Evidence-Based Medicine (EBM) - Complete Answers (5 Marks Each)

ls -la /home/daytona/workspace/

mkdir -p /home/daytona/workspace/ebm-notes && python3 -c "import reportlab; prin…

~/ebm-notes/generate_ebm_pdf.py

from reportlab.lib.pagesizes import A4
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
from reportlab.lib import colors
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, KeepTogether
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY

OUTPUT = "/home/daytona/workspace/ebm-notes/EBM_Clinical_Pharmacy_Notes.pdf"

doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    rightMargin=2*cm, leftMargin=2*cm,
    topMargin=2.5*cm, bottomMargin=2*cm
)

styles = getSampleStyleSheet()

# Custom styles
title_style = ParagraphStyle(
    'DocTitle', parent=styles['Title'],
    fontSize=18, textColor=colors.HexColor('#1a237e'),
    spaceAfter=4, alignment=TA_CENTER, fontName='Helvetica-Bold'
)
subtitle_style = ParagraphStyle(
    'DocSub', parent=styles['Normal'],
    fontSize=10, textColor=colors.HexColor('#455a64'),
    spaceAfter=6, alignment=TA_CENTER, fontName='Helvetica-Oblique'
)
q_heading = ParagraphStyle(
    'QHead', parent=styles['Heading1'],
    fontSize=13, textColor=colors.white,
    backColor=colors.HexColor('#1565c0'),
    spaceBefore=14, spaceAfter=6,
    leftIndent=-10, rightIndent=-10,
    borderPad=6, fontName='Helvetica-Bold',
    leading=18
)
h2_style = ParagraphStyle(
    'H2', parent=styles['Heading2'],
    fontSize=11, textColor=colors.HexColor('#0d47a1'),
    spaceBefore=8, spaceAfter=3,
    fontName='Helvetica-Bold', borderPad=2
)
h3_style = ParagraphStyle(
    'H3', parent=styles['Heading3'],
    fontSize=10, textColor=colors.HexColor('#1565c0'),
    spaceBefore=6, spaceAfter=2,
    fontName='Helvetica-Bold'
)
body = ParagraphStyle(
    'Body', parent=styles['Normal'],
    fontSize=9.5, leading=14, spaceAfter=4,
    fontName='Helvetica', alignment=TA_JUSTIFY
)
bullet = ParagraphStyle(
    'Bullet', parent=styles['Normal'],
    fontSize=9.5, leading=13, spaceAfter=2,
    leftIndent=14, fontName='Helvetica',
    bulletIndent=4
)
sub_bullet = ParagraphStyle(
    'SubBullet', parent=styles['Normal'],
    fontSize=9, leading=12, spaceAfter=2,
    leftIndent=28, fontName='Helvetica',
    bulletIndent=18
)
source_style = ParagraphStyle(
    'Source', parent=styles['Normal'],
    fontSize=8, textColor=colors.HexColor('#546e7a'),
    fontName='Helvetica-Oblique', spaceAfter=4,
    leftIndent=0, borderPad=4,
    backColor=colors.HexColor('#e3f2fd'),
    borderColor=colors.HexColor('#90caf9'),
    borderWidth=0.5, leading=11
)
note_style = ParagraphStyle(
    'Note', parent=styles['Normal'],
    fontSize=8.5, textColor=colors.HexColor('#37474f'),
    fontName='Helvetica-Oblique', spaceAfter=4,
    leftIndent=0, borderPad=6,
    backColor=colors.HexColor('#fff8e1'),
    borderColor=colors.HexColor('#ffd54f'),
    borderWidth=0.8, leading=12
)

def q_box(num, title):
    return Paragraph(f"  Q{num}. {title}", q_heading)

def h2(text):
    return Paragraph(text, h2_style)

def h3(text):
    return Paragraph(text, h3_style)

def p(text):
    return Paragraph(text, body)

def b(text):
    return Paragraph(f"• {text}", bullet)

def sb(text):
    return Paragraph(f"◦ {text}", sub_bullet)

def src(text):
    return Paragraph(f"📖 {text}", source_style)

def note(text):
    return Paragraph(f"ℹ {text}", note_style)

def hr():
    return HRFlowable(width="100%", thickness=0.5, color=colors.HexColor('#b0bec5'), spaceAfter=4)

