], alignment: AlignmentType.CENTER, spacing: { after: 40 } })],
        borders: singleBorder(),
        shading: { type: ShadingType.SOLID, color: n==='0'?'E8FFE8':n==='5'?'FFF0D0':n==='10'?'FFE8E8':'F8F8F8' },
        margins: { top: 100, bottom: 100, left: 60, right: 60 },
      }))
      }),
      new TableRow({ children: [
        new TableCell({
          children: [new Paragraph({ children: [r('No Pain')], alignment: AlignmentType.CENTER, spacing: { after: 40 } })],
          borders: noBorder(), columnSpan: 3
        }),
        new TableCell({ children: [new Paragraph({ children: [r('')], spacing: { after: 40 } })], borders: noBorder(), columnSpan: 5 }),
        new TableCell({
          children: [new Paragraph({ children: [r('Worst Pain')], alignment: AlignmentType.CENTER, spacing: { after: 40 } })],
          borders: noBorder(), columnSpan: 3
        }),
      ]})
    ]
  });
}

// ─── PRAKRITI PAQ ─────────────────────────────────────────────────────────────
function paqRow(no, question, options, subLabel=false) {
  return new TableRow({ children: [
    cell(`${no}.`, { align: AlignmentType.CENTER }, no%2===0?'FFFFFF':'F9F9F9'),
    new TableCell({
      children: [new Paragraph({ children: [r(question, { bold: subLabel })], spacing: { after: 40 } })],
      borders: singleBorder(),
      margins: { top: 60, bottom: 60, left: 100, right: 60 },
      width: { size: 40, type: WidthType.PERCENTAGE }
    }),
    ...options.map(opt => new TableCell({
      children: [new Paragraph({ children: [r(opt)], alignment: AlignmentType.CENTER, spacing: { after: 40 } })],
      borders: singleBorder(),
      margins: { top: 60, bottom: 60, left: 60, right: 60 },
      width: { size: 17, type: WidthType.PERCENTAGE }
    }))
  ]});
}

function paqGroupHeader(label) {
  return new TableRow({ children: [
    new TableCell({
      children: [new Paragraph({ children: [new TextRun({ text: label, font: FONT, size: 19, bold: true, color: 'FFFFFF' })], alignment: AlignmentType.CENTER, spacing: { after: 40 } })],
      borders: singleBorder(),
      shading: { type: ShadingType.SOLID, color: 'C00000' },
      columnSpan: 5,
      margins: { top: 80, bottom: 80, left: 100, right: 60 },
    })
  ]});
}

function buildPAQ() {
  const headerRow = new TableRow({ children: [
    cellH('#', 5),
    cellH('Feature / Question', 40),
    cellH('Vata Response', 18),
    cellH('Pitta Response', 18),
    cellH('Kapha Response', 18),
  ]});

  const rows = [
    paqGroupHeader('A. SHARIRA LAKSHANAS (Physical / Morphological Traits)'),
    paqRow(1,  'Body frame / Build',                  ['Lean, thin, underdeveloped',           'Medium, moderate',                         'Heavy, stout, well-built']),
    paqRow(2,  'Skin texture',                         ['Dry, rough, cracked',                  'Soft, oily, warm, reddish tinge',          'Smooth, moist, cool, pale/white']),
    paqRow(3,  'Complexion',                           ['Dark, dusky, brownish',                'Reddish, coppery, yellowish',              'Fair, whitish, lustrous']),
    paqRow(4,  'Hair (scalp)',                         ['Dry, frizzy, scanty, splits',          'Thin, silky, early graying/baldness',      'Thick, oily, lustrous, wavy']),
    paqRow(5,  'Eyes',                                 ['Small, dry, unsteady, dull',           'Sharp, penetrating, reddish, sensitive',   'Large, moist, attractive, white sclera']),
    paqRow(6,  'Nails',                                ['Dry, rough, brittle, cracked',         'Soft, pinkish, sharp',                     'Thick, smooth, oily, lustrous']),
    paqRow(7,  'Teeth & gums',                        ['Dry, irregular, spaced, receding gums','Moderate, yellowish, gums bleed easily',   'Strong, white, well-set, pink gums']),
    paqRow(8,  'Joints',                               ['Prominent, cracking sounds',           'Moderate, loose',                          'Strong, well-built, not prominent']),
    paqRow(9,  'Voice quality',                        ['Low, hoarse, weak',                    'Sharp, commanding, moderate',              'Deep, resonant, pleasant']),
    paqRow(10, 'Body weight tendency',                 ['Underweight, difficulty gaining',      'Moderate, easy to maintain',               'Overweight, gains easily']),

