cd /tmp/workspace && python3 -c " import pdfplumber text = '' with pdfplumber.open('/tmp/workspace/attachments/09a158b1-7ee9-4f6e-9524-7d3c34cc595d/12871_2023_Article_2360.pdf') as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): t = page.extract_text() if t: text += f'\n\n--- PAGE {i+1} ---\n' + t print(text[:8000]) "

cd /tmp/workspace && python3 -c " import pdfplumber text = '' with pdfplumber.open('/tmp/workspace/attachments/09a158b1-7ee9-4f6e-9524-7d3c34cc595d/12871_2023_Article_2360.pdf') as pdf: for i, page in enumerate(pdf.pages): t = page.extract_text() if t: text += f'\n\n--- PAGE {i+1} ---\n' + t print(text[8000:]) "

mkdir -p /tmp/workspace/gdft-journal-club && cat > /tmp/workspace/gdft-journal-club/build_pptx.py << 'PYEOF' from pptx import Presentation from pptx.util import Inches, Pt, Emu from pptx.dml.color import RGBColor from pptx.enum.text import PP_ALIGN, MSO_ANCHOR from pptx.util import Inches, Pt import copy # ── Colour palette ────────────────────────────────────────────── NAVY = RGBColor(0x0D, 0x3B, 0x66) # deep navy – slide headers / accent bar TEAL = RGBColor(0x15, 0x7A, 0xB3) # mid-blue – sub-headings MINT = RGBColor(0xE8, 0xF4, 0xFD) # very light blue – body bg WHITE = RGBColor(0xFF, 0xFF, 0xFF) DARK = RGBColor(0x1A, 0x1A, 0x2E) # near-black text ACCENT = RGBColor(0x00, 0xB4, 0xA6) # teal-green – key stats / highlights LIGHT_GREY = RGBColor(0xF0, 0xF4, 0xF8) MID_GREY = RGBColor(0xCC, 0xD6, 0xE0) GREEN = RGBColor(0x27, 0xAE, 0x60) RED = RGBColor(0xC0, 0x39, 0x2B) AMBER = RGBColor(0xF3, 0x9C, 0x12) W = Inches(13.333) H = Inches(7.5) prs = Presentation() prs.slide_width = W prs.slide_height = H blank = prs.slide_layouts[6] # ── Helper utilities ───────────────────────────────────────────── def bg(slide, color): from pptx.util import Emu from lxml import etree fill = slide.background.fill fill.solid() fill.fore_color.rgb = color def rect(slide, l, t, w, h, fill_color, line_color=None, line_width=Pt(0)): shape = slide.shapes.add_shape(1, l, t, w, h) # MSO_SHAPE_TYPE.RECTANGLE=1 shape.fill.solid() shape.fill.fore_color.rgb = fill_color if line_color: shape.line.color.rgb = line_color shape.line.width = line_width else: shape.line.fill.background() return shape def textbox(slide, l, t, w, h, txt, size=Pt(18), bold=False, color=DARK, align=PP_ALIGN.LEFT, word_wrap=True, italic=False, v_anchor=MSO_ANCHOR.TOP): tb = slide.shapes.add_textbox(l, t, w, h) tf = tb.text_frame tf.word_wrap = word_wrap tf.vertical_anchor = v_anchor tf.margin_left = Inches(0.05) tf.margin_right = Inches(0.05) tf.margin_top = Inches(0.03) tf.margin_bottom= Inches(0.03) p = tf.paragraphs[0] p.alignment = align run = p.add_run() run.text = txt run.font.size = size run.font.bold = bold run.font.italic= italic run.font.color.rgb = color run.font.name = "Calibri" return tf def add_para(tf, txt, size=Pt(16), bold=False, color=DARK, align=PP_ALIGN.LEFT, italic=False, space_before=Pt(4)): from pptx.oxml.ns import qn p = tf.add_paragraph() p.alignment = align p.space_before = space_before run = p.add_run() run.text = txt run.font.size = size run.font.bold = bold run.font.italic= italic run.font.color.rgb = color run.font.name = "Calibri" return p def header_bar(slide, title, subtitle=None): """Top navy bar with white title.""" rect(slide, 0, 0, W, Inches(1.25), NAVY) textbox(slide, Inches(0.4), Inches(0.12), Inches(12.5), Inches(0.7), title, size=Pt(28), bold=True, color=WHITE, align=PP_ALIGN.LEFT, v_anchor=MSO_ANCHOR.MIDDLE) if subtitle: textbox(slide, Inches(0.4), Inches(0.78), Inches(12.5), Inches(0.38), subtitle, size=Pt(14), bold=False, color=MINT, align=PP_ALIGN.LEFT, v_anchor=MSO_ANCHOR.TOP) def footer(slide, txt="Sun et al. BMC Anesthesiology 2023;23:397"): rect(slide, 0, Inches(7.1), W, Inches(0.4), NAVY) textbox(slide, Inches(0.3), Inches(7.12), Inches(12.7), Inches(0.32), txt, size=Pt(9), bold=False, color=MID_GREY, align=PP_ALIGN.LEFT, v_anchor=MSO_ANCHOR.MIDDLE) def stat_box(slide, l, t, w, h, value, label, val_color=ACCENT): rect(slide, l, t, w, h, WHITE, MID_GREY, Pt(1.5)) textbox(slide, l+Inches(0.1), t+Inches(0.12), w-Inches(0.2), Inches(0.65), value, size=Pt(30), bold=True, color=val_color, align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE) textbox(slide, l+Inches(0.08), t+Inches(0.72), w-Inches(0.16), h-Inches(0.82), label, size=Pt(12), bold=False, color=DARK, align=PP_ALIGN.CENTER, word_wrap=True) def bullet_tf(slide, l, t, w, h, items, size=Pt(15.5), color=DARK, bullet="• ", indent=0, bg_col=None): if bg_col: rect(slide, l, t, w, h, bg_col) tb = slide.shapes.add_textbox(l+Inches(0.1), t+Inches(0.1), w-Inches(0.2), h-Inches(0.15)) tf = tb.text_frame tf.word_wrap = True tf.vertical_anchor = MSO_ANCHOR.TOP tf.margin_left = Inches(0.05) tf.margin_right = Inches(0.05) tf.margin_top = Inches(0.05) tf.margin_bottom= Inches(0.05) first = True for item in items: if first: p = tf.paragraphs[0]; first = False else: p = tf.add_paragraph() p.alignment = PP_ALIGN.LEFT p.space_before = Pt(5) run = p.add_run() run.text = bullet + item run.font.size = size run.font.color.rgb = color run.font.name = "Calibri" return tf # ════════════════════════════════════════════════════════════════ # SLIDE 1 – TITLE SLIDE # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, NAVY) # accent stripe rect(sl, 0, Inches(2.7), Inches(0.18), Inches(2.2), ACCENT) # Journal club label textbox(sl, Inches(0.5), Inches(0.5), Inches(12), Inches(0.5), "JOURNAL