def make_table(headers, rows, col_widths=None):
    data = [headers] + rows
    if col_widths is None:
        col_widths = [doc.width / len(headers)] * len(headers)
    hdr_style = ParagraphStyle('THdr', parent=styles['Normal'],
        fontSize=9, fontName='Helvetica-Bold', textColor=colors.white,
        alignment=TA_CENTER, leading=12)
    cell_style = ParagraphStyle('TCell', parent=styles['Normal'],
        fontSize=8.5, fontName='Helvetica', leading=12, alignment=TA_LEFT)
    formatted = []
    for i, row in enumerate(data):
        fmt_row = []
        for cell in row:
            s = hdr_style if i == 0 else cell_style
            fmt_row.append(Paragraph(str(cell), s))
        formatted.append(fmt_row)
    tbl = Table(formatted, colWidths=col_widths, repeatRows=1)
    tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1565c0')),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [colors.HexColor('#f5f5f5'), colors.white]),
        ('GRID', (0,0), (-1,-1), 0.4, colors.HexColor('#b0bec5')),
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,0), (-1,-1), 4),
        ('BOTTOMPADDING', (0,0), (-1,-1), 4),
        ('LEFTPADDING', (0,0), (-1,-1), 5),
        ('RIGHTPADDING', (0,0), (-1,-1), 5),
    ]))
    return tbl

# ─── BUILD STORY ─────────────────────────────────────────────────────────────
story = []

# TITLE BLOCK
story.append(Spacer(1, 0.3*cm))
story.append(Paragraph("Evidence-Based Medicine (EBM)", title_style))
story.append(Paragraph("Clinical Pharmacy | 5-Mark Answer Notes", subtitle_style))
story.append(Paragraph("Reference: Parthasarathy (Clinical Pharmacy) & DiPiro (Pharmacotherapy)", subtitle_style))
story.append(hr())
story.append(Spacer(1, 0.2*cm))

# ═══════════════════════════════════════════════════════════════════
# Q1
# ═══════════════════════════════════════════════════════════════════
story.append(q_box(1, "Checklist for Critical Appraisal of Articles Addressing Pharmacotherapeutic Decision"))
story.append(Spacer(1, 0.2*cm))
story.append(p("<b>Critical appraisal</b> is the systematic process of evaluating a published research article for its <b>validity, results, and relevance</b> before applying it to a pharmacotherapeutic decision."))
story.append(Spacer(1, 0.2*cm))

sections = [
    ("A. Study Question & Design", [
        "Is the clinical question clearly stated using the <b>PICO format</b> (Population, Intervention, Comparison, Outcome)?",
        "Is the study design appropriate for the question (RCT, cohort, case-control, systematic review)?",
        "Is the study design clearly mentioned in the methods section?",
    ]),
    ("B. Population / Sample", [
        "Are inclusion and exclusion criteria clearly defined?",
        "Is the sample size adequate (was a power calculation performed)?",
        "Is the patient population similar to your own patient (external validity)?",
    ]),
    ("C. Randomization & Bias Control", [
        "Was randomization performed properly (concealed allocation)?",
        "Was blinding adequate (single-blind, double-blind, or open-label)?",
        "Were the groups comparable at baseline?",
        "Was the CONSORT checklist followed (for RCTs)?",
    ]),
    ("D. Intervention (Drug/Treatment)", [
        "Is the intervention (drug, dose, route, duration) clearly described?",
        "Is the comparator (placebo or active control) appropriate?",
        "Was co-intervention or contamination avoided?",
    ]),
    ("E. Outcomes", [
        "Are primary and secondary outcomes pre-specified and clinically meaningful?",
        "Were outcomes measured in the same way in all groups?",
        "Were outcomes assessed by blinded assessors?",
    ]),
    ("F. Statistical Analysis", [
        "Was the appropriate statistical test used?",
        "Are results reported as RR, OR, NNT with confidence intervals?",
        "Was an intention-to-treat (ITT) analysis performed?",
    ]),
    ("G. Results & Applicability", [
        "Are results clinically significant (not just statistically significant)?",
        "Are all patients accounted for at follow-up (attrition bias)?",
        "Can the results be applied to your patient (generalizability)?",
        "Do benefits outweigh harms and costs?",
        "Does the evidence align with patient values and preferences?",
    ]),
]

for sec_title, items in sections:
    story.append(h3(sec_title))
    for item in items:
        story.append(b(f"☐  {item}"))