    paqGroupHeader('B. KRIYA LAKSHANAS (Physiological / Functional Traits)'),
    paqRow(11, 'Appetite (Agni/Hunger)',               ['Variable, irregular',                  'Strong, intense; angry if meal missed',    'Slow, consistent, can skip meals']),
    paqRow(12, 'Digestion',                            ['Irregular, often bloating/gas',        'Fast, strong; heartburn/acidity common',   'Slow but steady; heaviness after meals']),
    paqRow(13, 'Bowel habits',                         ['Constipated, dry, hard stools',        'Loose, frequent, yellowish stools',        'Regular, heavy, oily stools']),
    paqRow(14, 'Thirst',                               ['Variable, erratic',                    'Intense, excessive thirst',                'Low, infrequent']),
    paqRow(15, 'Sweating',                             ['Scanty, odourless',                    'Profuse, strong odour',                    'Moderate, sweet/cold smell']),
    paqRow(16, 'Sleep pattern',                        ['Light, interrupted, dreams active',    'Moderate; can sleep on demand if needed',  'Deep, prolonged, refreshing']),
    paqRow(17, 'Sleep duration',                       ['Short (4-6 hrs), feels unrefreshed',   'Moderate (6-8 hrs)',                       'Long (8+ hrs), difficulty waking']),
    paqRow(18, 'Physical activity/exercise tolerance', ['Quick to fatigue, active mind',        'Moderate, competitive, focused',           'Enduring, slow to start but steady']),
    paqRow(19, 'Walking pace / Gait',                  ['Fast, quick, unsteady',                'Moderate, purposeful',                     'Slow, steady, graceful']),
    paqRow(20, 'Tolerance to temperature',             ['Dislikes cold, wind, dryness',         'Dislikes heat, sun, fire',                 'Dislikes cold, damp, clouds']),
    paqRow(21, 'Sexual drive',                         ['Strong desire, low stamina',           'Moderate, intense when aroused',           'Moderate to low desire, good stamina']),

    paqGroupHeader('C. MANASIKA LAKSHANAS (Psychological / Mental Traits)'),
    paqRow(22, 'Memory type',                         ['Quick to grasp, forgets quickly',      'Sharp, accurate, retentive',               'Slow to learn, remembers long-term']),
    paqRow(23, 'Decision making',                     ['Quick but changes mind often',         'Sharp, analytical, decisive',              'Slow, deliberate, steady once decided']),
    paqRow(24, 'Speech pattern',                      ['Fast, talkative, switches topics',     'Sharp, argumentative, precise',            'Slow, measured, melodious']),
    paqRow(25, 'Emotional temperament',               ['Anxious, fearful, nervous, excited',   'Irritable, ambitious, critical, angry',    'Calm, composed, content, slow to anger']),
    paqRow(26, 'Stress response',                     ['Anxiety, worry, restlessness',         'Irritability, anger, perfectionism',       'Withdrawal, attachment, possessiveness']),
    paqRow(27, 'Adaptability',                        ['Highly adaptable, erratic',            'Moderate, dislikes change in principles',  'Resistant to change, consistent']),
    paqRow(28, 'Financial tendency',                  ['Spends quickly, poor savings',         'Spends purposefully, planned',             'Saves well, accumulates']),
    paqRow(29, 'Social nature',                       ['Talkative, makes friends easily',      'Leader, discriminating in friendships',    'Loyal, long-term relationships']),
    paqRow(30, 'Spiritual/Religious tendency',        ['Quickly devoted, inconsistent',        'Rational, skeptical, seeks understanding', 'Deep, devoted, consistent faith']),
  ];

  return new Table({
    width: { size: 100, type: WidthType.PERCENTAGE },
    rows: [headerRow, ...rows]
  });
}

// ─── SCORING TABLE ────────────────────────────────────────────────────────────
function scoringTable() {
  return new Table({
    width: { size: 100, type: WidthType.PERCENTAGE },
    rows: [
      new TableRow({ children: [
        cellH('Dosha', 25), cellH('No. of Responses Ticked', 25),
        cellH('Score (×1 each)', 25), cellH('Predominance Rank', 25)
      ]}),
      new TableRow({ children: [cell('Vata', {},'FFF5F5'), blankCell(25), blankCell(25), blankCell(25)] }),
      new TableRow({ children: [cell('Pitta',{},'FFF5F5'), blankCell(25), blankCell(25), blankCell(25)] }),
      new TableRow({ children: [cell('Kapha',{},'FFF5F5'), blankCell(25), blankCell(25), blankCell(25)] }),
      new TableRow({ children: [
        cell('Final Prakriti Classification', { bold: true, color: 'FFFFFF' }, 'C00000'),
        new TableCell({
          children: [new Paragraph({ children: [r('')], spacing: { after: 40 } })],
          borders: singleBorder(), columnSpan: 3,
          margins: { top: 80, bottom: 80, left: 100, right: 80 },
        })
      ]}),
    ]
  });
}