CLUB PRESENTATION · BMC ANESTHESIOLOGY 2023", size=Pt(13), bold=False, color=MINT, align=PP_ALIGN.LEFT) # Main title tb = sl.shapes.add_textbox(Inches(0.5), Inches(1.2), Inches(12.3), Inches(2.2)) tf = tb.text_frame; tf.word_wrap = True p = tf.paragraphs[0]; p.alignment = PP_ALIGN.LEFT run = p.add_run() run.text = "Goal-Directed Fluid Therapy Using" run.font.size = Pt(38); run.font.bold = True; run.font.color.rgb = WHITE; run.font.name = "Calibri" add_para(tf, "Stroke Volume Variation (SVV)", size=Pt(38), bold=True, color=WHITE, space_before=Pt(2)) add_para(tf, "on Length of Stay and Postoperative GI Function", size=Pt(30), bold=False, color=MINT, space_before=Pt(4)) add_para(tf, "After Major Abdominal Surgery", size=Pt(30), bold=False, color=MINT, space_before=Pt(2)) # Sub info textbox(sl, Inches(0.5), Inches(3.55), Inches(12), Inches(0.45), "A Randomised Controlled Trial", size=Pt(18), bold=True, color=ACCENT, align=PP_ALIGN.LEFT) textbox(sl, Inches(0.5), Inches(4.05), Inches(12), Inches(0.38), "Sun Y, Liang X, Chai F, Shi D, Wang Y | Beijing Tongren Hospital, China", size=Pt(14), bold=False, color=MID_GREY, align=PP_ALIGN.LEFT) # divider rect(sl, Inches(0.5), Inches(4.52), Inches(6), Inches(0.04), MID_GREY) textbox(sl, Inches(0.5), Inches(4.65), Inches(12), Inches(0.6), "Presented by: ____________________ Date: ____________________", size=Pt(13), bold=False, color=MID_GREY, align=PP_ALIGN.LEFT) # bottom strip rect(sl, 0, Inches(7.1), W, Inches(0.4), RGBColor(0x07, 0x27, 0x48)) textbox(sl, Inches(0.3), Inches(7.12), Inches(12.7), Inches(0.32), "DOI: 10.1186/s12871-023-02360-1 · Registered: NCT03940144", size=Pt(9), bold=False, color=MID_GREY, align=PP_ALIGN.CENTER) # ════════════════════════════════════════════════════════════════ # SLIDE 2 – AGENDA # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Agenda", "What we will cover today") footer(sl) items = [ "1. Background & Clinical Problem", "2. What is Goal-Directed Fluid Therapy (GDFT)?", "3. What is SVV? – The FloTrac/Vigileo System", "4. Study Rationale & Aims", "5. Study Design & Methods", "6. Patient Population & Randomisation", "7. Fluid Protocols – GDFT vs Conventional", "8. Outcome Measures (Primary & Secondary)", "9. Results – Baseline Characteristics", "10. Results – Intraoperative Fluid Use", "11. Results – Primary Outcomes", "12. Results – Secondary Outcomes", "13. I-FEED Scoring System Explained", "14. Critical Appraisal – Strengths & Limitations", "15. Discussion & How it Fits in the Literature", "16. Clinical Implications", "17. Take-Home Messages", "18. Questions & Discussion", ] bullet_tf(sl, Inches(0.5), Inches(1.35), Inches(6.1), Inches(5.9), items[:9], size=Pt(14.5), color=DARK) bullet_tf(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(5.9), items[9:], size=Pt(14.5), color=DARK) # ════════════════════════════════════════════════════════════════ # SLIDE 3 – BACKGROUND & CLINICAL PROBLEM # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Background & Clinical Problem") footer(sl) # Left panel rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(5.5), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(0.5), Inches(1.42), Inches(5.8), Inches(0.45), "Why does this matter?", size=Pt(16), bold=True, color=TEAL) bullet_tf(sl, Inches(0.45), Inches(1.9), Inches(5.9), Inches(4.8), ["Prolonged hospital stay increases costs, readmission risk, and short-term mortality", "Postoperative GI Dysfunction (POGD) is the leading cause of prolonged stay after major abdominal surgery", "Appropriate perioperative fluid management is known to improve GI function", "Static measures (CVP, MAP) are poor predictors of fluid responsiveness", "Over-hydration causes gut interstitial oedema and inhibits GI transit", "Under-hydration causes mucosal hypoperfusion → apoptosis at villus tips → ~3 days to recover"], size=Pt(14.5), color=DARK) # Right panel rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(5.5), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(6.95), Inches(1.42), Inches(5.8), Inches(0.45), "The Fluid Dilemma", size=Pt(16), bold=True, color=TEAL) # Goldilocks diagram with shapes rect(sl, Inches(7.1), Inches(2.05), Inches(5.6), Inches(0.65), RED) textbox(sl, Inches(7.1), Inches(2.05), Inches(5.6), Inches(0.65), "TOO LITTLE FLUID → Hypovolaemia → Gut Ischaemia", size=Pt(13), bold=True, color=WHITE, align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE) rect(sl, Inches(7.1), Inches(2.9), Inches(5.6), Inches(0.65), GREEN) textbox(sl, Inches(7.1), Inches(2.9), Inches(5.6), Inches(0.65), "JUST RIGHT → Optimal Perfusion → GDFT Target", size=Pt(13), bold=True, color=WHITE, align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE) rect(sl, Inches(7.1), Inches(3.75), Inches(5.6), Inches(0.65), AMBER) textbox(sl, Inches(7.1), Inches(3.75), Inches(5.6), Inches(0.65), "TOO MUCH FLUID → Oedema → Ileus / POGD", size=Pt(13), bold=True, color=WHITE, align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE) textbox(sl, Inches(6.95), Inches(4.6), Inches(5.8), Inches(2.0), "Traditional markers (CVP 8-12 mmHg, MAP 65-90 mmHg) are static and do NOT reliably predict whether a patient will respond to a fluid bolus.", size=Pt(13.5), bold=False, color=DARK, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 4 – WHAT IS GDFT? # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "What is Goal-Directed Fluid Therapy (GDFT)?") footer(sl) textbox(sl, Inches(0.4), Inches(1.35), Inches(12.5), Inches(0.42), "GDFT monitors DYNAMIC haemodynamic indices to guide fluid and drug administration, targeting optimal oxygen delivery (DO₂) and organ perfusion.", size=Pt(15), bold=False, color=DARK, word_wrap=True) # 3 boxes for i, (title, body, col) in enumerate([ ("PRINCIPLE", "Give fluids only when the patient will respond (i.e., is preload-dependent). Stop when they won't.", TEAL), ("DYNAMIC INDICES", "SVV, PPV, Stroke Volume (SV) – all respond to the heart-lung interaction during mechanical ventilation to reveal fluid responsiveness.", NAVY), ("GOALS IN THIS STUDY", "SVV ≤ 12% (fluid-replete)\nCardiac Index (CI) ≥ 2.5 L/min/m²\nMAP ≥ 65 mmHg", ACCENT), ]): x = Inches(0.35) + i * Inches(4.35) rect(sl, x, Inches(2.0), Inches(4.15), Inches(4.7), col) textbox(sl, x+Inches(0.15), Inches(2.1), Inches(3.85), Inches(0.5), title, size=Pt(15), bold=True, color=WHITE, align=PP_ALIGN.CENTER) rect(sl, x+Inches(0.1), Inches(2.65), Inches(3.95), Inches(3.9), WHITE) textbox(sl, x+Inches(0.2), Inches(2.75), Inches(3.75), Inches(3.75), body, size=Pt(14.5), bold=False, color=DARK, word_wrap=True) textbox(sl, Inches(0.4), Inches(6.75), Inches(12.5), Inches(0.3), "GDFT has been shown to reduce hospital stay and GI complications especially in high-risk patients (Sun et al. Crit Care 2017; Giglio et al. BJA 2009).", size=Pt(12), bold=False, color=TEAL, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 5 – SVV & FloTrac/Vigileo # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Stroke Volume Variation (SVV) & The FloTrac/Vigileo System") footer(sl) # Left rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(5.55), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(0.5), Inches(1.42), Inches(5.8), Inches(0.45), "What is SVV?", size=Pt(16), bold=True, color=TEAL) bullet_tf(sl, Inches(0.45), Inches(1.9), Inches(5.9), Inches(5.0), ["SVV = the % variation in stroke volume over one respiratory cycle during mechanical ventilation", "Formula: SVV (%) = (SV max − SV min) / SV mean × 100", "SVV > 12% → patient is preload-dependent → will respond to fluids", "SVV ≤ 12% → patient is preload-independent → fluids unlikely to help", "Only valid during controlled mechanical ventilation with sinus rhythm and tidal volume ≥ 8 ml/kg", "Dynamic index – far superior to static CVP or filling pressures"], size=Pt(14), color=DARK) # Right rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(5.55), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(6.95), Inches(1.42), Inches(5.8), Inches(0.45), "FloTrac/Vigileo Monitor", size=Pt(16), bold=True, color=TEAL) bullet_tf(sl, Inches(6.9), Inches(1.9), Inches(5.9), Inches(2.8), ["Minimally invasive – uses existing RADIAL ARTERIAL LINE", "Pulse contour analysis from arterial waveform (no calibration needed)", "Provides continuous beat-to-beat SVV, SV, CO and CI", "Less invasive than oesophageal Doppler or pulmonary artery catheter", "Software version 1.14 (Edwards Lifesciences) used in this study"], size=Pt(14), color=DARK) # SVV threshold highlight box rect(sl, Inches(6.9), Inches(4.8), Inches(5.85), Inches(1.9), NAVY) textbox(sl, Inches(6.95), Inches(4.85), Inches(5.75), Inches(1.8), "Key Threshold Used in This Study:\n\nSVV > 12% for > 5 minutes → give 250 mL crystalloid bolus\nIf SVV still > 12% or drops > 10% → give 250 mL colloid\nCI < 2.5 → start inotropes", size=Pt(13), bold=False, color=WHITE, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 6 – STUDY RATIONALE & AIMS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Study Rationale & Aims") footer(sl) rect(sl, Inches(0.35), Inches(1.35), Inches(12.6), Inches(1.35), NAVY) textbox(sl, Inches(0.5), Inches(1.42), Inches(12.3), Inches(1.2), "Gap in Evidence: GDFT benefits are well-established in HIGH-RISK patients. However, whether GDFT helps LOW-TO-MODERATE risk patients undergoing major abdominal surgery remains controversial.", size=Pt(16), bold=False, color=WHITE, word_wrap=True) textbox(sl, Inches(0.4), Inches(2.9), Inches(5.0), Inches(0.4), "Primary Aims:", size=Pt(16), bold=True, color=TEAL) bullet_tf(sl, Inches(0.35), Inches(3.38), Inches(5.9), Inches(3.3), ["Does GDFT (guided by SVV + CI) shorten hospital length of stay?", "Does GDFT reduce postoperative GI dysfunction (POGD)?", "Does GDFT speed return of GI function (flatus, oral diet)?"], size=Pt(15), color=DARK, bg_col=WHITE) textbox(sl, Inches(6.8), Inches(2.9), Inches(5.0), Inches(0.4), "Secondary Aims:", size=Pt(16), bold=True, color=TEAL) bullet_tf(sl, Inches(6.8), Inches(3.38), Inches(6.15), Inches(3.3), ["Effect on serum lactate and blood glucose", "Quality of Recovery (QoR-40) scores at day 1, 3, 5", "Time to first mobilisation", "Postoperative complications and 30-day mortality"], size=Pt(15), color=DARK, bg_col=WHITE) # ════════════════════════════════════════════════════════════════ # SLIDE 7 – STUDY DESIGN # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Study Design & Setting") footer(sl) # Info cards row design_items = [ ("Design", "Single-centre\nProspective RCT\nPartly blinded"), ("Setting", "Beijing Tongren Hospital\n(Tertiary university\naffiliated hospital)"), ("Period", "May 2019 –\nJan 2021"), ("Registration", "ClinicalTrials.gov\nNCT03940144\n(Registered 07/05/2019)"), ("Ethics", "Approved: TR-IRB\n20170828\nDeclaration of Helsinki"), ] for i, (lbl, val) in enumerate(design_items): x = Inches(0.35) + i * Inches(2.6) rect(sl, x, Inches(1.35), Inches(2.45), Inches(2.2), NAVY) textbox(sl, x+Inches(0.1), Inches(1.4), Inches(2.25), Inches(0.45), lbl, size=Pt(13), bold=True, color=ACCENT, align=PP_ALIGN.CENTER) rect(sl, x+Inches(0.08), Inches(1.88), Inches(2.3), Inches(1.55), WHITE) textbox(sl, x+Inches(0.12), Inches(1.93), Inches(2.2), Inches(1.45), val, size=Pt(13), bold=False, color=DARK, align=PP_ALIGN.CENTER, word_wrap=True) # CONSORT flow description box rect(sl, Inches(0.35), Inches(3.75), Inches(12.6), Inches(3.05), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(0.5), Inches(3.82), Inches(12.3), Inches(0.38), "CONSORT Flow Summary", size=Pt(16), bold=True, color=TEAL) # Flow boxes for i, (n, lbl, col) in enumerate([ ("110", "Patients Recruited\n& Randomised", TEAL), ("10", "Excluded After\nRandomisation\n(3 surgery cancelled,\n4 withdrew consent,\n3 arrhythmia found)", RED), ("50", "Group G\n(GDFT – SVV guided)", GREEN), ("50", "Group C\n(Conventional:\nMAP + CVP guided)", AMBER), ("100", "Completed\n& Analysed\n(Modified ITT)", NAVY), ]): x = Inches(0.5) + i * Inches(2.56) rect(sl, x, Inches(4.3), Inches(2.4), Inches(2.2), col) textbox(sl, x+Inches(0.1), Inches(4.35), Inches(2.2), Inches(0.65), n, size=Pt(26), bold=True, color=WHITE, align=PP_ALIGN.CENTER) textbox(sl, x+Inches(0.1), Inches(4.95), Inches(2.2), Inches(1.45), lbl, size=Pt(12), bold=False, color=WHITE, align=PP_ALIGN.CENTER, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 8 – PATIENT POPULATION # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Patient Population – Inclusion & Exclusion Criteria") footer(sl) # Inclusion rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(5.55), WHITE, MID_GREY, Pt(1)) rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(0.48), GREEN) textbox(sl, Inches(0.4), Inches(1.38), Inches(6.0), Inches(0.42), "✔ INCLUSION CRITERIA", size=Pt(15), bold=True, color=WHITE) bullet_tf(sl, Inches(0.45), Inches(1.9), Inches(5.9), Inches(5.0), ["Adults (≥18 yrs) undergoing elective major abdominal surgery", "General anaesthesia planned", "Surgery listed for GI, gynaecologic, or urologic cancer resection", "Risk for significant surgical blood loss (major procedures: gastrectomy, Whipple, hemicolectomy, rectal resection, radical cystectomy/prostatectomy, etc.)", "Written informed consent obtained", "Enrolled May 2019 – Jan 2021"], size=Pt(14), color=DARK) # Exclusion rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(5.55), WHITE, MID_GREY, Pt(1)) rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(0.48), RED) textbox(sl, Inches(6.85), Inches(1.38), Inches(6.0), Inches(0.42), "✘ EXCLUSION CRITERIA", size=Pt(15), bold=True, color=WHITE) bullet_tf(sl, Inches(6.9), Inches(1.9), Inches(5.9), Inches(5.0), ["Congestive heart failure", "Chronic lung disease", "Renal dysfunction (creatinine > 50% of normal)", "Hepatic dysfunction (liver enzymes > 50% of normal)", "Cardiac arrhythmias (SVV unreliable with irregular rhythm)", "Age < 18 years", "Pregnancy or lactation", "Previous oesophageal or gastric surgery", "Emergency surgery"], size=Pt(14), color=DARK) # ════════════════════════════════════════════════════════════════ # SLIDE 9 – FLUID PROTOCOLS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Intraoperative Fluid Protocols – Side by Side") footer(sl) # GDFT column rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(5.55), WHITE, MID_GREY, Pt(1)) rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(0.48), GREEN) textbox(sl, Inches(0.4), Inches(1.38), Inches(6.0), Inches(0.42), "GROUP G – GDFT (SVV + CI Guided)", size=Pt(14), bold=True, color=WHITE) steps_G = [ "Induction: 500 mL crystalloid bolus + 4 mL/kg/h maintenance", "Assess SVV & CI every 5 minutes via FloTrac/Vigileo", "SVV > 12% for > 5 min → give 250 mL crystalloid", "If SVV still > 12% or drops > 10% → give 250 mL colloid", "CI < 2.5 L/min/m² → start inotropes", "MAP < 65 mmHg (with SVV/CI in target) → start vasopressor", "External SVV changes (position, pneumoperitoneum, vent changes) noted but do NOT trigger fluid", "Post-op PACU: 1 mL/kg/h + GDFT boluses continued", ] bullet_tf(sl, Inches(0.45), Inches(1.9), Inches(5.9), Inches(4.8), steps_G, size=Pt(13.5), color=DARK) # Control column rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(5.55), WHITE, MID_GREY, Pt(1)) rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(0.48), AMBER) textbox(sl, Inches(6.85), Inches(1.38), Inches(6.0), Inches(0.42), "GROUP C – Conventional (MAP + CVP Guided)", size=Pt(14), bold=True, color=WHITE) steps_C = [ "Induction: 500 mL crystalloid bolus + 4 mL/kg/h maintenance", "Targets: MAP 65–90 mmHg & CVP 8–12 mmHg", "MAP < 65 mmHg or CVP < 8 mmHg → give 250 mL crystalloid", "If CVP still < 8 after 5 min → give 250 mL colloid", "MAP < 65 mmHg unresponsive to fluids → vasopressor / inotrope", "Post-op PACU: 1 mL/kg/h crystalloid only", "NO cardiac output monitoring in group C", ] bullet_tf(sl, Inches(6.9), Inches(1.9), Inches(5.9), Inches(4.8), steps_C, size=Pt(13.5), color=DARK) # ════════════════════════════════════════════════════════════════ # SLIDE 10 – I-FEED SCORING SYSTEM # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "I-FEED Scoring System – Measuring GI Function") footer(sl) textbox(sl, Inches(0.4), Inches(1.35), Inches(12.5), Inches(0.42), "The I-FEED score (Intake, Feeling Nauseated, Emesis, physical Exam, Duration) was endorsed by ERAS/POQI 2018 consensus to