story.append(Spacer(1, 0.3*cm))
story.append(h3("Quality Reporting Tools"))
tools_data = [
    ["Tool", "Purpose"],
    ["CONSORT", "Reporting of Randomized Controlled Trials"],
    ["PRISMA", "Preferred Reporting for Systematic Reviews & Meta-Analyses"],
    ["STROBE", "Reporting of Observational Studies in Epidemiology"],
    ["AMSTAR", "Assessing quality of Systematic Reviews"],
    ["GRADE", "Grading quality of evidence & strength of recommendations"],
]
story.append(make_table(tools_data[0], tools_data[1:], col_widths=[3.5*cm, 12*cm]))
story.append(Spacer(1, 0.2*cm))
story.append(src("Source: Schwartz's Principles of Surgery 11th Ed., p. 2171; Fitzpatrick's Dermatology, p. 74"))

# ═══════════════════════════════════════════════════════════════════
# Q2
# ═══════════════════════════════════════════════════════════════════
story.append(Spacer(1, 0.3*cm))
story.append(q_box(2, "Level of Evidence and Strength of Recommendation Taxonomy in EBM"))
story.append(Spacer(1, 0.2*cm))
story.append(p("A <b>taxonomy</b> (classification system) provides a standardized framework for clinicians to judge the reliability of evidence and the strength with which a clinical recommendation should be followed. <b>Over 100 grading scales</b> exist globally; three are most widely used:"))
story.append(Spacer(1, 0.2*cm))

story.append(h2("A. SORT — Strength of Recommendation Taxonomy"))
story.append(p("Adopted by <i>American Family Physician</i>, <i>Journal of Family Practice</i>. Focuses on <b>patient-oriented outcomes</b> (symptoms, morbidity, mortality, quality of life) rather than disease-oriented surrogate markers."))
sort_data = [
    ["Grade", "Strength", "Basis"],
    ["A", "Strong", "Consistent, good-quality patient-oriented evidence"],
    ["B", "Moderate", "Inconsistent or limited-quality patient-oriented evidence"],
    ["C", "Weak", "Consensus, disease-oriented evidence, expert opinion, case series"],
]
story.append(make_table(sort_data[0], sort_data[1:], col_widths=[1.5*cm, 3*cm, 11.5*cm]))
story.append(Spacer(1, 0.3*cm))

story.append(h2("B. GRADE System (Grading of Recommendations, Assessment, Development and Evaluation)"))
story.append(p("Used by Cochrane, WHO, and many international guidelines."))
story.append(h3("Quality of Evidence Levels:"))
for item in [
    "<b>High</b> — Further research very unlikely to change confidence in estimate",
    "<b>Moderate</b> — Further research likely to change confidence",
    "<b>Low</b> — Further research very likely to change estimate",
    "<b>Very Low</b> — Very uncertain about the estimate",
]:
    story.append(b(item))

story.append(h3("Strength of Recommendation:"))
for item in [
    "<b>Strong</b> — Benefits clearly outweigh risks; most patients should receive the intervention",
    "<b>Weak/Conditional</b> — Tradeoffs less certain; decision depends on patient values",
]:
    story.append(b(item))

story.append(h3("Factors that DOWNGRADE evidence:"))
story.append(p("Risk of bias · Inconsistency · Indirectness · Imprecision · Publication bias"))
story.append(h3("Factors that UPGRADE evidence:"))
story.append(p("Large effect size · Dose-response relationship · All plausible confounders support the effect"))
story.append(Spacer(1, 0.3*cm))

story.append(h2("C. Oxford CEBM Levels of Evidence"))
cebm_data = [
    ["Level", "Evidence Type"],
    ["1a", "Systematic review of RCTs (homogeneous)"],
    ["1b", "Individual RCT with narrow confidence interval"],
    ["2a", "Systematic review of cohort studies"],
    ["2b", "Individual cohort study / low-quality RCT"],
    ["3a", "Systematic review of case-control studies"],
    ["3b", "Individual case-control study"],
    ["4", "Case series, poor-quality cohort/case-control study"],
    ["5", "Expert opinion, bench research, first principles"],
]
story.append(make_table(cebm_data[0], cebm_data[1:], col_widths=[2*cm, 14*cm]))
story.append(Spacer(1, 0.2*cm))
story.append(note("EBM Hierarchy Pyramid (highest to lowest): Systematic Reviews/Meta-analyses → RCTs → Cohort Studies → Case-Control Studies → Case Series/Case Reports → Expert Opinion/In-vitro research"))
story.append(src("Source: Fitzpatrick's Dermatology, p. 73-74; Schwartz's Principles of Surgery 11th Ed., p. 2168-2171"))