// ─── MIDAS GRADING TABLE ─────────────────────────────────────────────────────
function midasGradingTable() {
  return new Table({
    width: { size: 80, type: WidthType.PERCENTAGE },
    rows: [
      new TableRow({ children: [cellH('Grade', 15), cellH('Score', 20), cellH('Severity', 35), cellH('Patient Grade', 30)] }),
      new TableRow({ children: [cell('I',{},'F9F9F9'),  cell('0-5',{},'F9F9F9'),  cell('Minimal / Infrequent disability',{},'F9F9F9'), blankCell(30)] }),
      new TableRow({ children: [cell('II',{},'F2F2F2'), cell('6-10',{},'F2F2F2'), cell('Mild / Infrequent disability',{},'F2F2F2'),   blankCell(30)] }),
      new TableRow({ children: [cell('III',{},'F9F9F9'),cell('11-20',{},'F9F9F9'),cell('Moderate disability',{},'F9F9F9'),            blankCell(30)] }),
      new TableRow({ children: [cell('IV',{},'F2F2F2'), cell('21+',{},'F2F2F2'),  cell('Severe / Frequent disability',{},'F2F2F2'),   blankCell(30)] }),
    ]
  });
}

// ─── INVESTIGATIONS TABLE ─────────────────────────────────────────────────────
function investigationsTable() {
  return new Table({
    width: { size: 100, type: WidthType.PERCENTAGE },
    rows: [
      new TableRow({ children: [cellH('Investigation', 40), cellH('Result / Finding', 35), cellH('Normal Range', 25)] }),
      new TableRow({ children: [cell('Haemoglobin (Hb)',{},'F9F9F9'), blankCell(35), cell('M: 13-17 g/dL | F: 11.5-15.5',{},null)] }),
      new TableRow({ children: [cell('Total WBC Count',{},'FFFFFF'), blankCell(35), cell('4,000-11,000 /cmm',{},null)] }),
      new TableRow({ children: [cell('Blood Pressure (mmHg)',{},'F9F9F9'), blankCell(35), cell('<120/80 mmHg',{},null)] }),
      new TableRow({ children: [cell('Random Blood Sugar (RBS)',{},'FFFFFF'), blankCell(35), cell('70-140 mg/dL',{},null)] }),
      new TableRow({ children: [cell('CT/MRI Brain (if indicated)',{},'F9F9F9'), blankCell(35), cell('NAD / Findings:',{},null)] }),
      new TableRow({ children: [cell('Any other (specify)',{},'FFFFFF'), blankCell(35), blankCell(25)] }),
    ]
  });
}

// ════════════════════════════════════════════════════════════════════════════
// BUILD DOCUMENT
// ════════════════════════════════════════════════════════════════════════════
const doc = new Document({
  styles: { default: { document: { run: { font: FONT, size: 20 } } } },
  sections: [{
    properties: {
      page: { margin: { top: 900, bottom: 900, left: 1080, right: 900 } }
    },
    children: [

      // ── TITLE BLOCK ──────────────────────────────────────────────────────
      new Paragraph({
        children: [new TextRun({ text: 'SHREE SWAMINARAYAN AYURVEDIC COLLEGE', font: FONT, size: 26, bold: true, color: 'CC0000' })],
        alignment: AlignmentType.CENTER, spacing: { after: 40 }
      }),
      new Paragraph({
        children: [new TextRun({ text: 'Department of Rog Nidan Evum Vikriti Vigyan', font: FONT, size: 22, bold: true, color: '1F3864' })],
        alignment: AlignmentType.CENTER, spacing: { after: 40 }
      }),
      new Paragraph({
        children: [new TextRun({ text: 'Kalol, Gandhinagar, Gujarat - 382 725', font: FONT, size: 20, color: '333333' })],
        alignment: AlignmentType.CENTER, spacing: { after: 80 }
      }),
      new Paragraph({
        children: [new TextRun({ text: 'CASE RECORD FORM (CRF)', font: FONT, size: 28, bold: true, color: '000000',
          underline: { type: UnderlineType.SINGLE } })],
        alignment: AlignmentType.CENTER, spacing: { after: 40 }
      }),
      new Paragraph({
        children: [new TextRun({ text: 'Study Title: Assessment of Deha Prakriti in Patients of Migraine — A Cross Sectional Study', font: FONT, size: 20, bold: true, color: '1F3864' })],
        alignment: AlignmentType.CENTER, spacing: { after: 120 }
      }),

      // CRF ID + Date
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [ new TableRow({ children: [
          cell('CRF No.:',   { bold: true, width: 15 }, 'F2F2F2'), blankCell(18),
          cell('OPD/IPD No.:', { bold: true, width: 20 }, 'F2F2F2'), blankCell(20),
          cell('Date of Registration:', { bold: true, width: 15 }, 'F2F2F2'), blankCell(12),
        ]})],
      }),

