six-minute walk test postoperative complications abdominal surgery

cd /tmp/workspace && python3 -c " import pdfplumber pdf_path = '/tmp/workspace/attachments/e9c26152-246e-4e04-b624-3855bc26ee9d/ISRC Annex A Form 1A Clinical Research Proposal_Ong (April 2026 Final) with stamps.pdf' with pdfplumber.open(pdf_path) as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): text = page.extract_text() if text: print(f'\\n=== PAGE {i+1} ===') print(text[:4000]) "

six-minute walk test preoperative functional capacity prediction surgery outcomes

six-minute walk test postoperative pulmonary complications prediction

preoperative functional capacity major abdominal surgery morbidity mortality

PMID: 31111872

PMID: 31402737

PMID: 35253333

PMID: 38526466

PMID: 34629224

PMID: 29049742

PMID: 35579479

PMID: 28738386

mkdir -p /tmp/workspace/6mwt-proposal && ls /tmp/workspace/

cat << 'PYEOF' > /tmp/workspace/6mwt-proposal/build_proposal.py from docx import Document from docx.shared import Pt, Inches, RGBColor from docx.enum.text import WD_ALIGN_PARAGRAPH from docx.oxml.ns import qn from docx.oxml import OxmlElement import copy doc = Document() # ─── Page margins (match reference paper: normal margins) ─────────────────── for section in doc.sections: section.top_margin = Inches(1.0) section.bottom_margin = Inches(1.0) section.left_margin = Inches(1.25) section.right_margin = Inches(1.0) # ─── Default style ────────────────────────────────────────────────────────── style = doc.styles['Normal'] style.font.name = 'Times New Roman' style.font.size = Pt(12) style.paragraph_format.space_after = Pt(0) style.paragraph_format.space_before = Pt(0) def set_font(run, bold=False, italic=False, size=12, name='Times New Roman'): run.font.name = name run.font.size = Pt(size) run.bold = bold run.italic = italic def add_para(text='', bold=False, italic=False, size=12, align=WD_ALIGN_PARAGRAPH.JUSTIFY, space_before=0, space_after=6, indent_left=0, first_line=0): p = doc.add_paragraph() p.alignment = align p.paragraph_format.space_before = Pt(space_before) p.paragraph_format.space_after = Pt(space_after) p.paragraph_format.left_indent = Inches(indent_left) p.paragraph_format.first_line_indent = Inches(first_line) if text: run = p.add_run(text) set_font(run, bold=bold, italic=italic, size=size) return p def add_section_heading(number, title): """Bold numbered section heading like '2. Brief Description / Summary'""" p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(12) p.paragraph_format.space_after = Pt(6) run = p.add_run(f"{number}. {title}") run.font.name = 'Times New Roman' run.font.size = Pt(12) run.bold = True return p def add_subsection_heading(number, title): """Bold subsection like '3.1. Significance of the Project'""" p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(8) p.paragraph_format.space_after = Pt(4) run = p.add_run(f"{number} {title}") run.font.name = 'Times New Roman' run.font.size = Pt(12) run.bold = True return p # ════════════════════════════════════════════════════════════════════════════ # HEADER / TITLE BLOCK # ════════════════════════════════════════════════════════════════════════════ add_para('DATABANK INFO NEEDED:', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=2) add_para('No Yes', size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=2) add_para('1. R&B Form No. 1A', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=2) add_para('', space_after=4) # Institution header inst_p = doc.add_paragraph() inst_p.alignment = WD_ALIGN_PARAGRAPH.CENTER inst_p.paragraph_format.space_after = Pt(2) r = inst_p.add_run('St. Luke\'s Medical Center') r.font.name = 'Times New Roman'; r.font.size = Pt(12); r.bold = True add_para('RESEARCH AND BIOTECHNOLOGY', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.CENTER, space_after=6) add_para('1.1. CLINICAL RESEARCH PROPOSAL', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.CENTER, space_after=12) # Research Title p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_after = Pt(4) r = p.add_run('Research Title:') r.font.name = 'Times New Roman'; r.font.size = Pt(12); r.bold = True title_p = doc.add_paragraph() title_p.alignment = WD_ALIGN_PARAGRAPH.LEFT title_p.paragraph_format.space_after = Pt(10) r = title_p.add_run( 'Prognostic Value of the Six-Minute Walk Test in Predicting Postoperative Pulmonary ' 'and Major Complications Among Adults Undergoing Major Abdominal Surgery: ' 'A Prospective Cohort Study' ) r.font.name = 'Times New Roman'; r.font.size = Pt(12); r.bold = False # Investigators table add_para('Investigators:', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=2) table = doc.add_table(rows=4, cols=2) table.style = 'Table Grid' table.columns[0].width = Inches(3.5) table.columns[1].width = Inches(2.5) headers = ['Name and Signature', 'Unit/Position'] for i, h in enumerate(headers): cell = table.cell(0, i) cell.text = h for run in cell.paragraphs[0].runs: run.bold = True run.font.size = Pt(11) rows_data = [ ('Project Leader/s:\n\n_______________________________', 'Consultant\n(Consultant/Manager/Faculty)'), ('Co-Project Leader/s:\n\n_______________________________', 'Pulmonary/Surgery Fellow\n(Resident/Fellow/Student)'), ('Research Fellow:\n\n_______________________________', ''), ] for i, (name_col, unit_col) in enumerate(rows_data): table.cell(i+1, 0).text = name_col table.cell(i+1, 1).text = unit_col for col in [0, 1]: for run in table.cell(i+1, col).paragraphs[0].runs: run.font.size = Pt(11) doc.add_paragraph() # spacing add_para('Inst./Dept./Center/Group: Department of Surgery / Anesthesiology', size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=12) # ════════════════════════════════════════════════════════════════════════════ # SECTION 2 – BRIEF DESCRIPTION / SUMMARY # ════════════════════════════════════════════════════════════════════════════ add_section_heading('2', 'Brief Description / Summary') brief_desc = ( 'Major abdominal surgery carries a significant risk of postoperative pulmonary ' 'complications (PPCs) and other major adverse outcomes, which contribute substantially ' 'to perioperative morbidity and mortality. Identifying patients at high risk before surgery ' 'enables targeted preventive strategies, yet current preoperative risk tools are either ' 'resource-intensive or rely on subjective estimates of functional capacity.' ) add_para(brief_desc, size=12, space_after=6) brief_desc2 = ( 'This study investigates the prognostic value of the Six-Minute Walk Test (6MWT), ' 'a simple, low-cost, and widely available field exercise test that objectively quantifies ' 'functional exercise capacity through the distance walked in six minutes (6MWD). The 6MWT ' 'is hypothesized to serve as a composite marker reflecting cardiorespiratory reserve, ' 'physical conditioning, and overall physiologic resilience — factors directly relevant to ' 'the ability to withstand surgical stress.' ) add_para(brief_desc2, size=12, space_after=6) brief_desc3 = ( 'This will be a prospective cohort study at a tertiary hospital involving adult patients ' 'scheduled for elective or semi-elective major abdominal surgery. The 6MWT will be ' 'performed preoperatively, and participants will be followed through the postoperative ' 'period to ascertain the occurrence of PPCs and other major complications. The 6MWT could ' 'offer clinicians a practical, accessible, and inexpensive preoperative risk stratification ' 'tool, enabling timely optimization and potentially improving patient outcomes in both ' 'resource-rich and resource-limited settings.' ) add_para(brief_desc3, size=12, space_after=12) # ════════════════════════════════════════════════════════════════════════════ # SECTION 3 – INTRODUCTION # ════════════════════════════════════════════════════════════════════════════ add_section_heading('3', 'Introduction') # ── 3.1 Significance ──────────────────────────────────────────────────────── add_subsection_heading('3.1.', 'Significance of the Project') sig1 = ( 'Major abdominal surgery encompasses a broad range of high-risk procedures including ' 'colorectal resection, hepatobiliary surgery, gastrectomy, and pancreaticoduodenectomy. ' 'These procedures are associated with postoperative pulmonary complication rates ranging ' 'from 9% to 40%, depending on patient demographics, comorbidities, and surgical complexity ' '[1]. PPCs — encompassing pneumonia, respiratory failure, atelectasis requiring intervention, ' 'pleural effusion, bronchospasm, and aspiration — are among the most common causes of ' 'perioperative morbidity, prolonged hospital stay, and mortality following abdominal surgery [2].' ) add_para(sig1, size=12, space_after=6) sig2 = ( 'Despite their clinical importance, a reliable and practical bedside tool for preoperative ' 'risk prediction of PPCs remains elusive. Current tools such as the ARISCAT (Assess Respiratory ' 'Risk in Surgical Patients in Catalonia) score and ASA Physical Status classification provide ' 'general risk estimates but do not directly capture an individual\'s functional reserve. ' 'Cardiopulmonary exercise testing (CPET) is widely regarded as the gold standard for ' 'objective preoperative functional assessment, but it requires specialized equipment, ' 'trained personnel, and considerable time and cost, limiting its routine use especially ' 'in resource-limited settings [3].' ) add_para(sig2, size=12, space_after=6) sig3 = ( 'The Six-Minute Walk Test (6MWT) offers a compelling alternative: it requires no specialized ' 'equipment beyond a measured corridor, takes less than ten minutes to administer, and yields ' 'an objective, reproducible measure of submaximal exercise tolerance — the six-minute walk ' 'distance (6MWD). The 6MWT is already validated and widely used in cardiopulmonary ' 'rehabilitation and chronic disease management. Its perioperative application, particularly ' 'in abdominal surgery, is an emerging area of study with important clinical and public health ' 'implications.' ) add_para(sig3, size=12, space_after=6) sig4 = ( 'The study aims to:' ) add_para(sig4, size=12, space_after=4) aims = [ ('1. ', 'Determine the prognostic value of preoperative 6MWD in predicting PPCs and major ' 'postoperative complications in adults undergoing major abdominal surgery at a tertiary hospital.'), ('2. ', 'Identify an optimal 6MWD cut-off value that discriminates patients at high versus low ' 'risk for PPCs, enabling bedside clinical risk stratification.'), ('3. ', 'Contribute locally relevant evidence on preoperative functional capacity assessment in ' 'a setting where CPET is not routinely available, supporting cost-effective perioperative ' 'care pathways.'), ] for num, text in aims: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.3) r1 = p.add_run(num) r1.font.name = 'Times New Roman'; r1.font.size = Pt(12); r1.bold = True r2 = p.add_run(text) r2.font.name = 'Times New Roman'; r2.font.size = Pt(12) doc.add_paragraph() # ── 3.2 Rationale ─────────────────────────────────────────────────────────── add_subsection_heading('3.2.', 'Rationale for Doing the Study') rat1 = ( 'Timely and accurate preoperative risk stratification remains a persistent challenge in the ' 'perioperative management of patients undergoing major abdominal surgery. Existing severity ' 'scoring systems and risk indices are