standardise the definition of postoperative GI dysfunction.", size=Pt(14), bold=False, color=DARK, word_wrap=True) # Table headers = ["Domain", "0 Points", "1 Point", "2 Points"] rows = [ ["Intake", "Tolerating oral diet", "Limited tolerance", "Complete intolerance"], ["Nausea", "None", "Responsive to treatment", "Resistant to treatment"], ["Emesis", "None", "≥1 episode low volume\n(<100 mL), non-bilious", "≥1 episode high volume\n(>100 mL) or bilious"], ["Exam", "No distension", "Distension without tympany", "Significant distension\nwith tympany"], ["Duration", "0–24 h", "24–72 h", ">72 h"], ] cols_w = [Inches(2.2), Inches(3.2), Inches(3.5), Inches(3.8)] row_h = Inches(0.72) t_top = Inches(1.9) t_left = Inches(0.35) # Header row for ci, (hdr, cw) in enumerate(zip(headers, cols_w)): x = t_left + sum(cols_w[:ci]) rect(sl, x, t_top, cw, Inches(0.48), NAVY) textbox(sl, x+Inches(0.05), t_top+Inches(0.04), cw-Inches(0.1), Inches(0.4), hdr, size=Pt(13), bold=True, color=WHITE, align=PP_ALIGN.CENTER) # Data rows for ri, row in enumerate(rows): y = t_top + Inches(0.48) + ri * row_h bg_c = MINT if ri % 2 == 0 else WHITE for ci, (cell, cw) in enumerate(zip(row, cols_w)): x = t_left + sum(cols_w[:ci]) rect(sl, x, y, cw, row_h, bg_c, MID_GREY, Pt(0.5)) textbox(sl, x+Inches(0.07), y+Inches(0.05), cw-Inches(0.14), row_h-Inches(0.1), cell, size=Pt(12.5), bold=(ci==0), color=DARK if ci>0 else NAVY, align=PP_ALIGN.CENTER, word_wrap=True) # Category labels y_cat = t_top + Inches(0.48) + len(rows)*row_h + Inches(0.1) for cat, col, rng in [("Normal (0–2): no action needed", GREEN, "Score 0-2"), ("POGI (3–5): postoperative GI intolerance", AMBER, "Score 3-5"), ("POGD (≥6): postoperative GI dysfunction", RED, "Score ≥ 6")]: rect(sl, t_left, y_cat, Inches(12.6), Inches(0.36), col) textbox(sl, t_left+Inches(0.1), y_cat+Inches(0.04), Inches(12.4), Inches(0.32), cat, size=Pt(13), bold=True, color=WHITE) y_cat += Inches(0.38) # ════════════════════════════════════════════════════════════════ # SLIDE 11 – BASELINE CHARACTERISTICS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Results – Baseline Characteristics (Table 2)") footer(sl) rect(sl, Inches(0.35), Inches(1.35), Inches(12.6), Inches(0.38), TEAL) textbox(sl, Inches(0.4), Inches(1.38), Inches(12.3), Inches(0.32), "Both groups were WELL MATCHED – no significant differences in any baseline variable (p > 0.05 for all)", size=Pt(13), bold=True, color=WHITE) # Table hdrs2 = ["Variable", "Control (n=50)", "GDFT (n=50)", "P value"] cw2 = [Inches(4.5), Inches(2.8), Inches(2.8), Inches(2.0)] data2 = [ ["Age (mean ± SD)", "59.2 ± 13.1 yrs", "64.0 ± 14.0 yrs", "0.068"], ["Sex (Male/Female)", "34/16 (68%/32%)", "32/18 (64%/36%)", "0.671"], ["BMI (mean ± SD)", "23.8 ± 3.2", "23.0 ± 3.4", "0.208"], ["ASA I/II/III", "8/33/9", "6/36/8", "0.791"], ["Anaesthesia duration", "250.8 ± 91.0 min", "225.5 ± 87.2 min", "0.195"], ["P-POSSUM physiol. score", "15.6 ± 2.8", "14.9 ± 3.2", "0.685"], ["P-POSSUM operative score","13.4 ± 4.1", "14.2 ± 3.8", "0.779"], ["Laparoscopy/Open", "31/19 (62%/38%)", "38/12 (76%/24%)", "0.134"], ] t_top2 = Inches(1.85) rect(sl, Inches(0.35), t_top2, sum(cw2), Inches(0.45), NAVY) for ci, (h, cw) in enumerate(zip(hdrs2, cw2)): x = Inches(0.35) + sum(cw2[:ci]) textbox(sl, x+Inches(0.05), t_top2+Inches(0.04), cw-Inches(0.1), Inches(0.38), h, size=Pt(12.5), bold=True, color=WHITE, align=PP_ALIGN.CENTER) for ri, row in enumerate(data2): y = t_top2 + Inches(0.45) + ri * Inches(0.54) bg_c = MINT if ri % 2 == 0 else WHITE for ci, (cell, cw) in enumerate(zip(row, cw2)): x = Inches(0.35) + sum(cw2[:ci]) rect(sl, x, y, cw, Inches(0.54), bg_c, MID_GREY, Pt(0.4)) col2 = GREEN if (ci==3 and float(cell) > 0.05) else DARK textbox(sl, x+Inches(0.07), y+Inches(0.05), cw-Inches(0.14), Inches(0.44), cell, size=Pt(12), bold=(ci==0), color=col2, align=PP_ALIGN.CENTER if ci>0 else PP_ALIGN.LEFT, word_wrap=True) textbox(sl, Inches(0.35), Inches(6.6), Inches(12.6), Inches(0.42), "✔ Balanced randomisation confirmed – any differences in outcomes are attributable to the fluid strategy, not baseline differences.", size=Pt(13), bold=False, color=TEAL, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 12 – INTRAOPERATIVE FLUIDS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Results – Intraoperative Fluid Management (Table 3)") footer(sl) # Stat boxes stats = [ ("2750 mL", "Median total fluid\nGroup C (Control)", AMBER), ("1975 mL", "Median total fluid\nGroup G (GDFT)", GREEN), ("↓ 29%", "Reduction in total\nfluid given", ACCENT), ("↓ 27%", "Reduction in\ncrystalloid volume", TEAL), ("p < 0.001", "Significance\n(fluid volume)", RED), ] for i, (val, lbl, col) in enumerate(stats): x = Inches(0.35) + i * Inches(2.6) stat_box(sl, x, Inches(1.35), Inches(2.45), Inches(1.75), val, lbl, col) # Comparison table hdrs3 = ["Fluid Parameter", "Control (n=50)", "GDFT (n=50)", "P value"] cw3 = [Inches(4.6), Inches(2.8), Inches(2.8), Inches(2.0)] data3 = [ ["Total fluid – median (IQR)", "2750 (2250–3300) mL", "1975 (1575–2600) mL", "< 0.001*"], ["Crystalloid – median (IQR)", "2200 (2025–2513) mL", "1600 (837–2100) mL", "< 0.001*"], ["Colloid – median (IQR)", "500 (0–1000) mL", "500 (500–1000) mL", "0.981"], ["Urine output – median (IQR)", "350 (200–800) mL", "600 (300–800) mL", "0.041*"], ["Blood loss – median (IQR)", "100 (0–350) mL", "100 (50–225) mL", "0.970"], ["Vasopressor / inotrope use", "18 (36%)", "27 (54%)", "0.072"], ["Net fluid balance", "2116 (1100–3100) mL", "1199 (800–2750) mL", "< 0.001*"], ] t_top3 = Inches(3.25) rect(sl, Inches(0.35), t_top3, sum(cw3), Inches(0.42), NAVY) for ci, (h, cw) in enumerate(zip(hdrs3, cw3)): x = Inches(0.35) + sum(cw3[:ci]) textbox(sl, x+Inches(0.05), t_top3+Inches(0.03), cw-Inches(0.1), Inches(0.36), h, size=Pt(12.5), bold=True, color=WHITE, align=PP_ALIGN.CENTER) for ri, row in enumerate(data3): y = t_top3 + Inches(0.42) + ri * Inches(0.48) bg_c = MINT if ri % 2 == 0 else WHITE for ci, (cell, cw) in enumerate(zip(row, cw3)): x = Inches(0.35) + sum(cw3[:ci]) star_col = RED if "*" in cell else DARK rect(sl, x, y, cw, Inches(0.48), bg_c, MID_GREY, Pt(0.4)) textbox(sl, x+Inches(0.07), y+Inches(0.04), cw-Inches(0.14), Inches(0.4), cell, size=Pt(12), bold=(ci==0 or "*" in cell), color=star_col, align=PP_ALIGN.CENTER if ci>0 else PP_ALIGN.LEFT, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 13 – PRIMARY OUTCOMES # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Results – Primary Outcomes (Table 4)") footer(sl) # Big stat cards big_stats = [ ("9.0 days", "Mean LOS\nGroup G (GDFT)", GREEN), ("12.0 days", "Mean LOS\nGroup C (Control)", RED), ("3 days LESS", "Reduction in\nhospital stay (p=0.001)", ACCENT), ("4%", "POGD rate\nGroup G", GREEN), ("32%", "POGD rate\nGroup C", RED), ] for i, (val, lbl, col) in enumerate(big_stats): x = Inches(0.35) + i * Inches(2.6) stat_box(sl, x, Inches(1.35), Inches(2.45), Inches(1.95), val, lbl, col) # GI recovery comparison rect(sl, Inches(0.35), Inches(3.5), Inches(12.6), Inches(0.42), TEAL) textbox(sl, Inches(0.4), Inches(3.53), Inches(12.3), Inches(0.36), "GI Function Recovery", size=Pt(14), bold=True, color=WHITE) gi_data = [ ("Time to first flatus", "39.4 h (IQR 24.9–67.5)", "28.2 h (IQR 9.2–48.0)", "11 h FASTER", "p = 0.009"), ("Time to tolerate oral diet", "6.0 days (IQR 5.0–9.3)", "4.0 days (IQR 2.7–6.0)", "2 days SOONER", "p < 0.001"), ("POGD incidence", "16/50 (32%)", "2/50 (4%)", "8× lower risk", "p < 0.001"), ("POGI incidence", "17/50 (34%)", "12/50 (24%)", "Lower", "p < 0.001"), ] gi_hdrs = ["Outcome", "Control", "GDFT", "Difference", "P value"] gi_cw = [Inches(3.5), Inches(2.5), Inches(2.5), Inches(2.4), Inches(1.55)] t_top_gi = Inches(4.0) rect(sl, Inches(0.35), t_top_gi, sum(gi_cw), Inches(0.42), NAVY) for ci, (h, cw) in enumerate(zip(gi_hdrs, gi_cw)): x = Inches(0.35) + sum(gi_cw[:ci]) textbox(sl, x+Inches(0.05), t_top_gi+Inches(0.03), cw-Inches(0.1), Inches(0.36), h, size=Pt(12.5), bold=True, color=WHITE, align=PP_ALIGN.CENTER) for ri, row in enumerate(gi_data): y = t_top_gi + Inches(0.42) + ri * Inches(0.56) bg_c = MINT if ri % 2 == 0 else WHITE for ci, (cell, cw) in enumerate(zip(row, gi_cw)): x = Inches(0.35) + sum(gi_cw[:ci]) rect(sl, x, y, cw, Inches(0.56), bg_c, MID_GREY, Pt(0.4)) is_diff = (ci == 3) textbox(sl, x+Inches(0.07), y+Inches(0.06), cw-Inches(0.14), Inches(0.44), cell, size=Pt(12), bold=is_diff, color=GREEN if is_diff else DARK, align=PP_ALIGN.CENTER if ci>0 else PP_ALIGN.LEFT, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 14 – SECONDARY OUTCOMES # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Results – Secondary Outcomes (Table 5)") footer(sl) # Left panel rect(sl, Inches(0.35), Inches(1.35), Inches(6.1), Inches(5.5), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(0.5), Inches(1.42), Inches(5.8), Inches(0.4), "Metabolic & Recovery Markers", size=Pt(15), bold=True, color=TEAL) sec_left = [ "Serum lactate at 2h post-induction:\n Control 1.4 mmol/L vs GDFT 1.0 mmol/L (p < 0.001)", "Blood glucose at 2h post-induction:\n Control 7.8 mmol/L vs GDFT 6.9 mmol/L (p = 0.031)", "QoR-40 Day 1:\n Control 95.0 vs GDFT 130.0 (p < 0.001)", "QoR-40 Day 3:\n Control 117.5 vs GDFT 139.5 (p < 0.001)", "QoR-40 Day 5:\n Control 129.5 vs GDFT 147.0 (p < 0.001)", "Time to first mobilisation:\n Control 2.5 days vs GDFT 2.0 days (p = 0.025)", ] bullet_tf(sl, Inches(0.45), Inches(1.9), Inches(5.9), Inches(4.8), sec_left, size=Pt(13.5), color=DARK) # Right panel rect(sl, Inches(6.8), Inches(1.35), Inches(6.1), Inches(5.5), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(6.95), Inches(1.42), Inches(5.8), Inches(0.4), "Postoperative Complications", size=Pt(15), bold=True, color=TEAL) sec_right = [ "Total complications: 26% Control vs 12% GDFT (p = 0.072 – trend)", "Postoperative PNEUMONIA: 6 (12%) Control vs 0 (0%) GDFT (p = 0.010) ✔ Significant", "Arrhythmia: 2% vs 2% (p = 1.000) – no difference", "Lower limb DVT: 12% vs 2% (p = 0.054) – trend favouring GDFT", "Wound infection: 10% vs 4% (p = 0.242) – ns", "30-day mortality: 0% Control vs 1 patient GDFT (anastomotic rupture/haemorrhage) – p = 1.000", ] bullet_tf(sl, Inches(6.9), Inches(1.9), Inches(5.9), Inches(4.8), sec_right, size=Pt(13.5), color=DARK) # ════════════════════════════════════════════════════════════════ # SLIDE 15 – CRITICAL APPRAISAL – STRENGTHS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Critical Appraisal – Strengths") footer(sl) strengths = [ ("Prospective RCT", "Highest level of primary evidence. Prospective design minimises bias from outcome definition."), ("Pre-registered", "Registered on ClinicalTrials.gov (NCT03940144) before enrolment – reduces outcome reporting bias."), ("Standardised ERAS protocol", "All patients received the same ERAS care, isolating the fluid strategy as the only variable."), ("Validated outcome measure", "I-FEED scoring system – endorsed by ERAS/POQI 2018 consensus – gives standardised, objective GI assessment."), ("Modified ITT analysis", "Pragmatic and accepted approach. 