      ...empty(1),

      // ── SECTION 1: PATIENT IDENTIFICATION ────────────────────────────────
      sectionHeading('SECTION 1: PATIENT IDENTIFICATION & DEMOGRAPHIC DATA'),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Patient Name:', { bold: true, width: 20 }, 'F2F2F2'), blankCell(40),
            cell('Age (yrs):', { bold: true, width: 15 }, 'F2F2F2'), blankCell(25),
          ]}),
          new TableRow({ children: [
            cell('Sex:', { bold: true, width: 20 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Male   ☐ Female   ☐ Other')])],
              borders: singleBorder(), width: { size: 40, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
            cell('Date of Birth:', { bold: true, width: 15 }, 'F2F2F2'), blankCell(25),
          ]}),
          new TableRow({ children: [
            cell('Address:', { bold: true, width: 20 }, 'F2F2F2'), blankCell(80),
          ]}),
          new TableRow({ children: [
            cell('Contact No.:', { bold: true, width: 20 }, 'F2F2F2'), blankCell(30),
            cell('Religion:', { bold: true, width: 15 }, 'F2F2F2'), blankCell(35),
          ]}),
          new TableRow({ children: [
            cell('Occupation:', { bold: true, width: 20 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Housewife   ☐ Student   ☐ Service   ☐ Business   ☐ Labour   ☐ Other: _______')])],
              borders: singleBorder(), width: { size: 80, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }, columnSpan: 3,
            }),
          ]}),
          new TableRow({ children: [
            cell('Education:', { bold: true, width: 20 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Illiterate   ☐ Primary   ☐ Secondary   ☐ Graduate   ☐ Post-Graduate')])],
              borders: singleBorder(), width: { size: 80, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }, columnSpan: 3,
            }),
          ]}),
          new TableRow({ children: [
            cell('Socioeconomic Status:', { bold: true, width: 20 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Lower   ☐ Lower-Middle   ☐ Middle   ☐ Upper-Middle   ☐ Upper')])],
              borders: singleBorder(), columnSpan: 3,
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Marital Status:', { bold: true, width: 20 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Unmarried   ☐ Married   ☐ Divorced   ☐ Widowed')])],
              borders: singleBorder(), columnSpan: 3,
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Dietary Habits:', { bold: true, width: 20 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Vegetarian   ☐ Non-Vegetarian   ☐ Eggetarian')])],
              borders: singleBorder(), columnSpan: 3,
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),

      // ── SECTION 2: CHIEF COMPLAINTS ──────────────────────────────────────
      sectionHeading('SECTION 2: CHIEF COMPLAINTS'),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [ cellH('Complaint', 70), cellH('Duration', 30) ] }),
          new TableRow({ children: [ blankCell(70), blankCell(30) ] }),
          new TableRow({ children: [ blankCell(70), blankCell(30) ] }),
          new TableRow({ children: [ blankCell(70), blankCell(30) ] }),
          new TableRow({ children: [ blankCell(70), blankCell(30) ] }),
        ]
      }),

      ...empty(1),

      // ── SECTION 3: HISTORY OF PRESENT ILLNESS ────────────────────────────
      sectionHeading('SECTION 3: HISTORY OF PRESENT ILLNESS (MIGRAINE PROFILE)'),

      subHeading('3.1 Headache Characteristics'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Duration of illness (since when):', { bold: true, width: 40 }, 'F2F2F2'), blankCell(60),
          ]}),
          new TableRow({ children: [
            cell('Site of pain:', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Unilateral (Right / Left)   ☐ Bilateral   ☐ Whole head   ☐ Shifting')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Quality of pain:', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Throbbing/Pulsating   ☐ Pressing/Heavy   ☐ Stabbing/Piercing   ☐ Burning   ☐ Dull ache')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Severity of pain during attack (VAS):', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Mild (1-3)   ☐ Moderate (4-6)   ☐ Severe (7-10)   Score: _______')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Duration of each attack:', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ <4 hours   ☐ 4-24 hours   ☐ 24-72 hours   ☐ >72 hours   (specify): _______')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Frequency of attacks (per month):', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ 1-2   ☐ 3-4   ☐ 5-6   ☐ >6   (exact no.): _______')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Total lifetime attacks (approx.):', { bold: true, width: 40 }, 'F2F2F2'), blankCell(60),
          ]}),
          new TableRow({ children: [
            cell('Aggravating factors:', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Physical activity   ☐ Light   ☐ Sound   ☐ Smell   ☐ Head movement   ☐ Other: _______')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Relieving factors:', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Rest/Sleep   ☐ Dark room/Quiet   ☐ Cold compress   ☐ Analgesics   ☐ Other: _______')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Time of onset of attacks:', { bold: true, width: 40 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Morning   ☐ Afternoon   ☐ Evening   ☐ Night   ☐ No fixed time')])],
              borders: singleBorder(), width: { size: 60, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),
      subHeading('3.2 Associated Symptoms'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Nausea:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
            cell('Vomiting:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Photophobia:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
            cell('Phonophobia:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Osmophobia:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
            cell('Vertigo / Dizziness:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Neck stiffness / pain:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
            cell('Lacrimation / Nasal congestion:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 25, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Aura:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Present   ☐ Absent   If present — Type: ☐ Visual (zigzag/scintillating scotoma)   ☐ Sensory   ☐ Speech   ☐ Motor')])],
              borders: singleBorder(), columnSpan: 3,
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Prodromal symptoms:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('☐ Mood change   ☐ Yawning   ☐ Food craving   ☐ Neck stiffness   ☐ Fatigue   ☐ None')])],
              borders: singleBorder(), columnSpan: 3,
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),
      subHeading('3.3 Triggers'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            new TableCell({
              children: [
                P([rb('Dietary Triggers:  '), r('☐ Fasting   ☐ Irregular meals   ☐ Cheese   ☐ Chocolate   ☐ Alcohol   ☐ Caffeine/Tea   ☐ Citrus   ☐ MSG   ☐ Cold foods   ☐ None')]),
                P([rb('Sleep-related:  '), r('☐ Sleep deprivation   ☐ Oversleeping   ☐ Shift work')]),
                P([rb('Hormonal (Females):  '), r('☐ Menstrual cycle   ☐ OCP use   ☐ Pregnancy   ☐ Not applicable')]),
                P([rb('Environmental:  '), r('☐ Bright light   ☐ Loud noise   ☐ Strong odour   ☐ Weather change   ☐ High altitude')]),
                P([rb('Psychological:  '), r('☐ Mental stress   ☐ Anxiety   ☐ Depression   ☐ Emotional disturbance')]),
                P([rb('Physical:  '), r('☐ Exertion   ☐ Travel   ☐ Head injury history   ☐ Eye strain   ☐ Neck strain')]),
              ],
              borders: singleBorder(),
              margins: { top: 80, bottom: 80, left: 120, right: 80 }
            })
          ]}),
        ]
      }),