often underutilized due to complexity, limited ' 'applicability across different populations, or the absence of objective measures of a ' 'patient\'s functional reserve.' ) add_para(rat1, size=12, space_after=6) rat2 = ( 'Functional capacity — defined as the ability of an individual to perform physical activities ' 'that require aerobic metabolism — is a well-established, independent determinant of ' 'perioperative risk. Rose et al. (2022) reviewed the physiological basis linking ' 'cardiorespiratory fitness (CRF) to postoperative outcomes, demonstrating that impaired CRF ' 'is an independent risk factor for mortality and morbidity. Surgery triggers a period of ' 'substantially increased oxygen demand; patients unable to meet this demand face greater risk ' 'of organ failure and death. The authors emphasized that CRF is the greatest modifiable ' 'perioperative risk factor, and its accurate preoperative detection is essential for risk ' 'classification and patient management [3].' ) add_para(rat2, size=12, space_after=6) rat3 = ( 'The 6MWT provides an objective, standardized measure of submaximal exercise capacity that ' 'is closely correlated with peak oxygen consumption (VO2 peak) and reflects the integrated ' 'response of the cardiorespiratory, neuromuscular, and metabolic systems. Unlike CPET, the ' '6MWT is simple, inexpensive, and reproducible, making it practical for routine preoperative ' 'assessment even in settings with limited resources. Crucially, the 6MWT captures not only ' 'cardiorespiratory fitness but also the patient\'s nutritional status, muscle strength, and ' 'motivational state — all factors that independently influence surgical outcomes.' ) add_para(rat3, size=12, space_after=6) rat4 = ( 'Several studies have examined the relationship between preoperative 6MWD and postoperative ' 'outcomes. Soares and Nucci (2021) conducted a prospective cohort study of 50 patients ' 'undergoing elective abdominal surgery, finding that 25 (50%) developed postoperative ' 'pulmonary complications within the first seven postoperative days. The mean preoperative ' '6MWD was significantly shorter among those who developed PPCs (444.8 m vs. 498.3 m; ' 'p = 0.013). Multivariable logistic regression confirmed that a lower preoperative 6MWD was ' 'significantly and independently associated with PPCs (OR = 0.978; p = 0.010) in patients ' 'undergoing intestinal, gastric, or biliary tract resection [4].' ) add_para(rat4, size=12, space_after=6) rat5 = ( 'Extending this evidence to other abdominal organ surgeries, Magalhaes et al. (2017) ' 'prospectively studied 100 patients undergoing liver transplantation, finding that 44 ' 'developed at least one postoperative respiratory complication. In logistic regression ' 'analysis, each additional 50 meters walked during the preoperative 6MWT was associated ' 'with a 41% reduction in the odds of developing PPCs (OR = 0.589; 95% CI: 0.357–0.971; ' 'p = 0.03), establishing the 6MWT as an independent predictor of postoperative pulmonary ' 'complications in this population [5].' ) add_para(rat5, size=12, space_after=6) rat6 = ( 'In the oncologic setting, Inoue et al. (2020) retrospectively reviewed 111 patients ' 'undergoing thoracic surgery for esophageal cancer and found that a preoperative 6MWD ' 'of ≤454 m was a significant threshold for predicting grade II or higher Clavien-Dindo ' 'complications, with 71.0% sensitivity and 54.8% specificity. In multiple regression ' 'analysis, lower 6MWD was an independent preoperative risk factor for major complications [6]. ' 'Similarly, Hattori et al. (2018) demonstrated in a retrospective analysis of 321 patients ' 'undergoing lung resection for malignancy that a preoperative 6MWD ≤450 m predicted ' 'postoperative pneumonia with 69.2% sensitivity and 71.1% specificity (p = 0.002) [7].' ) add_para(rat6, size=12, space_after=6) rat7 = ( 'At the level of systematic evidence, Makker et al. (2022) performed a systematic review ' 'and meta-analysis of five studies (379 patients) evaluating preoperative 6MWT or five-times ' 'sit-to-stand performance and postoperative outcomes in gastrointestinal and abdominal ' 'cancer surgery. Higher preoperative 6MWT performance (≥400 m) was significantly associated ' 'with lower-grade postoperative complications (OR = 0.38; 95% CI: 0.15–0.95), though the ' 'association with length of stay was not significant. The authors noted the need for ' 'high-quality prospective studies with standardized definitions and broader patient ' 'populations [8].' ) add_para(rat7, size=12, space_after=6) rat8 = ( 'Argillander et al. (2022) conducted a systematic review of preoperative physical ' 'performance tests and their predictive value for postoperative outcomes specifically in ' 'patients aged ≥65 years undergoing major abdominal cancer surgery. Among non-CPET field ' 'tests, the 6MWT and the Incremental Shuttle Walk Test (ISWT) predicted adverse outcomes ' 'in two studies each. The authors concluded that the 6MWT is a feasible alternative to CPET ' 'for estimating aerobic capacity in older surgical patients, but emphasized the need for ' 'prospective studies comparing different physical tests in a standardized manner [9].' ) add_para(rat8, size=12, space_after=6) rat9 = ( 'In a recent study by Garg et al. (2025) evaluating predictive models for PPCs in upper ' 'abdominal surgery, 20.3% of 133 patients developed PPCs. While the study\'s multivariable ' 'analysis highlighted abnormal chest radiograph, blood urea nitrogen, and duration of surgery ' 'as independent predictors, the investigators specifically tested the 6MWT against established ' 'risk scores. Although 6MWD lacked independent predictive power in that particular cohort, ' 'the authors acknowledged that the study was limited by its single-centre retrospective ' 'design and variable timing of 6MWT administration, and called for prospective designs with ' 'standardized protocols to better characterize the 6MWT\'s predictive role [2].' ) add_para(rat9, size=12, space_after=6) rat10 = ( 'The 6MWT uniquely serves as a composite indicator: reduced 6MWD reflects not only limited ' 'cardiorespiratory reserve but also deconditioning, sarcopenia, and poor nutritional ' 'status — all factors shown to independently worsen surgical outcomes. Since the 6MWT ' 'is inexpensive, non-invasive, and requires minimal equipment or personnel training, it is ' 'ideally suited for routine preoperative application in most hospital settings, including ' 'those with limited access to CPET or advanced physiologic testing.' ) add_para(rat10, size=12, space_after=6) rat11 = ( 'Locally, there is a significant evidence gap regarding the use of objective functional ' 'capacity measures in preoperative risk assessment for abdominal surgery. Existing ' 'perioperative practice largely relies on subjective estimates of metabolic equivalents ' '(METs) via patient history rather than objective testing. Given the high burden of ' 'abdominal surgical disease in the Philippines and the challenges of access to advanced ' 'perioperative testing, there is a compelling rationale to evaluate whether the 6MWT — a ' 'simple, low-cost tool — can reliably predict PPCs and major complications in a local ' 'surgical population. Demonstrating its predictive value could establish the 6MWT as a ' 'practical and immediately implementable preoperative risk stratification tool for Filipino ' 'surgical patients and similar resource-constrained settings.' ) add_para(rat11, size=12, space_after=12) # ════════════════════════════════════════════════════════════════════════════ # SECTION 7 – REFERENCES (Vancouver, continuous numbering) # ════════════════════════════════════════════════════════════════════════════ add_section_heading('7', 'References') references = [ ('[1]', 'Smetana GW, Lawrence VA, Cornell JE; American College of Physicians. ' 'Preoperative pulmonary risk stratification for noncardiothoracic surgery: ' 'systematic review for the American College of Physicians. ' 'Ann Intern Med. 2006 Apr 18;144(8):581–95. doi: 10.7326/0003-4819-144-8-200604180-00009.'), ('[2]', 'Garg S, Govindaraj V, Dwivedi DP, Raja K, Theerthar EP. ' 'Postoperative pulmonary complications in patients undergoing upper abdominal surgery: ' 'risk factors and predictive models. ' 'Monaldi Arch Chest Dis. 2025 Mar 31. doi: 10.4081/monaldi.2024.2915. PMID: 38526466.'), ('[3]', 'Rose GA, Davies RG, Appadurai IR, Williams IM, Bashir M, Berg RMG. ' '\'Fit for surgery\': the relationship between cardiorespiratory fitness and postoperative outcomes. ' 'Exp Physiol. 2022 Aug;107(8):780–95. doi: 10.1113/EP090156. PMID: 35579479.'), ('[4]', 'Soares SMTP, Nucci LB. ' 'Association between early pulmonary complications after abdominal surgery and preoperative physical capacity. ' 'Physiother Theory Pract. 2021 Jul;37(7):852–9. doi: 10.1080/09593985.2019.1650404. PMID: 31402737.'), ('[5]', 'Magalhaes CBA, Nogueira IC, Marinho LS, Daher EF, Garcia JHP, Viana CFG. ' 'Exercise capacity impairment can predict postoperative pulmonary complications after liver transplantation. ' 'Respiration. 2017;94(6):538–44. doi: 10.1159/000479008. PMID: 28738386.'), ('[6]', 'Inoue T, Ito S, Kanda M, Niwa Y, Nagaya M, Nishida Y. ' 'Preoperative six-minute walk distance as a predictor of postoperative complication in patients with esophageal cancer. ' 'Dis Esophagus. 2020 Mar 5;33(3):doz050. doi: 10.1093/dote/doz050. PMID: 31111872.'), ('[7]', 'Hattori K, Matsuda T, Takagi Y, Nagaya M, Inoue T, Nishida Y. ' 'Preoperative six-minute walk distance is associated with pneumonia after lung resection. ' 'Interact Cardiovasc Thorac Surg. 2018 Feb 1;26(2):208–13. doi: 10.1093/icvts/ivx310. PMID: 29049742.'), ('[8]', 'Makker PGS, Koh CE, Solomon MJ, Steffens D. ' 'Preoperative functional capacity and postoperative outcomes following abdominal and pelvic cancer surgery: ' 'a systematic review and meta-analysis. ' 'ANZ J Surg. 2022 Jul;92(7-8):1732–40. doi: 10.1111/ans.17577. PMID: 35253333.'), ('[9]', 'Argillander TE, Heil TC, Melis RJF, van Duijvendijk P, Klaase JM, van Munster BC. ' 'Preoperative physical performance as predictor of postoperative outcomes in patients aged 65 and older ' 'scheduled for major abdominal cancer surgery: a systematic review. ' 'Eur J Surg Oncol. 2022 Mar;48(3):575–84. doi: 10.1016/j.ejso.2021.09.019. PMID: 34629224.'), ] for num, text in references: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.4) p.paragraph_format.first_line_indent = Inches(-0.4) r1 = p.add_run(num + ' ') r1.font.name = 'Times New Roman'; r1.font.size = Pt(12); r1.bold = False r2 = p.add_run(text) r2.font.name = 'Times New Roman'; r2.font.size = Pt(12) # ─── Footer note ──────────────────────────────────────────────────────────── doc.add_paragraph() footer_p = doc.add_paragraph() footer_p.alignment = WD_ALIGN_PARAGRAPH.RIGHT footer_p.paragraph_format.space_before = Pt(24) r = footer_p.add_run('Protocol Version 01 dated ________________') r.font.name = 'Times New Roman'; r.font.size = Pt(10) # ─── Save ──────────────────────────────────────────────────────────────────── out_path = '/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Sections.docx' doc.save(out_path) print(f'Saved: {out_path}') PYEOF python3 /tmp/workspace/6mwt-proposal/build_proposal.py