30-day follow-up with zero loss to follow-up is excellent."), ("Standardised discharge criteria", "Using validated discharge criteria means LOS reflects actual clinical readiness, not administrative delay."), ("Blinded post-op assessors", "Postoperative outcome assessors were blinded to group allocation, reducing assessment bias."), ("Well-powered", "Sample size calculated from previous meta-analysis and pilot data. 100/110 patients completed = 91% completion."), ] for i, (title, body) in enumerate(strengths): row = i // 2; col = i % 2 x = Inches(0.35) + col * Inches(6.5) y = Inches(1.35) + row * Inches(1.45) rect(sl, x, y, Inches(6.2), Inches(1.35), WHITE, MID_GREY, Pt(1)) rect(sl, x, y, Inches(0.22), Inches(1.35), GREEN) textbox(sl, x+Inches(0.3), y+Inches(0.07), Inches(5.8), Inches(0.38), title, size=Pt(14), bold=True, color=GREEN) textbox(sl, x+Inches(0.3), y+Inches(0.5), Inches(5.8), Inches(0.78), body, size=Pt(12.5), bold=False, color=DARK, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 16 – CRITICAL APPRAISAL – LIMITATIONS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Critical Appraisal – Limitations") footer(sl) limits = [ ("Mixed surgical procedures", "Included gastrectomy, Whipple, hemicolectomy, rectal resection, cystectomy etc. Different surgeries impose different mechanical forces on the gut – this heterogeneity may dilute or confound GI outcomes."), ("Partial blinding only", "Anaesthesiologists and intraoperative staff COULD NOT be blinded due to the Vigileo monitor. This is practically unavoidable but introduces potential performance/observer bias."), ("Intraoperative GDFT only", "GDFT was applied intraoperatively only. Post-op fluid management was not standardised. Suboptimal post-op fluids could have negated the intraoperative benefits."), ("Optimal SVV threshold uncertain", "The 12% SVV cut-off is not universally agreed upon. SVV also assumes constant tidal volume ≥ 8 mL/kg and sinus rhythm – both mandated in this study but limits generalisability."), ("Single-centre study", "Conducted at one tertiary hospital in China. Results may not generalise to other healthcare settings, surgical volumes, or patient populations."), ("LOS as a surrogate", "Length of hospital stay can be influenced by non-medical factors (system pressures, patient preferences). The study mitigated this with standardised discharge criteria, but some residual confounding possible."), ] for i, (title, body) in enumerate(limits): row = i // 2; col = i % 2 x = Inches(0.35) + col * Inches(6.5) y = Inches(1.35) + row * Inches(1.98) rect(sl, x, y, Inches(6.2), Inches(1.88), WHITE, MID_GREY, Pt(1)) rect(sl, x, y, Inches(0.22), Inches(1.88), RED) textbox(sl, x+Inches(0.3), y+Inches(0.07), Inches(5.8), Inches(0.38), title, size=Pt(14), bold=True, color=RED) textbox(sl, x+Inches(0.3), y+Inches(0.5), Inches(5.8), Inches(1.3), body, size=Pt(12.5), bold=False, color=DARK, word_wrap=True) # ════════════════════════════════════════════════════════════════ # SLIDE 17 – DISCUSSION & LITERATURE CONTEXT # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Discussion – How Does This Fit in the Literature?") footer(sl) rect(sl, Inches(0.35), Inches(1.35), Inches(12.6), Inches(5.55), WHITE, MID_GREY, Pt(1)) textbox(sl, Inches(0.5), Inches(1.42), Inches(12.3), Inches(0.38), "Prior Evidence", size=Pt(16), bold=True, color=TEAL) lit_items = [ "Gan et al. 2002 (Anesthesiology): Goal-directed fluid therapy reduced LOS after major surgery – aligns with this study.", "Benes et al. 2010 (Crit Care): SVV-guided GDFT in HIGH-RISK patients – shorter LOS, fewer complications. This study extends findings to LOW-TO-MODERATE risk.", "Mayer et al. 2010 (Crit Care): FloTrac/Vigileo GDFT in high-risk patients – reduced hospital stay. Same device used here.", "Sun et al. 2017 meta-analysis (Crit Care): Perioperative GDFT reduces LOS and GI complications – this RCT provides additional primary evidence.", "FEDORA trial 2018 (BJA – Calvo-Vecino): GDFT in low-moderate risk patients – showed benefit. Consistent with current findings.", "CONFLICTING EVIDENCE – Gomez-Izquierdo 2017; Arslan-Carlon 2020; RELIEF trial (NEJM 2018): Some trials found NO benefit of GDFT or restrictive therapy over liberal fluid management, highlighting ongoing debate.", "KEY DIFFERENCE OF THIS STUDY: Used I-FEED scoring (not the vague 'postoperative ileus' definition), making GI outcomes more precise and comparable. Also both SVV AND CI were used together.", "AUTHORS' MECHANISTIC EXPLANATION: GDFT reduces fluid overload → less gut oedema → faster GI recovery. Also reduces stress response and systemic inflammation → faster convalescence.", ] bullet_tf(sl, Inches(0.45), Inches(1.88), Inches(12.1), Inches(4.9), lit_items, size=Pt(13.5), color=DARK) # ════════════════════════════════════════════════════════════════ # SLIDE 18 – CLINICAL IMPLICATIONS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, LIGHT_GREY) header_bar(sl, "Clinical Implications for Anaesthetic Practice") footer(sl) impls = [ ("For the Anaesthetist", ["Consider SVV-guided GDFT for ALL patients undergoing major abdominal surgery, not just high-risk cases", "The FloTrac/Vigileo only requires an arterial line already routinely placed – minimal added cost or invasiveness", "Target