# ═══════════════════════════════════════════════════════════════════
# Q3
# ═══════════════════════════════════════════════════════════════════
story.append(Spacer(1, 0.3*cm))
story.append(q_box(3, "What is EBM? Mention the Modalities of EBM"))
story.append(Spacer(1, 0.2*cm))
story.append(h2("Definition"))
story.append(p("<b>Evidence-Based Medicine (EBM)</b> is defined as <i>"the conscientious, judicious, and explicit use of the best evidence in making decisions about the care of individual patients."</i> — Sackett et al., 1980s"))
story.append(p("EBM was formally developed in the early 1990s by proponents at <b>McMaster University</b>. It places greater emphasis on the processes by which clinicians gain knowledge of up-to-date clinical research to determine whether interventions alter disease course and improve length or quality of life."))
story.append(Spacer(1, 0.2*cm))

story.append(h2("Three Core Components of EBM"))
for item in [
    "<b>Best research evidence</b> — from valid, current clinical research",
    "<b>Clinical expertise</b> — physician's own accumulated experience and judgment",
    "<b>Patient values &amp; circumstances</b> — patient's unique preferences, values, and situation",
]:
    story.append(b(item))
story.append(Spacer(1, 0.3*cm))

story.append(h2("Modalities (Types of Evidence) in EBM"))
mod_data = [
    ["Modality", "Description"],
    ["Systematic Review", "Comprehensively summarizes available evidence using predefined reproducible search strategies; highest level in EBM hierarchy"],
    ["Meta-analysis", "Quantitatively combines data from multiple studies to produce a pooled estimate"],
    ["Randomized Controlled Trial (RCT)", "Gold standard for causation; randomly assigns subjects to intervention or control groups"],
    ["Cohort Study", "Prospective/retrospective follow-up of exposed vs unexposed groups; good for incidence and prognosis"],
    ["Case-Control Study", "Compares those with disease (cases) vs. without (controls); useful for rare diseases"],
    ["Cross-sectional Study", "Snapshot of a population at one point in time; useful for measuring prevalence"],
    ["Case Series / Case Reports", "Observations on individual patients; generates hypotheses but cannot establish causation"],
    ["Expert Opinion / Consensus", "Based on clinical experience and reasoning; lowest level in EBM hierarchy"],
    ["Clinical Practice Guidelines", "Synthesized recommendations from expert panels based on systematic evidence review"],
    ["Decision Analysis", "Mathematical modeling of clinical decisions under uncertainty"],
]
story.append(make_table(mod_data[0], mod_data[1:], col_widths=[5*cm, 11*cm]))
story.append(Spacer(1, 0.2*cm))
story.append(note("The Cochrane Database of Systematic Reviews is the prototype for the highest-level evidence resource in EBM."))
story.append(src("Source: Harrison's Principles of Internal Medicine 22nd Ed., p. 895-896; Tietz Textbook of Laboratory Medicine 7th Ed., p. 321-322"))

# ═══════════════════════════════════════════════════════════════════
# Q4
# ═══════════════════════════════════════════════════════════════════
story.append(Spacer(1, 0.3*cm))
story.append(q_box(4, "Patient-Specific Factors in the Final Analysis of EBM"))
story.append(Spacer(1, 0.2*cm))
story.append(p("The fourth key step of EBM (McMaster group) states: <i>"Integrate the appraised evidence with knowledge about the unique aspects of the patient, including the patient's preferences about possible outcomes."</i>"))
story.append(Spacer(1, 0.2*cm))