python3 -c " from docx import Document doc = Document('/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Sections.docx') for p in doc.paragraphs: if p.text.strip(): print(f'[{p.style.name}] {p.text[:120]}') "

python3 -c " from docx import Document doc = Document('/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Sections.docx') for i, p in enumerate(doc.paragraphs): if p.text.strip(): print(f'{i}: [{p.style.name}] {p.text[:150]}') "

six-minute walk test perioperative risk assessment abdominal surgery prospective

postoperative pulmonary complications definition incidence abdominal surgery

PMID: 35750401

PMID: 38472053

six-minute walk test standardization ATS guidelines reliability validity

six-minute walk distance reference values adults normative exercise capacity

Clavien-Dindo classification postoperative complications grading surgery outcomes

PMID: 41027267

PMID: 37560171

PMID: 34939921

cat << 'PYEOF' > /tmp/workspace/6mwt-proposal/append_sections.py from docx import Document from docx.shared import Pt, Inches from docx.enum.text import WD_ALIGN_PARAGRAPH # ── Load existing document ──────────────────────────────────────────────────── doc = Document('/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Sections.docx') # ── Remove the old "7. References" section and footer from existing doc ────── # We will re-add References at the very end with updated numbering paragraphs_to_keep = [] removing = False for p in doc.paragraphs: if p.text.strip().startswith('7. References'): removing = True if not removing: paragraphs_to_keep.append(p) # Delete all paragraphs after (and including) "7. References" # python-docx: remove from the XML body body = doc.element.body all_paras = body.findall('.//{http://schemas.openxmlformats.org/wordprocessingml/2006/main}p') found_refs = False for elem in list(body): tag = elem.tag.split('}')[-1] if '}' in elem.tag else elem.tag if tag == 'p': txt = ''.join( n.text or '' for n in elem.iter('{http://schemas.openxmlformats.org/wordprocessingml/2006/main}t') ) if txt.strip().startswith('7. References'): found_refs = True if found_refs: body.remove(elem) # ── Helper functions ────────────────────────────────────────────────────────── def set_font(run, bold=False, italic=False, size=12, name='Times New Roman'): run.font.name = name run.font.size = Pt(size) run.bold = bold run.italic = italic def add_para(text='', bold=False, italic=False, size=12, align=WD_ALIGN_PARAGRAPH.JUSTIFY, space_before=0, space_after=6, indent_left=0, first_line=0): p = doc.add_paragraph() p.alignment = align p.paragraph_format.space_before = Pt(space_before) p.paragraph_format.space_after = Pt(space_after) p.paragraph_format.left_indent = Inches(indent_left) p.paragraph_format.first_line_indent = Inches(first_line) if text: run = p.add_run(text) set_font(run, bold=bold, italic=italic, size=size) return p def add_section_heading(number, title): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(12) p.paragraph_format.space_after = Pt(6) run = p.add_run(f"{number}. {title}") run.font.name = 'Times New Roman'; run.font.size = Pt(12); run.bold = True return p def add_subsection_heading(number, title): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(8) p.paragraph_format.space_after = Pt(4) run = p.add_run(f"{number} {title}") run.font.name = 'Times New Roman'; run.font.size = Pt(12); run.bold = True return p def add_bullet(label, text, indent=0.3): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(indent) r1 = p.add_run(label) r1.font.name = 'Times New Roman'; r1.font.size = Pt(12); r1.bold = True r2 = p.add_run(text) r2.font.name = 'Times New Roman'; r2.font.size = Pt(12) return p def add_sub_bullet(text, indent=0.55): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(3) p.paragraph_format.left_indent = Inches(indent) run = p.add_run(u'\u2022 ' + text) run.font.name = 'Times New Roman'; run.font.size = Pt(12) return p # ════════════════════════════════════════════════════════════════════════════ # 3.3 BACKGROUND INFORMATION AND BRIEF LITERATURE REVIEW # ════════════════════════════════════════════════════════════════════════════ add_subsection_heading('3.3.', 'Background Information and Brief Literature Review') # --- Global & local burden of major abdominal surgery ---------------------- bg1 = ( 'Major abdominal surgery — defined as intraperitoneal procedures lasting more than one ' 'hour under general or regional anesthesia — represents one of the highest-risk categories ' 'of elective surgical care worldwide. Procedures in this group include open and laparoscopic ' 'colorectal resection, gastrectomy, hepatectomy, pancreatectomy, esophagectomy, and ' 'small-bowel resection. Globally, more than 300 million major surgical operations are ' 'performed annually, and the complication burden after abdominal surgery remains a major ' 'driver of perioperative mortality, intensive care utilization, and healthcare costs [1].' ) add_para(bg1, size=12, space_after=6) # --- Postoperative pulmonary complications ---------------------------------- bg2 = ( 'Postoperative pulmonary complications (PPCs) are among the most frequent and clinically ' 'consequential complications following major abdominal surgery. Based on the consensus ' 'Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative ' 'and Anaesthetic Care (StEP-COMPAC) definition, PPCs encompass a spectrum of disorders ' 'including pneumonia, respiratory failure requiring ventilatory support, pleural effusion ' 'requiring drainage, bronchospasm, and atelectasis requiring intervention. In a large ' 'international cohort study of 11,591 patients undergoing major abdominal surgery, the ' 'overall PPC rate was 7.8% using the StEP-COMPAC definition; however, rates vary widely ' '(9%–40%) depending on the operative site, patient population, and PPC definition used [10]. ' 'Among patients undergoing upper abdominal surgery specifically, Garg et al. (2025) reported ' 'a PPC incidence of 20.3%, with pleural effusion (11.3%), respiratory failure (7.5%), and ' 'pneumonia (4.5%) as the most common events [2].' ) add_para(bg2, size=12, space_after=6) bg3 = ( 'PPCs carry substantial prognostic weight. They are independently associated with prolonged ' 'hospital stay, escalation of care to the intensive care unit, increased 30-day and 90-day ' 'mortality, and significantly higher resource utilization. Boden et al. (2024) demonstrated ' 'in an individual patient-level meta-analysis of 800 patients across two randomized controlled ' 'trials that a single preoperative physiotherapy session reduced the odds of PPCs by 47% ' '(adjusted OR 0.53; 95% CI: 0.34–0.85), underscoring both the preventability of PPCs and ' 'the importance of identifying at-risk patients preoperatively [11].' ) add_para(bg3, size=12, space_after=6) # --- Current preoperative risk stratification tools ------------------------ bg4 = ( 'Current tools for preoperative PPC risk stratification are either complex, resource-intensive, ' 'or insufficiently validated. Existing risk prediction models — including the ARISCAT score, ' 'ASA Physical Status classification, Gupta Respiratory Failure Index, and spirometry-based ' 'risk estimates — show only moderate discriminative ability. In the STARSurg/TASMAN ' 'international validation study, none of the six externally validated prognostic models ' 'showed good discrimination (defined as AUROC ≥0.70) for PPCs; the ARISCAT score performed ' 'best with an AUROC of 0.700 (95% CI: 0.683–0.717) [10]. Similarly, a systematic review by ' 'Dankert et al. (2022) found that pulmonary function tests including spirometry provided ' 'inconclusive evidence for PPC prediction in non-thoracic surgery, with only a possible benefit ' 'identified in upper abdominal surgery subgroup analyses [12]. These findings highlight a ' 'critical gap: an objective, broadly applicable, and bedside-feasible tool for preoperative ' 'PPC risk stratification is currently lacking.' ) add_para(bg4, size=12, space_after=6) # --- Functional capacity and the physiologic basis for periop risk --------- bg5 = ( 'A patient\'s functional capacity — their ability to sustain aerobic metabolism during ' 'physical activity — is a fundamental determinant of perioperative risk. The physiologic ' 'basis is straightforward: surgery imposes an acute increase in whole-body oxygen demand ' 'through the stress response, inflammatory cascade, and the metabolic demands of tissue ' 'repair. Patients with limited preoperative cardiorespiratory reserve are unable to meet ' 'this demand, resulting in relative oxygen debt, organ dysfunction, and adverse outcomes. ' 'Rose et al. (2022) characterized this relationship in detail, demonstrating that impaired ' 'cardiorespiratory fitness (CRF) is an independent predictor of postoperative morbidity ' 'and mortality, and that CRF is the single greatest modifiable perioperative risk factor [3]. ' 'While cardiopulmonary exercise testing (CPET) provides the most objective metric of CRF ' 'via peak oxygen uptake (VO2 peak) and ventilatory anaerobic threshold, CPET requires ' 'specialized equipment, trained physiologists, and approximately 30–45 minutes per patient, ' 'limiting its routine perioperative use to well-resourced centers [9].' ) add_para(bg5, size=12, space_after=6) # --- The 6MWT: description, standardization, normative data ---------------- bg6 = ( 'The Six-Minute Walk Test (6MWT) is a standardized, submaximal exercise test in which the ' 'patient walks as far as possible along a flat, 30-meter corridor for six minutes, with ' 'the primary outcome being the six-minute walk distance (6MWD) in meters. The test was ' 'formally standardized by the American Thoracic Society (ATS) in 2002 and has been widely ' 'adopted across cardiopulmonary, oncology, musculoskeletal, and rehabilitation medicine. ' 'The 6MWT reflects the integrated performance of the pulmonary, cardiovascular, ' 'neuromuscular, and metabolic systems, and is strongly correlated with VO2 peak on formal ' 'CPET. Normative reference values for the 6MWT in adults have been well characterized: ' 'a systematic review and meta-analysis by Otadi and Malmir (2026) pooled data from 28 ' 'studies and reported mean 6MWDs of 473 m in older men and 428 m in older women, with ' 'distance declining by approximately 10.25 m per year of age [13]. For the Asian adult ' 'population — most relevant to a Filipino cohort — Yeung et al. (2022) reported an overall ' 'mean 6MWD of 578 m (±75 m), with age-stratified values ranging from 601 m in adults ' 'aged 21–39 to 519 m in those aged 60–80 [14]. These normative data provide a framework ' 'for identifying clinically relevant thresholds in the preoperative setting.' ) add_para(bg6, size=12, space_after=6) # --- 6MWT evidence in surgical populations --------------------------------- bg7 = ( 'Several prospective and retrospective studies have evaluated the 6MWT as a preoperative ' 'risk tool in surgical populations, with a growing body of evidence specifically addressing ' 'abdominal surgery. Soares and Nucci (2021) conducted a cross-sectional cohort study of ' '50 patients undergoing elective abdominal surgery and found that half developed early PPCs ' 'within the first seven postoperative days. The preoperative 6MWD was significantly shorter ' 'in patients who developed PPCs (444.8 m vs. 498.3 m; p = 0.013), and multivariable ' 'logistic regression confirmed 6MWD as an independent predictor of PPCs ' '(OR = 0.978; p = 0.010) for intestinal, gastric, and biliary tract resections [4]. ' 'In a prospective cohort of 100 liver transplant recipients, Magalhaes et al. (2017) ' 'demonstrated that every additional 50 m walked preoperatively was associated with a 41% ' 'reduction in the odds of postoperative respiratory complications ' '(OR = 0.589; 95% CI: 0.357–0.971; p = 0.03), establishing 6MWD as an independent ' 'predictor even in this complex surgical population [5].' ) add_para(bg7, size=12, space_after=6) bg8 = ( 'In oncologic surgery involving thoracoabdominal access, Inoue et al. (2020) found that ' 'a preoperative 6MWD of ≤454 m independently predicted grade II or higher Clavien-Dindo ' 'complications in 111 esophageal cancer patients undergoing thoracic surgery ' '(sensitivity 71.0%, specificity 54.8%) [6]. Similarly, Hattori et al. (2018) demonstrated ' 'in 321 patients undergoing lung resection for malignancy that a 6MWD of ≤450 m was ' 'significantly associated with postoperative pneumonia (p = 0.002), with 69.2% sensitivity ' 'and 71.1% specificity on ROC analysis [7]. These cut-off values, derived in thoracic ' 'surgical cohorts, provide a reasonable starting reference for comparable investigation ' 'in purely abdominal surgery populations, where the evidence remains sparse.' ) add_para(bg8, size=12, space_after=6) # --- Systematic review evidence ------------------------------------------- bg9 = ( 'At the level of systematic evidence, Makker et al. (2022) performed a meta-analysis of ' 'five studies encompassing 379 patients with gastrointestinal and abdominal cancer, ' 'finding that a preoperative 6MWT performance of ≥400 m was significantly associated with ' 'lower-grade postoperative complications (OR = 0.38; 95% CI: 0.15–0.95). The association ' 'with hospital length of stay, however, was not statistically significant ' '(MD = 3.29; 95% CI: -1.07 to 7.66) [8]. Argillander et al. (2022) reviewed objective ' 'preoperative physical tests in 23 studies of patients aged ≥65 undergoing major ' 'abdominal cancer surgery, concluding that the 6MWT and incremental shuttle walk test ' 'are feasible alternatives to CPET for aerobic capacity estimation, but that prospective ' 'studies with standardized protocols and consistent outcome definitions are still needed [9]. ' 'These reviews consistently identify a critical gap: the prospective prognostic value of ' 'a standardized preoperative 6MWT specifically in a non-oncologic, general major abdominal ' 'surgery population has not been rigorously established.' ) add_para(bg9, size=12, space_after=6) # --- Gap in local/Philippine context -------------------------------------- bg10 = ( 'In the Philippine clinical context, the routine preoperative assessment of functional ' 'capacity relies almost exclusively on clinical history and the subjective estimation of ' 'metabolic equivalents (METs). Formal exercise testing such as CPET is not routinely ' 'available outside academic tertiary centers. Published studies evaluating objective ' 'functional capacity measures as preoperative predictors of surgical complications in ' 'Filipino patients are essentially absent. Given the high incidence of major abdominal ' 'surgical disease, limited intensive care resources, and the need for practical and ' 'low-cost perioperative risk stratification tools in this setting, evaluating the 6MWT ' 'as a preoperative predictor fills a significant evidence gap. The present prospective ' 'cohort study is designed to address this gap by prospectively measuring preoperative ' '6MWD in adults undergoing major abdominal surgery and systematically ascertaining the ' 'occurrence of PPCs and major postoperative complications