      ...empty(1),

      // ── SECTION 4: ICHD-3 DIAGNOSTIC CHECKLIST ───────────────────────────
      sectionHeading('SECTION 4: ICHD-3 DIAGNOSTIC CHECKLIST FOR MIGRAINE WITHOUT AURA'),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [cellH('Criterion', 75), cellH('Met?', 12), cellH('Remarks', 13)] }),
          new TableRow({ children: [
            cell('A. At least 5 attacks fulfilling criteria B-D', {}, 'FFFAF0'),
            new TableCell({ children: [P([r('☐ Yes   ☐ No')])], borders: singleBorder(), width: { size: 12, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 60, right: 60 } }),
            blankCell(13)
          ]}),
          new TableRow({ children: [
            cell('B. Headache lasting 4-72 hours (untreated / unsuccessfully treated)', {}, 'F9F9F9'),
            new TableCell({ children: [P([r('☐ Yes   ☐ No')])], borders: singleBorder(), width: { size: 12, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 60, right: 60 } }),
            blankCell(13)
          ]}),
          new TableRow({ children: [
            new TableCell({
              children: [
                P([rb('C. Headache with at least 2 of the following 4 characteristics (tick applicable):')]),
                P([r('  ☐ Unilateral location')]),
                P([r('  ☐ Pulsating/throbbing quality')]),
                P([r('  ☐ Moderate to severe intensity')]),
                P([r('  ☐ Aggravated by / causes avoidance of routine physical activity')]),
              ],
              borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 120, right: 80 },
              shading: { type: ShadingType.SOLID, color: 'FFFAF0' }
            }),
            new TableCell({ children: [P([r('☐ Yes   ☐ No')])], borders: singleBorder(), width: { size: 12, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 60, right: 60 } }),
            blankCell(13)
          ]}),
          new TableRow({ children: [
            new TableCell({
              children: [
                P([rb('D. During headache at least 1 of the following (tick applicable):')]),
                P([r('  ☐ Nausea and/or vomiting')]),
                P([r('  ☐ Photophobia AND phonophobia')]),
              ],
              borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 120, right: 80 },
              shading: { type: ShadingType.SOLID, color: 'F9F9F9' }
            }),
            new TableCell({ children: [P([r('☐ Yes   ☐ No')])], borders: singleBorder(), width: { size: 12, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 60, right: 60 } }),
            blankCell(13)
          ]}),
          new TableRow({ children: [
            cell('E. Not better accounted for by another ICHD-3 diagnosis', {}, 'FFFAF0'),
            new TableCell({ children: [P([r('☐ Yes   ☐ No')])], borders: singleBorder(), width: { size: 12, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 60, right: 60 } }),
            blankCell(13)
          ]}),
          new TableRow({ children: [
            cell('FINAL DIAGNOSIS (ICHD-3):', { bold: true, color: 'FFFFFF' }, 'C00000'),
            new TableCell({
              children: [P([r('☐ Migraine without Aura   ☐ Migraine with Aura   ☐ Chronic Migraine   ☐ Probable Migraine')])],
              borders: singleBorder(), columnSpan: 2,
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),

      // ── SECTION 5: PAST HISTORY ───────────────────────────────────────────
      sectionHeading('SECTION 5: PAST HISTORY & FAMILY HISTORY'),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Past H/o Migraine treatment:', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ None   ☐ Allopathic   ☐ Ayurvedic   ☐ Homeopathic   ☐ Other: _______')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('H/o Hypertension:', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('H/o Diabetes Mellitus:', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present   ☐ Absent')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('H/o Epilepsy / Neurological disorder:', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present (specify): ________________   ☐ Absent')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('H/o Major surgery / Trauma:', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Present (specify): ________________   ☐ Absent')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Drug history (current medications):', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ None   List if any: ________________________________________________')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Family H/o Migraine:', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Positive (Relation: Father / Mother / Sibling / Other: _________)   ☐ Negative   ☐ Not known')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Menstrual history (Females):', { bold: true, width: 30 }, 'F2F2F2'),
            new TableCell({ children: [P([r('Regular / Irregular   Cycle: _____ days   Attacks related to menses: ☐ Yes   ☐ No')])], borders: singleBorder(), width: { size: 70, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
        ]
      }),