factors = [
    ("1. Clinical Factors", [
        "Patient's age, sex, weight, and comorbidities",
        "Disease severity and stage",
        "Organ function (renal, hepatic) affecting drug metabolism",
        "Allergies and prior adverse drug reactions",
        "Concurrent medications and potential drug interactions",
    ]),
    ("2. Patient Values & Preferences", [
        "Outcomes that matter most to the patient (symptom relief vs. survival vs. quality of life)",
        "Preference for aggressive vs. conservative treatment",
        "Tolerance for risk and uncertainty",
        "Cultural and religious beliefs affecting treatment choices",
    ]),
    ("3. Social & Economic Factors", [
        "Ability to afford medication (cost of treatment)",
        "Social support system and caregiver availability",
        "Adherence capability (literacy, complexity of regimen)",
        "Access to follow-up care and monitoring",
    ]),
    ("4. Evidence Applicability (External Validity)", [
        "Was the patient population in the study similar to this patient?",
        "Differences in disease prevalence, genetics, or co-morbidities",
        "Were special populations (elderly, pediatric, pregnant, renally impaired) included?",
    ]),
    ("5. Risk-Benefit Analysis", [
        "Balance between desirable effects (efficacy) and undesirable effects (ADRs, toxicity)",
        "NNT (Number Needed to Treat) vs. NNH (Number Needed to Harm)",
    ]),
    ("6. Clinical Expertise of the Physician", [
        "Physician's own experience with the treatment",
        "Recognition of clinical nuances that fall outside guideline scope",
    ]),
]

for sec_title, items in factors:
    story.append(h3(sec_title))
    for item in items:
        story.append(b(item))

story.append(Spacer(1, 0.3*cm))
story.append(h2("GRADE Framework — Factors Influencing Recommendation Strength"))
grade_data = [
    ["Factor", "Strong Recommendation (Example)", "Weak Recommendation (Example)"],
    ["Quality of evidence", "High-quality RCTs (inhaled steroids in asthma)", "Only case series available (pleurodesis in pneumothorax)"],
    ["Benefit vs. harm balance", "Clear benefit, minimal harm — Aspirin in MI reduces mortality", "Small benefit, significant risk — Warfarin in low-risk AF"],
    ["Patient values", "Young lymphoma patient uniformly values survival over toxicity", "Elderly patient may prefer quality of life over aggressive chemotherapy"],
    ["Cost / Resource use", "Low cost — Aspirin for stroke prevention in TIA", "High cost — Clopidogrel vs aspirin for stroke prophylaxis"],
]
story.append(make_table(grade_data[0], grade_data[1:], col_widths=[3.5*cm, 6.5*cm, 6*cm]))
story.append(Spacer(1, 0.2*cm))
story.append(src("Source: Harrison's Principles of Internal Medicine 22nd Ed., p. 904-905; Schwartz's Principles of Surgery 11th Ed., p. 2172-2173"))

# ═══════════════════════════════════════════════════════════════════
# Q5
# ═══════════════════════════════════════════════════════════════════
story.append(Spacer(1, 0.3*cm))
story.append(q_box(5, "Short Note on EBM Process"))
story.append(Spacer(1, 0.2*cm))
story.append(p("The process of practicing EBM follows the <b>\"A5\" cycle</b> — five sequential steps beginning with a clinical problem and ending with an evaluation of the outcome."))
story.append(Spacer(1, 0.2*cm))

steps = [
    ("Step 1: ASK — Formulate the Clinical Question", [
        "Convert the clinical problem into an answerable question using the <b>PICO format</b>:",
        "P — Patient/Population (who is the patient?)",
        "I — Intervention (what drug/test/procedure is being considered?)",
        "C — Comparison (what is the alternative/comparator?)",
        "O — Outcome (what are the desired/measured outcomes?)",
        "Example: In a 65-year-old patient with heart failure (P), does NT-proBNP testing (I) vs. clinical assessment alone (C) improve diagnostic accuracy (O)?",
    ]),
    ("Step 2: ACQUIRE — Search for Evidence", [
        "Systematically search the medical literature and online databases",
        "Sources: PubMed/MEDLINE, Cochrane Database, EMBASE, CINAHL",
        "Use structured search strategies with MeSH terms",
        "Identify the most current and relevant studies",
    ]),
    ("Step 3: APPRAISE — Critical Appraisal of Evidence", [
        "Evaluate the validity, importance, and applicability of retrieved studies",
        "Use quality appraisal tools: CONSORT (RCTs), PRISMA (systematic reviews), STROBE (observational studies)",
        "Assess for study design quality, sample size, bias, and statistical validity",
        "Grade the level of evidence using CEBM, GRADE, or SORT system",
    ]),
    ("Step 4: APPLY — Apply Evidence to the Patient", [
        "Integrate best evidence with clinical expertise and patient-specific factors",
        "Consider patient preferences, values, comorbidities, and cost",
        "Formulate the pharmacotherapeutic or clinical decision",
    ]),
    ("Step 5: AUDIT — Evaluate the Outcome", [
        "Assess whether the applied evidence achieved the expected clinical outcome",
        "Self-audit of the EBM decision-making process",
        "Feedback loop to improve future EBM practice",
    ]),
]