during the first 30 postoperative ' 'days.' ) add_para(bg10, size=12, space_after=12) # ════════════════════════════════════════════════════════════════════════════ # 4. OBJECTIVES # ════════════════════════════════════════════════════════════════════════════ add_section_heading('4', 'Objectives') # 4.1 General Objective add_subsection_heading('4.1.', 'General Objective') general_obj = ( 'To determine the prognostic value of the preoperative Six-Minute Walk Distance (6MWD) ' 'in predicting postoperative pulmonary complications and major postoperative complications ' 'among adults undergoing major abdominal surgery at a tertiary hospital.' ) add_para(general_obj, size=12, space_after=10) # 4.2 Specific Objectives add_subsection_heading('4.2.', 'Specific Objectives') specific_objs = [ ('1. ', 'To describe the baseline clinical and functional characteristics (including ' 'preoperative 6MWD, comorbidities, BMI, spirometry results, and ASA classification) ' 'of adult patients scheduled for major abdominal surgery.'), ('2. ', 'To determine the association between preoperative 6MWD and the occurrence of ' 'postoperative pulmonary complications (PPCs) within 30 days of surgery.'), ('3. ', 'To determine the association between preoperative 6MWD and the occurrence of ' 'major postoperative complications (Clavien-Dindo grade II or higher) within 30 days ' 'of surgery.'), ('4. ', 'To evaluate the relationship between preoperative 6MWD and secondary outcomes ' 'including: length of hospital stay, unplanned intensive care unit (ICU) admission, ' 'need for invasive or non-invasive mechanical ventilation, and in-hospital mortality.'), ('5. ', 'To identify an optimal preoperative 6MWD cut-off value, using ROC curve analysis, ' 'for predicting PPCs and major postoperative complications.'), ('6. ', 'To assess the discriminative accuracy of the preoperative 6MWT compared to ' 'established risk tools (ASA classification and ARISCAT score) in predicting PPCs.'), ] for num, text in specific_objs: add_bullet(num, text, indent=0.3) doc.add_paragraph() # ════════════════════════════════════════════════════════════════════════════ # 5. METHODS # ════════════════════════════════════════════════════════════════════════════ add_section_heading('5', 'Methods') # 5.1 Study Design, Time Period, Target Population add_subsection_heading('5.1.', 'Type of Study, Time Period and Target Population') study_design = ( 'This is a prospective analytic observational cohort study involving adult patients ' 'scheduled for elective or semi-elective major abdominal surgery at a tertiary hospital. ' 'Participants will undergo a standardized preoperative 6MWT and will be prospectively ' 'followed from the date of surgery until hospital discharge or 30 days postoperatively, ' 'whichever is shorter, for ascertainment of outcomes.' ) add_para(study_design, size=12, space_after=6) add_para('Time Period', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) tp1 = ( u'\u2022 Enrollment Period: Consecutive eligible patients will be enrolled over an ' 'estimated 12-month recruitment period.' ) tp2 = ( u'\u2022 Patient Follow-up: Each participant will be followed from the date of surgery ' 'through the 30th postoperative day (or until discharge if discharge occurs after ' 'day 30) for all outcome ascertainment.' ) for t in [tp1, tp2]: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.35) run = p.add_run(t) run.font.name = 'Times New Roman'; run.font.size = Pt(12) doc.add_paragraph() # 5.2 Criteria for Subject Selection add_subsection_heading('5.2.', 'Criteria for Subject Selection') add_para('5.2.1. Inclusion Criteria', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) inc = [ ('1. ', 'Age: ≥18 years old at the time of surgery.'), ('2. ', 'Surgery Type: Scheduled for elective or semi-elective major abdominal surgery ' '(intraperitoneal procedure with anticipated operative duration ≥60 minutes under ' 'general or regional anesthesia), including but not limited to colorectal resection, ' 'gastrectomy, hepatobiliary surgery, pancreatectomy, and small-bowel resection.'), ('3. ', 'Functional Assessment: Able to perform the preoperative 6MWT (must be ambulatory ' 'without a mobility aid that precludes standardized testing).'), ('4. ', 'Clinical Course: Inpatient stay resulting in either documented hospital discharge ' 'or documented in-hospital mortality.'), ('5. ', 'Consent: Provision of written informed consent prior to enrollment.'), ] for num, text in inc: add_bullet(num, text, indent=0.35) doc.add_paragraph() add_para('5.2.2. Exclusion Criteria', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) exc = [ ('1. ', 'Emergency Surgery: Patients undergoing emergency (non-elective) abdominal surgery ' 'in whom preoperative 6MWT cannot be safely performed.'), ('2. ', 'Inability to Walk: Patients who are non-ambulatory preoperatively or have ' 'neurological, orthopedic, or vascular conditions that independently preclude safe ' 'completion of a 6MWT (e.g., severe lower-limb ischemia, active musculoskeletal injury, ' 'hemiplegia).'), ('3. ', 'Hemodynamic Instability: Patients with resting hemodynamic instability or ' 'oxygen saturation <88% on room air at rest, in whom exercise testing is contraindicated.'), ('4. ', 'Severe Cardiorespiratory Disease: Patients with known unstable angina, acute ' 'decompensated heart failure, or acute exacerbation of COPD within four weeks of surgery.'), ('5. ', 'Prior Major Abdominal Surgery in the Same Admission: Patients undergoing ' 're-operation during the same index admission (to avoid confounding of outcomes).'), ('6. ', 'Data Incompleteness: Patients for whom key baseline or outcome data cannot ' 'be obtained.'), ] for num, text in exc: add_bullet(num, text, indent=0.35) doc.add_paragraph() # 5.3 Operational Definitions add_subsection_heading('5.3.', 'Operational Definitions, if applicable') # Build definitions table table = doc.add_table(rows=1, cols=2) table.style = 'Table Grid' table.columns[0].width = Inches(2.0) table.columns[1].width = Inches(4.0) hdr = table.rows[0].cells hdr[0].text = 'Variable' hdr[1].text = 'Definition' for cell in hdr: for run in cell.paragraphs[0].runs: run.bold = True run.font.size = Pt(11) run.font.name = 'Times New Roman' defs = [ ('Major Abdominal Surgery', 'Any intraperitoneal operative procedure (open or laparoscopic) anticipated to last ' '≥60 minutes under general or regional anesthesia, including colorectal resection, ' 'gastrectomy, hepatobiliary surgery, pancreatectomy, and small-bowel resection.'), ('Six-Minute Walk Test (6MWT)', 'A standardized submaximal exercise test in which the patient walks as far as possible ' 'on a flat, 30-meter corridor for six minutes. Administered per ATS 2002 guidelines. ' 'The primary metric is the six-minute walk distance (6MWD) in meters.'), ('Six-Minute Walk Distance (6MWD)', 'Total distance walked (in meters) during the 6MWT. A 6MWD below the study-defined ' 'cut-off (to be determined by ROC analysis) will classify the patient as having ' '"reduced functional capacity."'), ('Postoperative Pulmonary Complication (PPC)', 'Any of the following occurring within 30 days of surgery: (a) pneumonia — new ' 'pulmonary infiltrate with fever, leukocytosis, and purulent secretions; ' '(b) respiratory failure — SpO2 <90% on room air or requirement for mechanical ' 'ventilation beyond 24 hours postoperatively; (c) atelectasis — radiologically confirmed ' 'requiring physiotherapy or bronchoscopy; (d) pleural effusion — requiring drainage; ' '(e) bronchospasm — requiring bronchodilator treatment. Defined per StEP-COMPAC consensus.'), ('Major Postoperative Complication', 'Any postoperative complication graded Clavien-Dindo grade II or higher occurring ' 'within 30 days of surgery.'), ('Clavien-Dindo Grade II or Higher', 'Grade II: Complication requiring pharmacological treatment (e.g., antibiotics, ' 'anti-arrhythmics). Grade III: Requiring surgical, endoscopic, or radiological ' 'intervention. Grade IV: Life-threatening complication requiring ICU management. ' 'Grade V: Death.'), ('Unplanned ICU Admission', 'Transfer to the intensive care unit at any point following the initial return ' 'from the operating theater, not as part of the planned postoperative pathway.'), ('Mechanical Ventilation', 'Initiation of invasive mechanical ventilation via endotracheal tube or tracheostomy ' 'beyond the immediate post-anesthetic recovery period (>24 hours postoperatively).'), ('Non-Invasive Ventilation', 'Initiation of non-invasive positive pressure ventilation (CPAP, BiPAP) or ' 'high-flow nasal cannula (HFNC) beyond the immediate post-anesthetic recovery period.'), ('Prolonged Hospitalization', 'Total hospital length of stay exceeding the 75th percentile for the ' 'specific procedure type, or a stay of ≥14 days (whichever is defined a priori).'), ('In-Hospital Mortality', 'Death from any cause occurring during the index hospital admission.'), ('Reduced Functional Capacity', 'Preoperative 6MWD below the study-defined ROC-derived cut-off value, ' 'or a 6MWD of <400 m based on existing literature thresholds.'), ] for var, defn in defs: row = table.add_row() row.cells[0].text = var row.cells[1].text = defn for ci in [0, 1]: for run in row.cells[ci].paragraphs[0].runs: run.font.size = Pt(11) run.font.name = 'Times New Roman' add_para('Table 1: Operational Definitions', italic=True, size=11, align=WD_ALIGN_PARAGRAPH.CENTER, space_before=4, space_after=8) # 5.4 Study Procedure add_subsection_heading('5.4.', 'Description of Study Procedure') add_para('5.4.1. For observational (prospective cohort) studies:', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=4) add_para('5.4.1.1. Method of Subject Selection', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'Subjects will be identified prospectively from the surgical schedule of the institution. ' 'All adult patients listed for elective or semi-elective major abdominal surgery will be ' 'screened by the study team during the preoperative assessment visit, typically occurring ' '2–7 days prior to the scheduled operation. Eligible patients meeting inclusion criteria ' 'and providing written informed consent will be enrolled consecutively until the target ' 'sample size is achieved.', size=12, space_after=6 ) add_para('5.4.1.2. Data to Be Gathered', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'The following data points will be systematically collected using a standardized case ' 'report form:', size=12, space_after=4 ) data_items = [ ('Demographics: ', 'Age, sex, height, weight, body mass index (BMI).'), ('Clinical Characteristics: ', 'Comorbidities (e.g., COPD, diabetes mellitus, ' 'hypertension, ischemic heart disease, heart failure, chronic kidney disease, ' 'cerebrovascular disease), smoking status, ASA Physical Status classification, ' 'ARISCAT score.'), ('Exposure Variable: ', '6MWD (meters), resting and post-test heart rate, oxygen ' 'saturation (SpO2), Borg dyspnea scale, and reason for test termination (if applicable).'), ('Surgical Data: ', 'Type of procedure, operative approach (open vs. laparoscopic/robotic), ' 'estimated blood loss, operative duration, type of anesthesia.'), ('Postoperative Outcome Data (primary): ', 'Occurrence of any PPC within 30 days ' '(pneumonia, respiratory failure, atelectasis, pleural effusion, bronchospasm) — ' 'Yes/No with date.'), ('Postoperative Outcome Data (secondary): ', 'Clavien-Dindo grade of all complications, ' 'unplanned ICU admission, need for mechanical or non-invasive ventilation, length of ' 'hospital stay (days), in-hospital mortality.'), ] for label, text in data_items: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.4) r1 = p.add_run(u'\u2022 ' + label) r1.font.name = 'Times New Roman'; r1.font.size = Pt(12); r1.bold = True r2 = p.add_run(text) r2.font.name = 'Times New Roman'; r2.font.size = Pt(12) doc.add_paragraph() add_para('5.4.1.3. Description of Procedures to Be Done to Subjects', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'Each enrolled participant will undergo one standardized preoperative 6MWT performed ' 'by a trained research physiotherapist or nurse, within 2–7 days prior to surgery, ' 'following ATS (2002) guidelines. The test will be conducted on a flat, indoor, ' '30-meter corridor, clearly marked at each end. Standardized verbal encouragement ' 'will be provided at one-minute intervals. Participants will be instructed to walk as ' 'fast as safely possible for six minutes, and are permitted to slow down or stop if ' 'needed. Resting SpO2, heart rate, and Borg dyspnea scale will be recorded immediately ' 'before and after the test. The test will be terminated early if any safety criterion ' 'is met (SpO2 <85%, chest pain, acute dyspnea, or patient request). No other study ' 'procedures will be performed; all postoperative data will be obtained through ' 'prospective chart review and clinical follow-up.', size=12, space_after=6 ) add_para('5.4.1.4. Instruments Used for Measuring Exposure and/or Outcome', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) instruments = [ ('Exposure (6MWT): ', 'A measured 30-meter corridor, pulse oximeter, stopwatch, and ' 'Borg dyspnea scale. Distance will be recorded in meters to the nearest meter.'), ('Outcome Assessment (PPCs): ', 'Clinical, radiologic, and laboratory findings ' 'documented in the official patient chart by the attending surgical and medical team, ' 'adjudicated against the StEP-COMPAC consensus PPC definition.'), ('Outcome Assessment (Clavien-Dindo Grade): ', 'Classified by the principal investigator ' 'based on chart review of all postoperative events, using the standard ' 'Clavien-Dindo classification.'), ('Data Abstraction: ', 'A standardized Case Report Form (CRF) will serve as the primary ' 'instrument for uniform data collection.'), ('Risk Scores: ', 'ASA classification assigned by the attending anesthesiologist; ' 'ARISCAT score computed from seven preoperative variables at time of enrollment.'), ] for label, text in instruments: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.4) r1 = p.add_run(u'\u2022 ' + label) r1.font.name = 'Times New Roman'; r1.font.size = Pt(12); r1.bold = True r2 = p.add_run(text) r2.font.name = 'Times New Roman'; r2.font.size = Pt(12) doc.add_paragraph() add_para('5.4.1.5. Method of Validating Measuring Instruments', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'The 6MWT will be administered according to the standardized ATS 2002 protocol, ' 'ensuring reproducibility and comparability with published normative and prognostic ' 'data. Research personnel performing the test will undergo a standardized training ' 'session prior to study commencement to ensure protocol fidelity. Pulse oximeters ' 'will be calibrated and validated per hospital biomedical engineering standards. ' 'Postoperative outcome adjudication will be performed by two independent investigators ' 'blinded to the 6MWD results, with discrepancies resolved by consensus.', size=12, space_after=6 ) add_para('5.4.1.6. Laboratory Procedures to Be Performed, if any', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'No study-specific laboratory procedures will be