      ...empty(1),

      // ── SECTION 6: NIDANA PANCHAKA (PAGE BREAK FOR NEATNESS) ─────────────
      new Paragraph({ children: [new PageBreak()] }),

      sectionHeading('SECTION 6: NIDANA PANCHAKA (AYURVEDIC PATHOLOGICAL ASSESSMENT)'),

      subHeading('6.1 Nidana (Causative Factors)'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [ cellH('Category', 25), cellH('Nidana Factors (tick applicable)', 75) ] }),
          new TableRow({ children: [
            cell('Aharaja Nidana\n(Dietary)', { bold: true }, 'FFF5F5'),
            new TableCell({
              children: [P([r('☐ Ruksha (Dry/Rough food)   ☐ Ushna (Very hot food)   ☐ Tikshna (Pungent/Spicy)   ☐ Katu (Bitter excess)\n☐ Vega Dharana (suppressing urges)   ☐ Adhyashana (eating before previous meal digests)   ☐ Viruddha Ahara')])],
              borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Viharaja Nidana\n(Lifestyle)', { bold: true }, 'F5FFF5'),
            new TableCell({
              children: [P([r('☐ Ratrijagarana (Night waking)   ☐ Divaswapna (Day sleep)   ☐ Atimaithuna   ☐ Vyayama (Excess exertion)\n☐ Ativata sevana (excess wind/cold exposure)   ☐ Atapa sevana (excess sun exposure)')])],
              borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Manasika Nidana\n(Psychological)', { bold: true }, 'F5F5FF'),
            new TableCell({
              children: [P([r('☐ Chinta (Worry/Anxiety)   ☐ Shoka (Grief)   ☐ Bhaya (Fear)   ☐ Krodha (Anger)   ☐ Mental overwork')])],
              borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Agantuja Nidana\n(Exogenous)', { bold: true }, 'FFFFF0'),
            new TableCell({
              children: [P([r('☐ Head trauma   ☐ Loud noise   ☐ Bright lights   ☐ Strong odours   ☐ Change in climate')])],
              borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),
      subHeading('6.2 Purvarupa (Premonitory Signs & Symptoms)'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            new TableCell({
              children: [P([r('☐ Hrillasa (Nausea)   ☐ Moordhni Gaurava (Heaviness of head)   ☐ Akshi Sphutana (Pain in eyes)   ☐ Ardha Shiroruja (Vague half-head pain)\n☐ Anga Marda (Body ache)   ☐ Aruchi (Anorexia)   ☐ Tandra (Drowsiness)   ☐ Neck stiffness   ☐ Mood change   ☐ None')])],
              borders: singleBorder(),
              margins: { top: 80, bottom: 80, left: 120, right: 80 }
            })
          ]]
        }),
        ],
      }),

      ...empty(1),
      subHeading('6.3 Rupa (Clinical Features / Signs & Symptoms)'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            new TableCell({
              children: [
                P([r('☐ Ardhashiroruja (Unilateral headache — cardinal feature)   ☐ Intense stabbing/piercing quality (Bheda Vedana)')]),
                P([r('☐ Temporal/frontal location   ☐ Neck pain associated   ☐ Trishna (thirst)   ☐ Trasa (restlessness)')]),
                P([r('☐ Nausea/Vomiting   ☐ Photophobia   ☐ Phonophobia   ☐ Aura (visual/sensory)   ☐ Vertigo')]),
              ],
              borders: singleBorder(),
              margins: { top: 80, bottom: 80, left: 120, right: 80 }
            })
          ]]),
        ],
      }),

      ...empty(1),
      subHeading('6.4 Upashaya & Anupashaya (Factors that relieve or aggravate)'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Upashaya (Relieving):', { bold: true, width: 22 }, 'F5FFF5'),
            new TableCell({
              children: [P([r('☐ Rest   ☐ Sleep   ☐ Darkness/silence   ☐ Cold water/compress   ☐ Snehana (oily food/massage)   ☐ Vomiting   ☐ Mrudu Basti   ☐ Swedana')])],
              borders: singleBorder(), width: { size: 78, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
          new TableRow({ children: [
            cell('Anupashaya (Aggravating):', { bold: true, width: 22 }, 'FFF5F5'),
            new TableCell({
              children: [P([r('☐ Physical activity   ☐ Light/sound/smell   ☐ Fasting   ☐ Cold/dry weather   ☐ Mental stress   ☐ Head movement')])],
              borders: singleBorder(), width: { size: 78, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),
      subHeading('6.5 Samprapti (Pathogenesis — Ayurvedic)'),
      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Dosha involved:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Vata   ☐ Pitta   ☐ Kapha   ☐ Vata-Pitta   ☐ Vata-Kapha   ☐ Tridosha')])], borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Dushya:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Rasa   ☐ Rakta   ☐ Majja   ☐ Manas')])], borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Srotas involved:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Rasavaha   ☐ Raktavaha   ☐ Majjavaha   ☐ Manovaha Srotas')])], borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Adhisthana (site):', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('Shiras (Head) — Ardhabhaga (Half portion)')])], borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
          new TableRow({ children: [
            cell('Vyadhi Swabhava:', { bold: true, width: 25 }, 'F2F2F2'),
            new TableCell({ children: [P([r('☐ Krichhrasadhya   ☐ Sadhya   ☐ Asadhya')])], borders: singleBorder(), width: { size: 75, type: WidthType.PERCENTAGE }, margins: { top: 80, bottom: 80, left: 100, right: 80 } }),
          ]}),
        ]
      }),