SVV ≤ 12% + CI ≥ 2.5 as dual safety criteria", "Do not ignore SVV changes due to position, pneumoperitoneum, or vent changes – note them but don't treat unless sustained > 5 min"], TEAL), ("For the ERAS Team", ["GDFT aligns with ERAS principles – avoid fluid excess, early GI function, early oral intake, early mobilisation", "Post-operative fluid protocol should also be optimised – intraoperative GDFT alone may not be enough", "I-FEED scoring is now recommended – adopt it to standardise GI outcome reporting in your institution"], GREEN), ("For the Healthcare System", ["3-day reduction in LOS per patient = significant cost savings and bed availability", "8× reduction in POGD rate reduces complications, ICU admissions, and readmissions", "Investment in FloTrac/Vigileo monitors likely cost-effective at scale"], NAVY), ] for i, (title, pts, col) in enumerate(impls): y = Inches(1.35) + i * Inches(2.02) rect(sl, Inches(0.35), y, Inches(12.6), Inches(1.92), WHITE, MID_GREY, Pt(1)) rect(sl, Inches(0.35), y, Inches(0.22), Inches(1.92), col) textbox(sl, Inches(0.65), y+Inches(0.07), Inches(12.0), Inches(0.4), title, size=Pt(15), bold=True, color=col) tb = sl.shapes.add_textbox(Inches(0.65), y+Inches(0.52), Inches(12.0), Inches(1.3)) tf = tb.text_frame; tf.word_wrap = True first = True for pt in pts: if first: p = tf.paragraphs[0]; first = False else: p = tf.add_paragraph() p.space_before = Pt(3) run = p.add_run() run.text = "• " + pt run.font.size = Pt(13); run.font.color.rgb = DARK; run.font.name = "Calibri" # ════════════════════════════════════════════════════════════════ # SLIDE 19 – TAKE-HOME MESSAGES # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, NAVY) rect(sl, 0, 0, W, Inches(1.25), RGBColor(0x07, 0x27, 0x48)) textbox(sl, Inches(0.4), Inches(0.1), Inches(12.5), Inches(1.1), "Take-Home Messages", size=Pt(30), bold=True, color=WHITE, align=PP_ALIGN.LEFT, v_anchor=MSO_ANCHOR.MIDDLE) takes = [ ("1", "GDFT WORKS in low-to-moderate risk patients", "SVV + CI guided fluid therapy using FloTrac/Vigileo significantly reduced hospital stay by 3 days and POGD by 8-fold compared to conventional MAP/CVP-guided therapy."), ("2", "Less fluid is more", "GDFT group received 29% less total fluid intraoperatively. Avoiding fluid excess is as important as avoiding hypovolaemia."), ("3", "GI recovery is faster", "Time to first flatus was 11 hours shorter and time to oral intake was 2 days shorter with GDFT – both clinically meaningful for patient experience and ERAS pathways."), ("4", "Better metabolic profile", "Lower serum lactate and blood glucose with GDFT suggest improved tissue perfusion and reduced surgical stress response."), ("5", "Minimally invasive monitoring is sufficient", "The FloTrac/Vigileo provides continuous cardiac output data from an existing arterial line – feasible in routine anaesthetic practice."), ] for i, (num, title, body) in enumerate(takes): y = Inches(1.3) + i * Inches(1.2) rect(sl, Inches(0.35), y, Inches(0.7), Inches(1.05), ACCENT) textbox(sl, Inches(0.35), y, Inches(0.7), Inches(1.05), num, size=Pt(26), bold=True, color=WHITE, align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE) rect(sl, Inches(1.15), y, Inches(11.8), Inches(1.05), RGBColor(0x11, 0x2D, 0x4D)) textbox(sl, Inches(1.3), y+Inches(0.04), Inches(11.5), Inches(0.42), title, size=Pt(15), bold=True, color=ACCENT) textbox(sl, Inches(1.3), y+Inches(0.48), Inches(11.5), Inches(0.5), body, size=Pt(12.5), bold=False, color=MID_GREY, word_wrap=True) rect(sl, 0, Inches(7.1), W, Inches(0.4), RGBColor(0x07, 0x27, 0x48)) textbox(sl, Inches(0.3), Inches(7.12), Inches(12.7), Inches(0.32), "Sun et al. BMC Anesthesiology 2023;23:397 · DOI: 10.1186/s12871-023-02360-1", size=Pt(9), bold=False, color=MID_GREY, align=PP_ALIGN.CENTER) # ════════════════════════════════════════════════════════════════ # SLIDE 20 – QUESTIONS # ════════════════════════════════════════════════════════════════ sl = prs.slides.add_slide(blank) bg(sl, NAVY) rect(sl, 0, 0, W, Inches(0.12), ACCENT) rect(sl, 0, Inches(7.38), W, Inches(0.12), ACCENT) textbox(sl, Inches(0.5), Inches(1.5), Inches(12.3), Inches(1.2), "Thank You", size=Pt(48), bold=True, color=ACCENT, align=PP_ALIGN.CENTER) textbox(sl, Inches(0.5), Inches(2.8), Inches(12.3), Inches(0.6), "Questions & Discussion", size=Pt(28), bold=False, color=WHITE, align=PP_ALIGN.CENTER) rect(sl, Inches(3.5), Inches(3.55), Inches(6.3), Inches(0.04), ACCENT) qs = [ "Q1: Why is SVV superior to CVP in predicting fluid responsiveness?", "Q2: What are the main conditions that make SVV unreliable?", "Q3: How could you further improve this study design?", "Q4: Would you change your own fluid practice based on this trial?", "Q5: How does this study compare to the RELIEF trial (NEJM 2018)?", ] bullet_tf(sl, Inches(1.5), Inches(3.75), Inches(10.3), Inches(3.2), qs, size=Pt(15), color=MINT, bullet="❓ ") textbox(sl, Inches(0.5), Inches(6.9), Inches(12.3), Inches(0.3), "Sun Y et al. BMC Anesthesiology 2023;23:397 · NCT03940144", size=Pt(10), bold=False, color=MID_GREY, align=PP_ALIGN.CENTER) # ════════════════════════════════════════════════════════════════ # SAVE # ════════════════════════════════════════════════════════════════ out_path = "/tmp/workspace/gdft-journal-club/GDFT_SVV_JournalClub.pptx" prs.save(out_path) print(f"Saved: {out_path}") print(f"Slides: {len(prs.slides)}") PYEOF python3 /tmp/workspace/gdft-journal-club/build_pptx.py