performed beyond routine preoperative ' 'workup. Preoperative spirometry results (FEV1, FVC, FEV1/FVC) will be recorded if ' 'available as part of standard preoperative care. Routine admission laboratory values ' '(complete blood count, serum albumin, serum creatinine) will be extracted from the ' 'medical record.', size=12, space_after=6 ) add_para('5.4.1.7. Follow-Up Procedures', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'All enrolled patients will be followed prospectively from the date of surgery. ' 'Research personnel will perform daily postoperative chart reviews while the patient ' 'is hospitalized, and a structured clinical review at postoperative day 30 ' '(or at hospital discharge, whichever is later) to ascertain all outcome events. ' 'Patients discharged before day 30 will be contacted by telephone and/or reviewed ' 'at their scheduled outpatient follow-up appointment for 30-day outcome data.', size=12, space_after=8 ) # 5.5 Outcome Measures add_subsection_heading('5.5.', 'Description of Outcome Measures') add_para( 'The primary outcome measure is the occurrence of any postoperative pulmonary ' 'complication (PPC) within 30 days of surgery, defined per the StEP-COMPAC consensus ' 'framework. The rationale for selecting PPCs as the primary outcome is their high ' 'clinical relevance, direct link to impaired preoperative cardiorespiratory reserve, ' 'and consistent use as the primary outcome across the existing 6MWT perioperative ' 'literature [4,5,7,8].', size=12, space_after=6 ) add_para( 'A co-primary outcome is the occurrence of any major postoperative complication ' '(Clavien-Dindo grade II or higher) within 30 days of surgery. This broader composite ' 'outcome captures major systemic complications beyond the pulmonary domain and is ' 'consistent with grading systems used in comparable surgical outcome studies [6].', size=12, space_after=6 ) add_para( 'Secondary outcome measures include: length of hospital stay (continuous, in days), ' 'unplanned ICU admission (dichotomous — Yes/No), need for invasive mechanical ' 'ventilation beyond 24 hours postoperatively (dichotomous), need for non-invasive ' 'ventilation or high-flow nasal cannula beyond the immediate recovery period ' '(dichotomous), and in-hospital mortality (dichotomous). These secondary outcomes ' 'were selected based on their clinical relevance, their established association with ' 'reduced preoperative functional capacity, and their consistent use in comparable ' 'cohort studies and systematic reviews [3,4,5,8].', size=12, space_after=8 ) # 5.6 Sample Size add_subsection_heading('5.6.', 'Sample Size Estimation') add_para( 'Sample size was estimated based on the hypothesis that a lower preoperative 6MWD is ' 'independently associated with a higher rate of PPCs. Using data from Soares and Nucci ' '(2021) as the primary reference — which reported a PPC incidence of 30% in patients ' 'with 6MWD ≥400 m and 65% in those with 6MWD <400 m — with a two-sided alpha of 0.05, ' 'power of 80%, and an anticipated 1:1 ratio of exposed (low 6MWD) to unexposed (normal ' '6MWD) participants, the initial sample size is calculated at approximately 38 patients ' 'per group (76 total). To account for multivariable adjustment of up to 6 covariates ' '(at 10 events per variable) and an estimated 15% loss to follow-up or incomplete data, ' 'the final target sample size is 120 participants. Sample size was computed using ' 'standard logistic regression sample size formulae.', size=12, space_after=8 ) # 5.7 Data Analysis add_subsection_heading('5.7.', 'Data Analysis') add_para( 'Statistical analyses will be performed using SPSS version 29.0 or R (version 4.3 or ' 'higher). Descriptive statistics will summarize baseline clinical and functional ' 'characteristics. Categorical variables will be reported as frequencies and percentages; ' 'continuous variables will be reported as mean ± standard deviation or median ' '(interquartile range) depending on distribution. Univariable comparisons between ' 'patients who develop PPCs and those who do not will use the Chi-squared test or ' 'Fisher\'s exact test for categorical variables and the independent-samples t-test or ' 'Mann-Whitney U test for continuous variables, as appropriate.', size=12, space_after=6 ) add_para( 'The primary hypothesis will be tested using multivariable binary logistic regression, ' 'with PPC occurrence as the dependent variable and preoperative 6MWD as the primary ' 'independent variable, adjusting for clinically relevant covariates identified a priori ' '(age, sex, BMI, ASA class, operative duration, and procedure type). Results will be ' 'expressed as odds ratios (OR) with 95% confidence intervals (CI).', size=12, space_after=6 ) add_para( 'Receiver Operating Characteristic (ROC) curve analysis will be used to determine the ' 'optimal 6MWD cut-off value for predicting PPCs and major postoperative complications, ' 'with the Youden index used to identify the threshold that maximizes sensitivity and ' 'specificity. The area under the ROC curve (AUROC) will be calculated for the 6MWT, ' 'ASA classification, and ARISCAT score, with pairwise AUROC comparisons performed to ' 'assess the discriminative performance of the 6MWT relative to established risk tools. ' 'The level of significance is set at α = 0.05 (two-sided).', size=12, space_after=8 ) # 5.8 Ethical Considerations add_subsection_heading('5.8.', 'Ethical Consideration') add_para( 'This prospective study may enroll participants spanning a range of age groups, including ' 'elderly patients, and may include individuals with significant comorbidities. Given that ' 'the 6MWT is a validated, widely used clinical assessment with an established safety ' 'profile, and that no additional invasive procedures will be performed beyond routine ' 'preoperative care, the risk to participants is considered minimal. Strict confidentiality ' 'of all participant data will be maintained. All study records will be coded and ' 'de-identified, and investigators are responsible for the accuracy, completeness, ' 'and integrity of all collected data.', size=12, space_after=6 ) add_para('5.8.1. Method/s of Dealing with Adverse Events', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'While the 6MWT is associated with very low risk in supervised settings, the test will ' 'be immediately terminated if the participant develops chest pain, severe dyspnea, ' 'dizziness, leg cramps, pallor, or SpO2 <85%. A qualified clinician will be available ' 'during all test sessions and emergency protocols will be in place. Any adverse event ' 'occurring during the 6MWT will be documented, reported to the Principal Investigator, ' 'and managed per institutional protocols. Serious adverse events will be reported to ' 'the IERC within the required timeframe.', size=12, space_after=6 ) add_para('5.8.2. Anticipated Risks and Discomforts to Subjects', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'The anticipated physical risk to participants is minimal, limited primarily to the ' 'physiologic exertion of walking at a self-selected pace for six minutes, which is ' 'analogous to activities of daily living. Potential discomforts include transient ' 'breathlessness and fatigue, which are expected and self-limiting. Pre-test safety ' 'screening will exclude participants for whom exercise testing is contraindicated.', size=12, space_after=6 ) add_para('5.8.3. Expected Benefits to the Subject and to Others', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'The results of this study are expected to establish whether the preoperative 6MWT ' 'independently predicts PPCs and major complications following major abdominal surgery. ' 'If validated, the 6MWT could provide clinicians with a simple, immediately implementable ' 'preoperative risk stratification tool that enables targeted preventive interventions ' '(prehabilitation, physiotherapy, anesthesia optimization) in high-risk patients. ' 'The study will generate locally relevant evidence applicable to Filipino patients ' 'and similar resource-limited surgical settings.', size=12, space_after=6 ) add_para('5.8.4. Protection of Confidentiality', bold=True, size=12, align=WD_ALIGN_PARAGRAPH.LEFT, space_after=3) add_para( 'The following procedures will be strictly adhered to:', size=12, space_after=4 ) conf_items = [ 'A. The study shall abide by the Principles of the Declaration of Helsinki (2013) and ' 'will be conducted in accordance with the Guidelines of the International Conference ' 'on Harmonization – Good Clinical Practice (ICH-GCP).', 'B. The Clinical Protocol and all relevant documents shall be reviewed and approved ' 'by the SLMC Institutional Ethics Review Committee (IERC) prior to enrollment of any participant.', 'C. Patient confidentiality shall be maintained by assigning each participant a unique ' 'study code. No identifying information (name, birth date, hospital number) will be ' 'included in any study database or report.', 'D. Data Storage and Security: All study data will be stored in a password-protected, ' 'encrypted file accessible only to the Principal Investigator and Co-Investigators. ' 'All study documents will be retained by the Principal Investigator for a minimum of ' '5 years after study completion, after which they will be securely destroyed.', 'E. Inspection of Records: Access to study records is restricted to the Principal ' 'Investigator, Co-Investigators, and duly authorized representatives of the IERC ' 'or institutional audit bodies.', 'F. Results will be disseminated only in aggregate, de-identified form through ' 'peer-reviewed publication or scientific conference presentation.', ] for item in conf_items: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.35) run = p.add_run(item) run.font.name = 'Times New Roman'; run.font.size = Pt(12) doc.add_paragraph() # ════════════════════════════════════════════════════════════════════════════ # 7. REFERENCES (with new additions [10]–[14]) # ════════════════════════════════════════════════════════════════════════════ p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(12) p.paragraph_format.space_after = Pt(6) run = p.add_run('7. References') run.font.name = 'Times New Roman'; run.font.size = Pt(12); run.bold = True all_refs = [ ('[1]', 'Smetana GW, Lawrence VA, Cornell JE; American College of Physicians. ' 'Preoperative pulmonary risk stratification for noncardiothoracic surgery: systematic ' 'review for the American College of Physicians. Ann Intern Med. 2006 Apr 18;144(8):581–95. ' 'doi: 10.7326/0003-4819-144-8-200604180-00009.'), ('[2]', 'Garg S, Govindaraj V, Dwivedi DP, Raja K, Theerthar EP. Postoperative pulmonary ' 'complications in patients undergoing upper abdominal surgery: risk factors and predictive ' 'models. Monaldi Arch Chest Dis. 2025 Mar 31. doi: 10.4081/monaldi.2024.2915. PMID: 38526466.'), ('[3]', 'Rose GA, Davies RG, Appadurai IR, Williams IM, Bashir M, Berg RMG. \'Fit for ' 'surgery\': the relationship between cardiorespiratory fitness and postoperative outcomes. ' 'Exp Physiol. 2022 Aug;107(8):780–95. doi: 10.1113/EP090156. PMID: 35579479.'), ('[4]', 'Soares SMTP, Nucci LB. Association between early pulmonary complications after ' 'abdominal surgery and preoperative physical capacity. Physiother Theory Pract. 2021 ' 'Jul;37(7):852–9. doi: 10.1080/09593985.2019.1650404. PMID: 31402737.'), ('[5]', 'Magalhaes CBA, Nogueira IC, Marinho LS, Daher EF, Garcia JHP, Viana CFG. Exercise ' 'capacity impairment can predict postoperative pulmonary complications after liver ' 'transplantation. Respiration. 2017;94(6):538–44. doi: 10.1159/000479008. PMID: 28738386.'), ('[6]', 'Inoue T, Ito S, Kanda M, Niwa Y, Nagaya M, Nishida Y. Preoperative six-minute ' 'walk distance as a predictor of postoperative complication in patients with esophageal ' 'cancer. Dis Esophagus. 2020 Mar 5;33(3):doz050. doi: 10.1093/dote/doz050. PMID: 31111872.'), ('[7]', 'Hattori K, Matsuda T, Takagi Y, Nagaya M, Inoue T, Nishida Y. Preoperative ' 'six-minute walk distance is associated with pneumonia after lung resection. Interact ' 'Cardiovasc Thorac Surg. 2018 Feb 1;26(2):208–13. doi: 10.1093/icvts/ivx310. PMID: 29049742.'), ('[8]', 'Makker PGS, Koh CE, Solomon MJ, Steffens D. Preoperative functional capacity and ' 'postoperative outcomes following abdominal and pelvic cancer surgery: a systematic review ' 'and meta-analysis. ANZ J Surg. 2022 Jul;92(7-8):1732–40. doi: 10.1111/ans.17577. ' 'PMID: 35253333.'), ('[9]', 'Argillander TE, Heil TC, Melis RJF, van Duijvendijk P, Klaase JM, van Munster BC. ' 'Preoperative physical performance as predictor of postoperative outcomes in patients aged ' '65 and older scheduled for major abdominal cancer surgery: a systematic review. Eur J Surg ' 'Oncol. 2022 Mar;48(3):575–84. doi: 10.1016/j.ejso.2021.09.019. PMID: 34629224.'), ('[10]', 'STARSurg Collaborative and TASMAN Collaborative. Evaluation of prognostic risk ' 'models for postoperative pulmonary complications in adult patients undergoing major ' 'abdominal surgery: a systematic review and international external validation cohort study. ' 'Lancet Digit Health. 2022 Jul;4(7):e498–e507. doi: 10.1016/S2589-7500(22)00069-3. ' 'PMID: 35750401.'), ('[11]', 'Boden I, Reeve J, Jernas A, Denehy L, Fagevik Olsen M. Preoperative physiotherapy ' 'prevents postoperative pulmonary complications after major abdominal surgery: a ' 'meta-analysis of individual patient data. J Physiother. 2024 Jul;70(3):195–202. ' 'doi: 10.1016/j.jphys.2024.02.012. PMID: 38472053.'), ('[12]', 'Dankert A, Dohrmann T, Loser B, Zapf A, Zollner C, Petzoldt M. Pulmonary function ' 'tests for the prediction of postoperative pulmonary complications. Dtsch Arztebl Int. ' '2022 Feb 18;119(7):99–106. doi: 10.3238/arztebl.m2022.0074. PMID: 34939921.'), ('[13]', 'Otadi K, Malmir K. Normative reference values for the six-minute walk test in ' 'older adults: a systematic review and meta-analysis. Arch Gerontol Geriatr. 2026 ' 'Jan;128:106026. doi: 10.1016/j.archger.2025.106026. PMID: 41027267.'), ('[14]', 'Yeung MT, Chan MY, Huang KS, Chen TJ, Chia CP, Fong MM. Normative reference values ' 'and regression equations to predict the 6-minute walk distance in the Asian adult ' 'population aged 21-80 years. Hong Kong Physiother J. 2022 Dec;42(2):69–78. ' 'doi: 10.1142/S1013702522500111. PMID: 37560171.'), ] for num, text in all_refs: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.4) p.paragraph_format.first_line_indent = Inches(-0.4) r1 = p.add_run(num + ' ') r1.font.name = 'Times New Roman'; r1.font.size = Pt(12) r2 = p.add_run(text) r2.font.name = 'Times New Roman'; r2.font.size = Pt(12) # Footer doc.add_paragraph() fp = doc.add_paragraph() fp.alignment = WD_ALIGN_PARAGRAPH.RIGHT fp.paragraph_format.space_before = Pt(24) r = fp.add_run('Protocol Version 01 dated ________________') r.font.name = 'Times New Roman'; r.font.size = Pt(10) # ── Save ───────────────────────────────────────────────────────────────────── out = '/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Complete.docx' doc.save(out) print(f'Saved: {out}') PYEOF python3 /tmp/workspace/6mwt-proposal/append_sections.py