      ...empty(1),

      // ── SECTION 7: VAS ────────────────────────────────────────────────────
      sectionHeading('SECTION 7: VISUAL ANALOGUE SCALE (VAS) FOR PAIN INTENSITY'),

      P([r('Please circle or shade the number that best describes the pain during a typical migraine attack:')]),
      ...empty(1),
      vasTable(),
      ...empty(1),
      new Table({
        width: { size: 60, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('VAS Score recorded:', { bold: true, width: 60 }, 'FFE8E8'),
            blankCell(40)
          ]})
        ]
      }),

      ...empty(1),

      // ── SECTION 8: MIDAS SCORE ────────────────────────────────────────────
      sectionHeading('SECTION 8: MIDAS SCORE (Migraine Disability Assessment)'),

      P([r('Instructions: For each question, enter the number of days in the LAST 3 MONTHS. If the activity was not applicable, enter "0".')]),
      ...empty(1),
      midasTable(),
      ...empty(1),
      P([rb('MIDAS Grading:')]),
      midasGradingTable(),
      ...empty(1),

      new Paragraph({ children: [new PageBreak()] }),

      // ── SECTION 9: DEHA PRAKRITI ASSESSMENT ─────────────────────────────
      sectionHeading('SECTION 9: DEHA PRAKRITI ASSESSMENT — CCRAS VALIDATED PAQ'),

      P([r('Instructions: Read each question carefully and tick (✓) the response that BEST describes the individual\'s LIFELONG and HABITUAL traits — NOT their current disease state. Choose only ONE response per question.')]),
      ...empty(1),
      buildPAQ(),
      ...empty(1),

      subHeading('Prakriti Scoring Summary'),
      scoringTable(),
      ...empty(1),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            cell('Final Prakriti Type (circle):', { bold: true, width: 35 }, 'F2F2F2'),
            new TableCell({
              children: [P([r('Vata   |   Pitta   |   Kapha   |   Vata-Pitta   |   Vata-Kapha   |   Pitta-Kapha   |   Sama')])],
              borders: singleBorder(), width: { size: 65, type: WidthType.PERCENTAGE },
              margins: { top: 80, bottom: 80, left: 100, right: 80 }
            }),
          ]}),
        ]
      }),

      ...empty(1),

      // ── SECTION 10: INVESTIGATIONS ────────────────────────────────────────
      sectionHeading('SECTION 10: INVESTIGATIONS (for exclusion criteria screening)'),

      investigationsTable(),
      ...empty(1),

      // ── SECTION 11: ELIGIBILITY CONFIRMATION ─────────────────────────────
      sectionHeading('SECTION 11: ELIGIBILITY CHECKLIST (Inclusion / Exclusion Confirmation)'),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [ cellH('Criteria', 80), cellH('Confirmed', 10), cellH('Remarks', 10) ] }),
          new TableRow({ children: [cell('Age 18-60 years',{},null), new TableCell({ children:[P([r('☐ Yes   ☐ No')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('ICHD-3 criteria for Migraine fulfilled (≥5 attacks)',{},null), new TableCell({ children:[P([r('☐ Yes   ☐ No')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('No secondary headache (BP, tumor, trauma, infection)',{},null), new TableCell({ children:[P([r('☐ Ruled out')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('No chronic daily headache / MOH',{},null), new TableCell({ children:[P([r('☐ Ruled out')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('Not pregnant / lactating',{},null), new TableCell({ children:[P([r('☐ Confirmed')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('No long-term corticosteroids / hormonal therapy',{},null), new TableCell({ children:[P([r('☐ Confirmed')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('No major psychiatric illness',{},null), new TableCell({ children:[P([r('☐ Confirmed')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [cell('Informed consent taken',{},null), new TableCell({ children:[P([r('☐ Yes')])], borders:singleBorder(), margins:{top:80,bottom:80,left:80,right:80}}), blankCell(10)] }),
          new TableRow({ children: [
            cell('PATIENT ELIGIBLE FOR STUDY:', { bold: true, color: 'FFFFFF' }, 'C00000'),
            new TableCell({ children:[P([r('☐ YES   ☐ NO')])], borders:singleBorder(), columnSpan:2, margins:{top:80,bottom:80,left:80,right:80} }),
          ]})
        ]
      }),