for step_title, items in steps:
    story.append(h3(step_title))
    for i, item in enumerate(items):
        if i == 0 and "PICO" in step_title or ("P —" in item or "I —" in item or "C —" in item or "O —" in item or "Example:" in item):
            story.append(sb(item))
        else:
            story.append(b(item))

story.append(Spacer(1, 0.3*cm))
story.append(h2("A5 EBM Cycle Summary"))
cycle_data = [
    ["Step", "Activity", "Key Action"],
    ["A1 — ASK", "Formulate the Question", "PICO format"],
    ["A2 — ACQUIRE", "Search Literature", "PubMed, Cochrane, EMBASE"],
    ["A3 — APPRAISE", "Critical Appraisal", "CONSORT, PRISMA, GRADE, SORT"],
    ["A4 — APPLY", "Apply to Patient", "Integrate evidence + expertise + patient values"],
    ["A5 — AUDIT", "Evaluate Outcome", "Feedback loop for continuous improvement"],
]
story.append(make_table(cycle_data[0], cycle_data[1:], col_widths=[4*cm, 5*cm, 7*cm]))
story.append(Spacer(1, 0.2*cm))

story.append(h2("Importance of EBM Process in Pharmacotherapy"))
for item in [
    "Reduces practice variability and dependence on anecdotal experience",
    "Supports rational drug selection and evidence-based dosing decisions",
    "Helps integrate current research with individual patient needs",
    "Promotes lifelong learning and professional development in clinical pharmacy",
    "Reduces cognitive bias in clinical decision-making",
    "Improves patient outcomes by using the highest quality evidence available",
]:
    story.append(b(item))

story.append(Spacer(1, 0.2*cm))
story.append(src("Source: Tietz Textbook of Laboratory Medicine 7th Ed., p. 321-323 (A5 Cycle); Harrison's Principles of Internal Medicine 22nd Ed., p. 895-896; Schwartz's Principles of Surgery 11th Ed., p. 2168-2170"))

story.append(Spacer(1, 0.4*cm))
story.append(hr())
story.append(Paragraph(
    "References: Parthasarathy S. — A Textbook of Clinical Pharmacy Practice; DiPiro JT et al. — Pharmacotherapy: A Pathophysiologic Approach; "
    "Harrison's Principles of Internal Medicine 22nd Ed.; Schwartz's Principles of Surgery 11th Ed.; "
    "Tietz Textbook of Laboratory Medicine 7th Ed.; Fitzpatrick's Dermatology.",
    ParagraphStyle('Refs', parent=styles['Normal'], fontSize=7.5, textColor=colors.HexColor('#607d8b'),
                   fontName='Helvetica-Oblique', leading=11, spaceAfter=0)
))

# ─── BUILD ───────────────────────────────────────────────────────────────────
doc.build(story)
print(f"PDF generated: {OUTPUT}")

cd /home/daytona/workspace/ebm-notes && python3 generate_ebm_pdf.py

~/ebm-notes/generate_ebm_pdf.py

Successfully replaced 1 instance(s) of the string in '/home/daytona/workspace/ebm-notes/generate_ebm_pdf.py'

cd /home/daytona/workspace/ebm-notes && python3 generate_ebm_pdf.py

cd /home/daytona/workspace/ebm-notes && python3 -c " content = open('generate_eb…

cd /home/daytona/workspace/ebm-notes && python3 generate_ebm_pdf.py

cd /home/daytona/workspace/ebm-notes && python3 -c " content = open('generate_eb…

cd /home/daytona/workspace/ebm-notes && python3 -c " import ast with open('gener…

cd /home/daytona/workspace/ebm-notes && python3 << 'PYEOF' with open('generate_e…

cd /home/daytona/workspace/ebm-notes && python3 -c " import ast with open('gener…

cd /home/daytona/workspace/ebm-notes && python3 generate_ebm_pdf.py

ls -lh /home/daytona/workspace/ebm-notes/EBM_Clinical_Pharmacy_Notes.pdf