cat << 'PYEOF' > /tmp/workspace/6mwt-proposal/build_complete.py from docx import Document from docx.shared import Pt, Inches, RGBColor from docx.enum.text import WD_ALIGN_PARAGRAPH doc = Document() # ── Page margins ───────────────────────────────────────────────────────────── for section in doc.sections: section.top_margin = Inches(1.0) section.bottom_margin = Inches(1.0) section.left_margin = Inches(1.25) section.right_margin = Inches(1.0) # ── Default style ───────────────────────────────────────────────────────────── style = doc.styles['Normal'] style.font.name = 'Times New Roman' style.font.size = Pt(12) style.paragraph_format.space_after = Pt(0) style.paragraph_format.space_before = Pt(0) # ── Helpers ─────────────────────────────────────────────────────────────────── def set_font(run, bold=False, italic=False, size=12, name='Times New Roman'): run.font.name = name; run.font.size = Pt(size) run.bold = bold; run.italic = italic def para(text='', bold=False, italic=False, size=12, align=WD_ALIGN_PARAGRAPH.JUSTIFY, sb=0, sa=6, li=0, fi=0): p = doc.add_paragraph() p.alignment = align p.paragraph_format.space_before = Pt(sb) p.paragraph_format.space_after = Pt(sa) p.paragraph_format.left_indent = Inches(li) p.paragraph_format.first_line_indent = Inches(fi) if text: r = p.add_run(text) set_font(r, bold=bold, italic=italic, size=size) return p def sec_h(num, title): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(12); p.paragraph_format.space_after = Pt(6) r = p.add_run(f"{num}. {title}") set_font(r, bold=True) def sub_h(num, title): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(8); p.paragraph_format.space_after = Pt(4) r = p.add_run(f"{num} {title}") set_font(r, bold=True) def bullet(label, text, li=0.35): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(li) r1 = p.add_run(label); set_font(r1, bold=True) r2 = p.add_run(text); set_font(r2) def dot(label, text, li=0.4): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(li) r1 = p.add_run(u'\u2022 ' + label); set_font(r1, bold=True) r2 = p.add_run(text); set_font(r2) def ref_entry(num, text): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.4) p.paragraph_format.first_line_indent = Inches(-0.4) r1 = p.add_run(num + ' '); set_font(r1) r2 = p.add_run(text); set_font(r2) # ════════════════════════════════════════════════════════════════════════════ # HEADER # ════════════════════════════════════════════════════════════════════════════ para('DATABANK INFO NEEDED:', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=2) para('No Yes', align=WD_ALIGN_PARAGRAPH.LEFT, sa=2) para('1. R&B Form No. 1A', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=4) para('St. Luke\'s Medical Center', bold=True, align=WD_ALIGN_PARAGRAPH.CENTER, sa=2) para('RESEARCH AND BIOTECHNOLOGY', bold=True, align=WD_ALIGN_PARAGRAPH.CENTER, sa=2) para('1.1. CLINICAL RESEARCH PROPOSAL', bold=True, align=WD_ALIGN_PARAGRAPH.CENTER, sa=10) para('Research Title:', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'Prognostic Value of the Six-Minute Walk Test in Predicting Postoperative Pulmonary ' 'and Major Complications Among Adults Undergoing Major Abdominal Surgery: ' 'A Prospective Cohort Study', align=WD_ALIGN_PARAGRAPH.LEFT, sa=10 ) para('Investigators:', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) # Investigators table tbl = doc.add_table(rows=4, cols=2) tbl.style = 'Table Grid' tbl.columns[0].width = Inches(3.5) tbl.columns[1].width = Inches(2.5) for i, h in enumerate(['Name and Signature', 'Unit/Position']): c = tbl.cell(0, i); c.text = h for r in c.paragraphs[0].runs: r.bold = True; r.font.size = Pt(11); r.font.name = 'Times New Roman' rows_data = [ ('Project Leader/s:\n\n_______________________________', 'Consultant\n(Consultant/Manager/Faculty)'), ('Co-Project Leader/s:\n\n_______________________________', 'Pulmonary/Surgery Fellow\n(Resident/Fellow/Student)'), ('Research Fellow:\n\n_______________________________', ''), ] for i, (n, u) in enumerate(rows_data): tbl.cell(i+1, 0).text = n; tbl.cell(i+1, 1).text = u for ci in [0, 1]: for r in tbl.cell(i+1, ci).paragraphs[0].runs: r.font.size = Pt(11); r.font.name = 'Times New Roman' doc.add_paragraph() para('Inst./Dept./Center/Group: Department of Surgery / Anesthesiology', align=WD_ALIGN_PARAGRAPH.LEFT, sa=12) # ════════════════════════════════════════════════════════════════════════════ # SECTION 2 – BRIEF DESCRIPTION / SUMMARY # ════════════════════════════════════════════════════════════════════════════ sec_h('2', 'Brief Description / Summary') para( 'Major abdominal surgery carries a significant risk of postoperative pulmonary ' 'complications (PPCs) and other major adverse outcomes, which contribute substantially ' 'to perioperative morbidity and mortality. Identifying patients at high risk before surgery ' 'enables targeted preventive strategies, yet current preoperative risk tools are either ' 'resource-intensive or rely on subjective estimates of functional capacity.', sa=6 ) para( 'This study investigates the prognostic value of the Six-Minute Walk Test (6MWT), ' 'a simple, low-cost, and widely available field exercise test that objectively quantifies ' 'functional exercise capacity through the distance walked in six minutes (6MWD). The 6MWT ' 'is hypothesized to serve as a composite marker reflecting cardiorespiratory reserve, ' 'physical conditioning, and overall physiologic resilience — factors directly relevant to ' 'the ability to withstand surgical stress.', sa=6 ) para( 'This will be a prospective cohort study at a tertiary hospital involving adult patients ' 'scheduled for elective or semi-elective major abdominal surgery. The 6MWT will be ' 'performed preoperatively, and participants will be followed through the postoperative ' 'period to ascertain the occurrence of PPCs and other major complications. The 6MWT could ' 'offer clinicians a practical, accessible, and inexpensive preoperative risk stratification ' 'tool, enabling timely optimization and potentially improving patient outcomes in both ' 'resource-rich and resource-limited settings.', sa=12 ) # ════════════════════════════════════════════════════════════════════════════ # SECTION 3 – INTRODUCTION # ════════════════════════════════════════════════════════════════════════════ sec_h('3', 'Introduction') # ─── 3.1 Significance ──────────────────────────────────────────────────────── sub_h('3.1.', 'Significance of the Project') para( 'Major abdominal surgery encompasses a broad range of high-risk procedures including ' 'colorectal resection, hepatobiliary surgery, gastrectomy, and pancreaticoduodenectomy. ' 'These procedures are associated with postoperative pulmonary complication rates ranging ' 'from 9% to 40%, depending on patient demographics, comorbidities, and surgical complexity ' '[1]. PPCs — encompassing pneumonia, respiratory failure, atelectasis requiring intervention, ' 'pleural effusion, bronchospasm, and aspiration — are among the most common causes of ' 'perioperative morbidity, prolonged hospital stay, and mortality following abdominal surgery [2].', sa=6 ) para( 'Despite their clinical importance, a reliable and practical bedside tool for preoperative ' 'risk prediction of PPCs remains elusive. Current tools such as the ARISCAT (Assess Respiratory ' 'Risk in Surgical Patients in Catalonia) score and ASA Physical Status classification provide ' 'general risk estimates but do not directly capture an individual\'s functional reserve. ' 'Cardiopulmonary exercise testing (CPET) is widely regarded as the gold standard for objective ' 'preoperative functional assessment, but it requires specialized equipment, trained personnel, ' 'and considerable time and cost, limiting its routine use especially in resource-limited ' 'settings [3].', sa=6 ) para( 'The Six-Minute Walk Test (6MWT) offers a compelling alternative: it requires no specialized ' 'equipment beyond a measured corridor, takes less than ten minutes to administer, and yields ' 'an objective, reproducible measure of submaximal exercise tolerance — the six-minute walk ' 'distance (6MWD). The 6MWT is already validated and widely used in cardiopulmonary ' 'rehabilitation and chronic disease management. Its perioperative application, particularly ' 'in abdominal surgery, is an emerging area of study with important clinical and public health ' 'implications.', sa=6 ) para('The study aims to:', sa=4) aims = [ ('1. ', 'Determine the prognostic value of preoperative 6MWD in predicting PPCs and major ' 'postoperative complications in adults undergoing major abdominal surgery at a tertiary hospital.'), ('2. ', 'Identify an optimal 6MWD cut-off value that discriminates patients at high versus ' 'low risk for PPCs, enabling bedside clinical risk stratification.'), ('3. ', 'Contribute locally relevant evidence on preoperative functional capacity assessment ' 'in a setting where CPET is not routinely available, supporting cost-effective perioperative ' 'care pathways.'), ] for num, text in aims: bullet(num, text, li=0.3) doc.add_paragraph() # ─── 3.2 Rationale ─────────────────────────────────────────────────────────── sub_h('3.2.', 'Rationale for Doing the Study') para( 'Timely and accurate preoperative risk stratification remains a persistent challenge in the ' 'perioperative management of patients undergoing major abdominal surgery. Existing severity ' 'scoring systems and risk indices are often underutilized due to complexity, limited ' 'applicability across different populations, or the absence of objective measures of a ' 'patient\'s functional reserve.', sa=6 ) para( 'Functional capacity — defined as the ability of an individual to perform physical activities ' 'that require aerobic metabolism — is a well-established, independent determinant of ' 'perioperative risk. Rose et al. (2022) reviewed the physiological basis linking cardiorespiratory ' 'fitness (CRF) to postoperative outcomes, demonstrating that impaired CRF is an independent risk ' 'factor for mortality and morbidity. Surgery triggers a period of substantially increased oxygen ' 'demand; patients unable to meet this demand face greater risk of organ failure and death. ' 'The authors emphasized that CRF is the greatest modifiable perioperative risk factor, and its ' 'accurate preoperative detection is essential for risk classification and patient management [3].', sa=6 ) para( 'The 6MWT provides an objective, standardized measure of submaximal exercise capacity that is ' 'closely correlated with peak oxygen consumption (VO2 peak) and reflects the integrated response ' 'of the cardiorespiratory, neuromuscular, and metabolic systems. Unlike CPET, the 6MWT is simple, ' 'inexpensive, and reproducible, making it practical for routine preoperative assessment even in ' 'settings with limited resources. Crucially, the 6MWT captures not only cardiorespiratory fitness ' 'but also the patient\'s nutritional status, muscle strength, and motivational state — all factors ' 'that independently influence surgical outcomes.', sa=6 ) para( 'Several studies have examined the relationship between preoperative 6MWD and postoperative ' 'outcomes. Soares and Nucci (2021) conducted a prospective cohort study of 50 patients ' 'undergoing elective abdominal surgery, finding that 25 (50%) developed postoperative pulmonary ' 'complications within the first seven postoperative days. The mean preoperative 6MWD was ' 'significantly shorter among those who developed PPCs (444.8 m vs. 498.3 m; p = 0.013). ' 'Multivariable logistic regression confirmed that a lower preoperative 6MWD was significantly ' 'and independently associated with PPCs (OR = 0.978; p = 0.010) in patients undergoing ' 'intestinal, gastric, or biliary tract resection [4].', sa=6 ) para( 'Extending this evidence to other abdominal organ surgeries, Magalhaes et al. (2017) ' 'prospectively studied 100 patients undergoing liver transplantation, finding that 44 developed ' 'at least one postoperative respiratory complication. In logistic regression analysis, each ' 'additional 50 meters walked during the preoperative 6MWT was associated with a 41% reduction ' 'in the odds of developing PPCs (OR = 0.589; 95% CI: 0.357–0.971; p = 0.03), establishing the ' '6MWT as an independent predictor of postoperative pulmonary complications in this population [5].', sa=6 ) para( 'In the oncologic setting, Inoue et al. (2020) retrospectively reviewed 111 patients undergoing ' 'thoracic surgery for esophageal cancer and found that a preoperative 6MWD of ≤454 m was a ' 'significant threshold for predicting grade II or higher Clavien-Dindo complications, with 71.0% ' 'sensitivity and 54.8% specificity. In multiple regression analysis, lower 6MWD was an ' 'independent preoperative risk factor for major complications [6]. Similarly, Hattori et al. ' '(2018) demonstrated in a retrospective analysis of 321 patients undergoing lung resection for ' 'malignancy that a preoperative 6MWD ≤450 m predicted postoperative pneumonia with 69.2% ' 'sensitivity and 71.1% specificity (p = 0.002) [7].', sa=6 ) para( 'At the level of systematic evidence, Makker et al. (2022) performed a systematic review and ' 'meta-analysis of five studies (379 patients) evaluating preoperative 6MWT or five-times ' 'sit-to-stand performance and postoperative outcomes in gastrointestinal and abdominal cancer ' 'surgery. Higher preoperative 6MWT performance (≥400 m) was significantly associated with ' 'lower-grade postoperative complications (OR = 0.38; 95% CI: 0.15–0.95), though the association ' 'with length of stay was not significant. The authors noted the need for high-quality prospective ' 'studies with standardized definitions and broader patient populations [8].', sa=6 ) para( 'Argillander et al. (2022) conducted a systematic review of preoperative physical performance ' 'tests and their predictive value for postoperative outcomes specifically in patients aged ≥65 ' 'years undergoing major abdominal cancer surgery. Among non-CPET field tests, the 6MWT and the ' 'Incremental Shuttle Walk Test (ISWT) predicted outcomes in two studies each. The authors ' 'concluded that the 6MWT is a feasible alternative to CPET for estimating aerobic capacity in ' 'older surgical patients, but emphasized the need for prospective studies comparing different ' 'physical tests in a standardized manner [9].', sa=6 ) para( 'In a recent study by Garg et al. (2025) evaluating predictive models for PPCs in upper ' 'abdominal surgery, 20.3% of 133 patients developed PPCs. While the study\'s multivariable ' 'analysis highlighted abnormal chest radiograph, blood urea nitrogen, and duration of surgery ' 'as independent predictors, the investigators specifically tested the 6MWT against established ' 'risk scores. Although 6MWD lacked independent predictive power in that particular cohort, the ' 'authors acknowledged that the study was limited by its single-centre retrospective design and ' 'variable timing of 6MWT administration, and called for prospective designs with standardized ' 'protocols to better characterize the 6MWT\'s predictive role [2].', sa=6 ) para( 'The 6MWT uniquely serves as a composite indicator: reduced 6MWD reflects not only limited ' 'cardiorespiratory reserve but also deconditioning, sarcopenia, and poor nutritional status — ' 'all factors shown to independently worsen surgical outcomes. Since the 6MWT is inexpensive, ' 'non-invasive, and requires minimal equipment or personnel training, it is ideally suited for ' 'routine preoperative application in most hospital settings, including those with limited access ' 'to CPET or advanced physiologic testing.', sa=6 ) para( 'Locally, there is a significant evidence gap