      ...empty(1),

      // ── SECTION 12: EXAMINER DECLARATION ──────────────────────────────────
      sectionHeading('SECTION 12: EXAMINER DECLARATION & SIGNATURES'),

      ...empty(1),
      P([r('I certify that the above information has been collected accurately and that the patient has given voluntary informed consent for participation in this study.')]),
      ...empty(2),

      new Table({
        width: { size: 100, type: WidthType.PERCENTAGE },
        rows: [
          new TableRow({ children: [
            new TableCell({
              children: [
                P([rb('Examiner (Scholar):')]),
                ...empty(2),
                P([r('Name: ________________________________________________')]),
                P([r('Signature: ___________________________________________')]),
                P([r('Date: ________________________________________________')]),
              ],
              borders: noBorder(), width: { size: 50, type: WidthType.PERCENTAGE }
            }),
            new TableCell({
              children: [
                P([rb('Guide / Co-Guide:')]),
                ...empty(2),
                P([r('Name: ________________________________________________')]),
                P([r('Signature: ___________________________________________')]),
                P([r('Date: ________________________________________________')]),
              ],
              borders: noBorder(), width: { size: 50, type: WidthType.PERCENTAGE }
            }),
          ]})
        ]
      }),

      ...empty(2),

      // Footer note
      new Paragraph({
        children: [new TextRun({
          text: 'CRF Version 1.0 | Study: Assessment of Deha Prakriti in Patients of Migraine — A Cross Sectional Study | SSAC, Kalol | Dept. of Rog Nidan Evum Vikriti Vigyan',
          font: SFONT, size: 16, color: '888888', italics: true
        })],
        alignment: AlignmentType.CENTER, spacing: { before: 120 }
      }),
    ]
  }]
});

Packer.toBuffer(doc).then(buf => {
  fs.writeFileSync('/home/daytona/workspace/synopsis-prakriti-migraine/CRF_Prakriti_Migraine.docx', buf);
  console.log('SUCCESS: CRF written.');
}).catch(e => { console.error('ERROR:', e); process.exit(1); });

cd /home/daytona/workspace/synopsis-prakriti-migraine && node crf.js 2>&1

~/synopsis-prakriti-migraine/crf.js

Successfully replaced 1 instance(s) of the string in '/home/daytona/workspace/synopsis-prakriti-migraine/crf.js'

cd /home/daytona/workspace/synopsis-prakriti-migraine && node crf.js 2>&1

~/synopsis-prakriti-migraine/crf.js

Successfully replaced 1 instance(s) of the string in '/home/daytona/workspace/synopsis-prakriti-migraine/crf.js'

cd /home/daytona/workspace/synopsis-prakriti-migraine && node crf.js 2>&1

cd /home/daytona/workspace/synopsis-prakriti-migraine && pandoc --track-changes=…

grep -n "SECTION\|Prakriti Scoring\|MIDAS SCORE\|VAS\|Nidana Panchaka\|ICHD-3\|E…

Prakriti body constitution PCOS polycystic ovary syndrome Ayurveda

Deha Prakriti assessment PCOS polycystic ovary syndrome Ayurveda cross sectional study India

Deha Prakriti assessment migraine Ardhavabhedaka published study India Ayurveda

Prakriti constitution PCOS Ayurveda observational study

Prakriti PCOS Artava Kshaya Pushpaghni MD thesis Shodhganga site:shodhganga.inflibnet.ac.in

"Prakriti" "PCOS" OR "polycystic" assessment cross sectional study Ayurveda journal published

Prakriti migraine Ardhavabhedaka thesis Shodhganga Ayurveda MD

site:shodhganga.inflibnet.ac.in "Prakriti" "migraine" OR "Ardhavabhedaka"

site:shodhganga.inflibnet.ac.in "Deha Prakriti" "migraine"

https://shodhganga.inflibnet.ac.in/simple-search?query=Prakr…

"Prakriti" "Ardhavabhedaka" OR "migraine" assessment study published journal AYU JAIM

https://shodhganga.inflibnet.ac.in/simple-search?query=Prakr…

"Prakriti" "Ardhavabhedaka" OR "migraine" "cross sectional" "Rog Nidan" thesis 2020 2021 2022 2023 2024

CCRAS Prakriti disease association India cross sectional

CCRAS "Prakriti" disease association study published research list

site:ccras.nic.in Prakriti disease cross sectional study

https://ccras.nic.in/services/fundamental-research

Prakriti Ayurveda disease association observational study India

Prakriti constitution disease diabetes cancer cardiovascular India published

CCRAS Prakriti published studies cancer diabetes COVID metabolic syndrome breast cancer genomics CSIR AYU journal

Prakriti Ayurveda chronic disease susceptibility cross sectional study

Prakriti disease association published studies IPGT RA Jamnagar NIA Jaipur BHU diabetes hypertension cancer thyroid psoriasis