regarding the use of objective functional capacity ' 'measures in preoperative risk assessment for abdominal surgery. Existing perioperative practice ' 'largely relies on subjective estimates of metabolic equivalents (METs) via patient history rather ' 'than objective testing. Given the high burden of abdominal surgical disease in the Philippines ' 'and the challenges of access to advanced perioperative testing, there is a compelling rationale ' 'to evaluate whether the 6MWT — a simple, low-cost tool — can reliably predict PPCs and major ' 'complications in a local surgical population. Demonstrating its predictive value could establish ' 'the 6MWT as a practical and immediately implementable preoperative risk stratification tool for ' 'Filipino surgical patients and similar resource-constrained settings.', sa=12 ) # ─── 3.3 Background Information ────────────────────────────────────────────── sub_h('3.3.', 'Background Information and Brief Literature Review') para( 'Major abdominal surgery — defined as intraperitoneal procedures lasting more than one hour ' 'under general or regional anesthesia — represents one of the highest-risk categories of ' 'elective surgical care worldwide. Procedures in this group include open and laparoscopic ' 'colorectal resection, gastrectomy, hepatectomy, pancreatectomy, esophagectomy, and ' 'small-bowel resection. Globally, more than 300 million major surgical operations are performed ' 'annually, and the complication burden after abdominal surgery remains a major driver of ' 'perioperative mortality, intensive care utilization, and healthcare costs [1].', sa=6 ) para( 'Postoperative pulmonary complications (PPCs) are among the most frequent and clinically ' 'consequential complications following major abdominal surgery. Based on the consensus ' 'Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative ' 'and Anaesthetic Care (StEP-COMPAC) definition, PPCs encompass a spectrum of disorders ' 'including pneumonia, respiratory failure requiring ventilatory support, pleural effusion ' 'requiring drainage, bronchospasm, and atelectasis requiring intervention. In a large ' 'international cohort study of 11,591 patients undergoing major abdominal surgery, the overall ' 'PPC rate was 7.8% using the StEP-COMPAC definition; however, rates vary widely (9%–40%) ' 'depending on the operative site, patient population, and PPC definition used [10]. Among ' 'patients undergoing upper abdominal surgery specifically, Garg et al. (2025) reported a PPC ' 'incidence of 20.3%, with pleural effusion (11.3%), respiratory failure (7.5%), and pneumonia ' '(4.5%) as the most common events [2].', sa=6 ) para( 'PPCs carry substantial prognostic weight. They are independently associated with prolonged ' 'hospital stay, escalation of care to the intensive care unit, increased 30-day and 90-day ' 'mortality, and significantly higher resource utilization. Boden et al. (2024) demonstrated ' 'in an individual patient-level meta-analysis of 800 patients across two randomized controlled ' 'trials that a single preoperative physiotherapy session reduced the odds of PPCs by 47% ' '(adjusted OR 0.53; 95% CI: 0.34–0.85), underscoring both the preventability of PPCs and the ' 'importance of identifying at-risk patients preoperatively [11].', sa=6 ) para( 'Current tools for preoperative PPC risk stratification are either complex, resource-intensive, ' 'or insufficiently validated. Existing risk prediction models — including the ARISCAT score, ' 'ASA Physical Status classification, Gupta Respiratory Failure Index, and spirometry-based risk ' 'estimates — show only moderate discriminative ability. In the STARSurg/TASMAN international ' 'validation study, none of the six externally validated prognostic models showed good ' 'discrimination (defined as AUROC ≥0.70) for PPCs; the ARISCAT score performed best with an ' 'AUROC of 0.700 (95% CI: 0.683–0.717) [10]. Similarly, a systematic review by Dankert et al. ' '(2022) found that pulmonary function tests including spirometry provided inconclusive evidence ' 'for PPC prediction in non-thoracic surgery, with only a possible benefit identified in upper ' 'abdominal surgery subgroup analyses [12]. These findings highlight a critical gap: an objective, ' 'broadly applicable, and bedside-feasible tool for preoperative PPC risk stratification is ' 'currently lacking.', sa=6 ) para( 'A patient\'s functional capacity — their ability to sustain aerobic metabolism during physical ' 'activity — is a fundamental determinant of perioperative risk. The physiologic basis is ' 'straightforward: surgery imposes an acute increase in whole-body oxygen demand through the ' 'stress response, inflammatory cascade, and the metabolic demands of tissue repair. Patients ' 'with limited preoperative cardiorespiratory reserve are unable to meet this demand, resulting ' 'in relative oxygen debt, organ dysfunction, and adverse outcomes. Rose et al. (2022) ' 'characterized this relationship in detail, demonstrating that impaired cardiorespiratory fitness ' '(CRF) is an independent predictor of postoperative morbidity and mortality, and that CRF is the ' 'single greatest modifiable perioperative risk factor [3]. While cardiopulmonary exercise testing ' '(CPET) provides the most objective metric of CRF via peak oxygen uptake (VO2 peak) and ' 'ventilatory anaerobic threshold, CPET requires specialized equipment, trained physiologists, ' 'and approximately 30–45 minutes per patient, limiting its routine perioperative use to ' 'well-resourced centers [9].', sa=6 ) para( 'The Six-Minute Walk Test (6MWT) is a standardized, submaximal exercise test in which the ' 'patient walks as far as possible along a flat, 30-meter corridor for six minutes, with the ' 'primary outcome being the six-minute walk distance (6MWD) in meters. The test was formally ' 'standardized by the American Thoracic Society (ATS) in 2002 and has been widely adopted across ' 'cardiopulmonary, oncology, musculoskeletal, and rehabilitation medicine. The 6MWT reflects the ' 'integrated performance of the pulmonary, cardiovascular, neuromuscular, and metabolic systems, ' 'and is strongly correlated with VO2 peak on formal CPET. Normative reference values for the ' '6MWT in adults have been well characterized: a systematic review and meta-analysis by Otadi ' 'and Malmir (2026) pooled data from 28 studies and reported mean 6MWDs of 473 m in older men ' 'and 428 m in older women, with distance declining by approximately 10.25 m per year of age [13]. ' 'For the Asian adult population — most relevant to a Filipino cohort — Yeung et al. (2022) ' 'reported an overall mean 6MWD of 578 m (±75 m), with age-stratified values ranging from 601 m ' 'in adults aged 21–39 to 519 m in those aged 60–80 [14]. These normative data provide a ' 'framework for identifying clinically relevant thresholds in the preoperative setting.', sa=6 ) para( 'Several prospective and retrospective studies have evaluated the 6MWT as a preoperative risk ' 'tool in surgical populations, with a growing body of evidence specifically addressing abdominal ' 'surgery. Soares and Nucci (2021) conducted a cross-sectional cohort study of 50 patients ' 'undergoing elective abdominal surgery and found that half developed early PPCs within the first ' 'seven postoperative days. The preoperative 6MWD was significantly shorter in patients who ' 'developed PPCs (444.8 m vs. 498.3 m; p = 0.013), and multivariable logistic regression confirmed ' '6MWD as an independent predictor of PPCs (OR = 0.978; p = 0.010) for intestinal, gastric, and ' 'biliary tract resections [4]. In a prospective cohort of 100 liver transplant recipients, ' 'Magalhaes et al. (2017) demonstrated that every additional 50 m walked preoperatively was ' 'associated with a 41% reduction in the odds of postoperative respiratory complications ' '(OR = 0.589; 95% CI: 0.357–0.971; p = 0.03), establishing 6MWD as an independent predictor ' 'even in this complex surgical population [5].', sa=6 ) para( 'In oncologic surgery involving thoracoabdominal access, Inoue et al. (2020) found that a ' 'preoperative 6MWD of ≤454 m independently predicted grade II or higher Clavien-Dindo ' 'complications in 111 esophageal cancer patients undergoing thoracic surgery (sensitivity 71.0%, ' 'specificity 54.8%) [6]. Similarly, Hattori et al. (2018) demonstrated in 321 patients ' 'undergoing lung resection for malignancy that a 6MWD of ≤450 m was significantly associated ' 'with postoperative pneumonia (p = 0.002), with 69.2% sensitivity and 71.1% specificity on ROC ' 'analysis [7]. These cut-off values, derived in thoracic surgical cohorts, provide a reasonable ' 'starting reference for comparable investigation in purely abdominal surgery populations, where ' 'the evidence remains sparse.', sa=6 ) para( 'At the level of systematic evidence, Makker et al. (2022) performed a meta-analysis of five ' 'studies encompassing 379 patients with gastrointestinal and abdominal cancer, finding that a ' 'preoperative 6MWT performance of ≥400 m was significantly associated with lower-grade ' 'postoperative complications (OR = 0.38; 95% CI: 0.15–0.95). The association with hospital ' 'length of stay, however, was not statistically significant (MD = 3.29; 95% CI: −1.07 to 7.66) ' '[8]. Argillander et al. (2022) reviewed objective preoperative physical tests in 23 studies of ' 'patients aged ≥65 undergoing major abdominal cancer surgery, concluding that the 6MWT and ' 'incremental shuttle walk test are feasible alternatives to CPET for aerobic capacity estimation, ' 'but that prospective studies with standardized protocols and consistent outcome definitions are ' 'still needed [9]. These reviews consistently identify a critical gap: the prospective prognostic ' 'value of a standardized preoperative 6MWT specifically in a non-oncologic, general major ' 'abdominal surgery population has not been rigorously established.', sa=6 ) para( 'In the Philippine clinical context, the routine preoperative assessment of functional capacity ' 'relies almost exclusively on clinical history and the subjective estimation of metabolic ' 'equivalents (METs). Formal exercise testing such as CPET is not routinely available outside ' 'academic tertiary centers. Published studies evaluating objective functional capacity measures ' 'as preoperative predictors of surgical complications in Filipino patients are essentially absent. ' 'Given the high incidence of major abdominal surgical disease, limited intensive care resources, ' 'and the need for practical and low-cost perioperative risk stratification tools in this setting, ' 'evaluating the 6MWT as a preoperative predictor fills a significant evidence gap. The present ' 'prospective cohort study is designed to address this gap by prospectively measuring preoperative ' '6MWD in adults undergoing major abdominal surgery and systematically ascertaining the occurrence ' 'of PPCs and major postoperative complications during the first 30 postoperative days.', sa=12 ) # ════════════════════════════════════════════════════════════════════════════ # SECTION 4 – OBJECTIVES # ════════════════════════════════════════════════════════════════════════════ sec_h('4', 'Objectives') sub_h('4.1.', 'General Objective') para( 'To determine the prognostic value of the preoperative Six-Minute Walk Distance (6MWD) in ' 'predicting postoperative pulmonary complications and major postoperative complications among ' 'adults undergoing major abdominal surgery at a tertiary hospital.', sa=10 ) sub_h('4.2.', 'Specific Objectives') spec = [ ('1. ', 'To describe the baseline clinical and functional characteristics (including preoperative ' '6MWD, comorbidities, BMI, spirometry results, and ASA classification) of adult patients ' 'scheduled for major abdominal surgery.'), ('2. ', 'To determine the association between preoperative 6MWD and the occurrence of ' 'postoperative pulmonary complications (PPCs) within 30 days of surgery.'), ('3. ', 'To determine the association between preoperative 6MWD and the occurrence of major ' 'postoperative complications (Clavien-Dindo grade II or higher) within 30 days of surgery.'), ('4. ', 'To evaluate the relationship between preoperative 6MWD and secondary outcomes including: ' 'length of hospital stay, unplanned intensive care unit (ICU) admission, need for invasive or ' 'non-invasive mechanical ventilation, and in-hospital mortality.'), ('5. ', 'To identify an optimal preoperative 6MWD cut-off value, using ROC curve analysis, for ' 'predicting PPCs and major postoperative complications.'), ('6. ', 'To assess the discriminative accuracy of the preoperative 6MWT compared to established ' 'risk tools (ASA classification and ARISCAT score) in predicting PPCs.'), ] for num, text in spec: bullet(num, text, li=0.3) doc.add_paragraph() # ════════════════════════════════════════════════════════════════════════════ # SECTION 5 – METHODS # ════════════════════════════════════════════════════════════════════════════ sec_h('5', 'Methods') # 5.1 sub_h('5.1.', 'Type of Study, Time Period and Target Population') para( 'This is a prospective analytic observational cohort study involving adult patients scheduled ' 'for elective or semi-elective major abdominal surgery at a tertiary hospital. Participants ' 'will undergo a standardized preoperative 6MWT and will be prospectively followed from the date ' 'of surgery until hospital discharge or 30 days postoperatively, whichever is shorter, for ' 'ascertainment of outcomes.', sa=6 ) para('Time Period', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) for t in [ u'\u2022 Enrollment Period: Consecutive eligible patients will be enrolled over an estimated ' '12-month recruitment period.', u'\u2022 Patient Follow-up: Each participant will be followed from the date of surgery through ' 'the 30th postoperative day (or until discharge if discharge occurs after day 30) for all ' 'outcome ascertainment.', ]: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.35) r = p.add_run(t); set_font(r) doc.add_paragraph() # 5.2 sub_h('5.2.', 'Criteria for Subject Selection') para('5.2.1. Inclusion Criteria', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) inc = [ ('1. ', 'Age: ≥18 years old at the time of surgery.'), ('2. ', 'Surgery Type: Scheduled for elective or semi-elective major abdominal surgery ' '(intraperitoneal procedure with anticipated operative duration ≥60 minutes under general or ' 'regional anesthesia), including but not limited to colorectal resection, gastrectomy, ' 'hepatobiliary surgery, pancreatectomy, and small-bowel resection.'), ('3. ', 'Functional Assessment: Able to perform the preoperative 6MWT (must be ambulatory ' 'without a mobility aid that precludes standardized testing).'), ('4. ', 'Clinical Course: Inpatient stay resulting in either documented hospital discharge or ' 'documented in-hospital mortality.'), ('5. ', 'Consent: Provision of written informed consent prior to enrollment.'), ] for n, t in inc: bullet(n, t) doc.add_paragraph() para('5.2.2. Exclusion Criteria', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) exc = [ ('1. ', 'Emergency Surgery: Patients undergoing emergency (non-elective) abdominal surgery in ' 'whom preoperative 6MWT cannot be safely performed.'), ('2. ', 'Inability to Walk: Patients who are non-ambulatory preoperatively or have neurological, ' 'orthopedic, or vascular conditions that independently preclude safe completion of a 6MWT ' '(e.g., severe lower-limb ischemia, active musculoskeletal injury, hemiplegia).'), ('3. ', 'Hemodynamic Instability: Patients with resting hemodynamic instability or oxygen ' 'saturation <88% on room air at rest, in whom exercise testing is contraindicated.'), ('4. ', 'Severe Cardiorespiratory Disease: Patients with known unstable angina, acute ' 'decompensated heart failure, or acute exacerbation of COPD within four weeks prior to surgery.'), ('5. ', 'Prior Major Abdominal Surgery in the Same Admission: Patients undergoing re-operation ' 'during the same index admission (to avoid confounding of outcomes).'), ('6. ', 'Data Incompleteness: Patients for whom key baseline or outcome data cannot be obtained.'), ] for n, t in exc: bullet(n, t) doc.add_paragraph() # 5.3 Operational Definitions Table sub_h('5.3.', 'Operational Definitions, if applicable') tbl2 = doc.add_table(rows=1, cols=2) tbl2.style = 'Table Grid' tbl2.columns[0].width = Inches(2.0) tbl2.columns[1].width = Inches(4.0) hdr2 = tbl2.rows[0].cells hdr2[0].text = 'Variable'; hdr2[1].text = 'Definition' for c in hdr2: for r in c.paragraphs[0].runs: r.bold = True; r.font.size = Pt(11); r.font.name = 'Times New Roman' op_defs = [ ('Major Abdominal Surgery', 'Any intraperitoneal operative procedure (open or laparoscopic) anticipated to last ≥60 minutes ' 'under general or regional anesthesia, including colorectal resection, gastrectomy, hepatobiliary ' 'surgery, pancreatectomy, and small-bowel resection.'), ('Six-Minute Walk Test (6MWT)', 'A standardized submaximal exercise test in which the patient walks as far as possible on a flat, ' '30-meter corridor for six minutes. Administered per ATS 2002 guidelines. The primary metric is ' 'the six-minute walk distance (6MWD) in meters.'), ('Six-Minute Walk Distance (6MWD)', 'Total distance walked (in meters) during the 6MWT. A 6MWD below the study-defined cut-off ' '(determined by ROC analysis) will classify the patient as having "reduced functional capacity."'), ('Postoperative Pulmonary Complication (PPC)', 'Any of the following occurring within 30 days of surgery: (a) pneumonia — new pulmonary ' 'infiltrate with fever, leukocytosis, and purulent secretions; (b) respiratory failure — SpO2 ' '<90% on room air or requirement for mechanical ventilation beyond 24 hours postoperatively; ' '(c) atelectasis — radiologically confirmed requiring physiotherapy or bronchoscopy; ' '(d) pleural effusion — requiring drainage; (e) bronchospasm — requiring bronchodilator ' 'treatment. Defined per StEP-COMPAC consensus.'), ('Major Postoperative Complication', 'Any postoperative complication graded Clavien-Dindo grade II or higher occurring within ' '30 days of surgery.'), ('Clavien-Dindo Grade II or Higher', 'Grade II: Complication requiring pharmacological treatment (e.g., antibiotics, ' 'anti-arrhythmics). Grade III: Requiring surgical, endoscopic, or radiological intervention. ' 'Grade IV: Life-threatening complication requiring ICU management. Grade V: Death.'), ('Unplanned ICU Admission', 'Transfer to the ICU at any point following the initial return from the operating theater, ' 'not as part of the planned postoperative pathway.'), ('Mechanical Ventilation', 'Initiation of invasive mechanical ventilation via endotracheal tube or tracheostomy beyond ' 'the immediate post-anesthetic recovery period (>24 hours postoperatively).'), ('Non-Invasive Ventilation', 'Initiation of non-invasive positive pressure ventilation (CPAP, BiPAP) or high-flow nasal ' 'cannula (HFNC) beyond the immediate post-anesthetic recovery period.'), ('Prolonged Hospitalization', 'Total hospital length of stay exceeding the 75th percentile for the specific procedure type, ' 'or a stay of ≥14 days (whichever is defined a priori).'), ('In-Hospital Mortality', 'Death from any cause occurring during the index hospital admission.'), ('Reduced Functional Capacity', 'Preoperative 6MWD below the study-defined ROC-derived cut-off value, or a 6MWD of <400 m ' 'based on existing literature thresholds.'), ] for var, defn in op_defs: row = tbl2.add_row() row.cells[0].text = var; row.cells[1].text = defn for ci in [0, 1]: for r in row.cells[ci].paragraphs[0].runs: r.font.size = Pt(11); r.font.name = 'Times New Roman' para('Table 1: Operational Definitions', italic=True, size=11, align=WD_ALIGN_PARAGRAPH.CENTER, sb=4, sa=8) # 5.4 sub_h('5.4.', 'Description of Study Procedure') para('5.4.1. For observational (prospective cohort) studies:', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=4) para('5.4.1.1. Method of Subject Selection', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'Subjects will be identified prospectively from the surgical schedule of the institution. ' 'All adult patients listed for elective or semi-elective major abdominal surgery will be ' 'screened by the study team during the preoperative assessment visit, typically occurring ' '2–7 days prior to the scheduled operation. Eligible patients meeting inclusion criteria and ' 'providing written informed consent will be enrolled consecutively until the target sample ' 'size is achieved.', sa=6 ) para('5.4.1.2. Data to Be Gathered', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para('The following data points will be systematically collected using a standardized case ' 'report form:', sa=4) data_items = [ ('Demographics: ', 'Age, sex, height, weight, body mass index (BMI).'), ('Clinical Characteristics: ', 'Comorbidities (e.g., COPD, diabetes mellitus, hypertension, ' 'ischemic heart disease, heart failure, chronic kidney disease, cerebrovascular disease), ' 'smoking status, ASA Physical Status classification, ARISCAT score.'), ('Exposure Variable: ', '6MWD (meters), resting and post-test heart rate, oxygen saturation ' '(SpO2), Borg dyspnea scale, and reason for test termination (if applicable).'), ('Surgical Data: ', 'Type of procedure, operative approach (open vs. laparoscopic/robotic), ' 'estimated blood loss, operative duration, type of anesthesia.'), ('Postoperative Outcome Data (primary): ', 'Occurrence of any PPC within 30 days — pneumonia, ' 'respiratory failure, atelectasis, pleural effusion, bronchospasm — (Yes/No with date).'), ('Postoperative Outcome Data (secondary): ', 'Clavien-Dindo grade of all complications, ' 'unplanned ICU admission, need for mechanical or non-invasive ventilation, length of hospital ' 'stay (days), in-hospital mortality.'), ] for lbl, txt in data_items: dot(lbl, txt) doc.add_paragraph() para('5.4.1.3. Description of Procedures to Be Done to Subjects', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'Each enrolled participant will undergo one standardized preoperative 6MWT performed by a ' 'trained research physiotherapist or nurse, within 2–7 days prior to surgery, following ATS ' '(2002) guidelines. The test will be conducted on a flat, indoor, 30-meter corridor, clearly ' 'marked at each end. Standardized verbal encouragement will be provided at one-minute intervals. ' 'Participants will be instructed to walk as fast as safely possible for six minutes, and are ' 'permitted to slow down or stop if needed. Resting SpO2, heart rate, and Borg dyspnea scale ' 'will be recorded immediately before and after the test. The test will be terminated early if ' 'any safety criterion is met (SpO2 <85%, chest pain, acute dyspnea, leg cramps, or patient ' 'request). No other study-specific procedures will be performed; all postoperative data will ' 'be obtained through prospective chart review and clinical follow-up.', sa=6 ) para('5.4.1.4. Instruments Used for Measuring Exposure and/or Outcome', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) instr = [ ('Exposure (6MWT): ', 'A measured 30-meter corridor, pulse oximeter, stopwatch, and Borg ' 'dyspnea scale. Distance will be recorded in meters to the nearest meter.'), ('Outcome Assessment (PPCs): ', 'Clinical, radiologic, and laboratory findings documented in ' 'the official patient chart by the attending surgical and medical team, adjudicated against the ' 'StEP-COMPAC consensus PPC definition.'), ('Outcome Assessment (Clavien-Dindo Grade): ', 'Classified by the principal investigator based ' 'on chart review of all postoperative events, using the standard Clavien-Dindo classification.'), ('Data Abstraction: ', 'A standardized Case Report Form (CRF) will serve as the primary ' 'instrument for uniform data collection.'), ('Risk Scores: ', 'ASA classification assigned by the attending anesthesiologist; ARISCAT score ' 'computed from seven preoperative variables at time of enrollment.'), ] for lbl, txt in instr: dot(lbl, txt) doc.add_paragraph() para('5.4.1.5. Method of Validating Measuring Instruments', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'The 6MWT will be administered according to the standardized ATS 2002 protocol, ensuring ' 'reproducibility and comparability with published normative and prognostic data. Research ' 'personnel performing the test will undergo a standardized training session prior to study ' 'commencement to ensure protocol fidelity. Pulse oximeters will be calibrated and validated ' 'per hospital biomedical engineering standards. Postoperative outcome adjudication will be ' 'performed by two independent investigators blinded to the 6MWD results, with discrepancies ' 'resolved by consensus.', sa=6 ) para('5.4.1.6. Laboratory Procedures to Be Performed, if any', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'No study-specific laboratory procedures will be performed beyond routine preoperative workup. ' 'Preoperative spirometry results (FEV1, FVC, FEV1/FVC) will be recorded if available as part ' 'of standard preoperative care. Routine admission laboratory values (complete blood count, serum ' 'albumin, serum creatinine) will be extracted from the medical record.', sa=6 ) para('5.4.1.7. Follow-Up Procedures', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'All enrolled patients will be followed prospectively from the date of surgery. Research ' 'personnel will perform daily postoperative chart reviews while the patient is hospitalized, ' 'and a structured clinical review at postoperative day 30 (or at hospital discharge, whichever ' 'is later) to ascertain all outcome events. Patients discharged before day 30 will be contacted ' 'by telephone and/or reviewed at their scheduled outpatient follow-up appointment for 30-day ' 'outcome data.', sa=8 ) # 5.5 sub_h('5.5.', 'Description of Outcome Measures') para( 'The primary outcome measure is the occurrence of any postoperative pulmonary complication ' '(PPC) within 30 days of surgery, defined per the StEP-COMPAC consensus framework. The ' 'rationale for selecting PPCs as the primary outcome is their high clinical relevance, direct ' 'link to impaired preoperative cardiorespiratory reserve, and consistent use as the primary ' 'outcome across the existing 6MWT perioperative literature [4,5,7,8].', sa=6 ) para( 'A co-primary outcome is the occurrence of any major postoperative complication (Clavien-Dindo ' 'grade II or higher) within 30 days of surgery. This broader composite outcome captures major ' 'systemic complications beyond the pulmonary domain and is consistent with grading systems used ' 'in comparable surgical outcome studies [6].', sa=6 ) para( 'Secondary outcome measures include: length of hospital stay (continuous, in days), unplanned ' 'ICU admission (dichotomous — Yes/No), need for invasive mechanical ventilation beyond 24 hours ' 'postoperatively (dichotomous), need for non-invasive ventilation or high-flow nasal cannula ' 'beyond the immediate recovery period (dichotomous), and in-hospital mortality (dichotomous). ' 'These secondary outcomes were selected based on their clinical relevance, their established ' 'association with reduced preoperative functional capacity, and their consistent use in ' 'comparable cohort studies and systematic reviews [3,4,5,8].', sa=8 ) # 5.6 sub_h('5.6.', 'Sample Size Estimation') para( 'Sample size was estimated based on the hypothesis that a lower preoperative 6MWD is ' 'independently associated with a higher rate of PPCs. Using data from Soares and Nucci (2021) ' 'as the primary reference — which reported a PPC incidence of 30% in patients with 6MWD ≥400 m ' 'and 65% in those with 6MWD <400 m — with a two-sided alpha of 0.05, power of 80%, and an ' 'anticipated 1:1 ratio of exposed (low 6MWD) to unexposed (normal 6MWD) participants, the ' 'initial sample size is calculated at approximately 38 patients per group (76 total). To account ' 'for multivariable adjustment of up to 6 covariates (at 10 events per variable) and an estimated ' '15% loss to follow-up or incomplete data, the final target sample size is 120 participants. ' 'Sample size was computed using standard logistic regression sample size formulae.', sa=8 ) # 5.7 sub_h('5.7.', 'Data Analysis') para( 'Statistical analyses will be performed using SPSS version 29.0 or R (version 4.3 or higher). ' 'Descriptive statistics will summarize baseline clinical and functional characteristics. ' 'Categorical variables will be reported as frequencies and percentages; continuous variables ' 'will be reported as mean ± standard deviation or median (interquartile range) depending on ' 'distribution. Univariable comparisons between patients who develop PPCs and those who do not ' 'will use the Chi-squared test or Fisher\'s exact test for categorical variables and the ' 'independent-samples t-test or Mann-Whitney U test for continuous variables, as appropriate.', sa=6 ) para( 'The primary hypothesis will be tested using multivariable binary logistic regression, with PPC ' 'occurrence as the dependent variable and preoperative 6MWD as the primary independent variable, ' 'adjusting for clinically relevant covariates identified a priori (age, sex, BMI, ASA class, ' 'operative duration, and procedure type). Results will be expressed as odds ratios (OR) with ' '95% confidence intervals (CI).', sa=6 ) para( 'Receiver Operating Characteristic (ROC) curve analysis will be used to determine the optimal ' '6MWD cut-off value for predicting PPCs and major postoperative complications, with the Youden ' 'index used to identify the threshold that maximizes sensitivity and specificity. The area under ' 'the ROC curve (AUROC) will be calculated for the 6MWT, ASA classification, and ARISCAT score, ' 'with pairwise AUROC comparisons performed to assess the discriminative performance of the 6MWT ' 'relative to established risk tools. The level of significance is set at α = 0.05 (two-sided).', sa=8 ) # 5.8 sub_h('5.8.', 'Ethical Consideration') para( 'This prospective study may enroll participants spanning a range of age groups, including elderly ' 'patients, and may include individuals with significant comorbidities. Given that the 6MWT is a ' 'validated, widely used clinical assessment with an established safety profile, and that no ' 'additional invasive procedures will be performed beyond routine preoperative care, the risk to ' 'participants is considered minimal. Strict confidentiality of all participant data will be ' 'maintained. All study records will be coded and de-identified, and investigators are responsible ' 'for the accuracy, completeness, and integrity of all collected data.', sa=6 ) para('5.8.1. Method/s of Dealing with Adverse Events', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'While the 6MWT is associated with very low risk in supervised settings, the test will be ' 'immediately terminated if the participant develops chest pain, severe dyspnea, dizziness, ' 'leg cramps, pallor, or SpO2 <85%. A qualified clinician will be available during all test ' 'sessions and emergency protocols will be in place. Any adverse event occurring during the ' '6MWT will be documented, reported to the Principal Investigator, and managed per institutional ' 'protocols. Serious adverse events will be reported to the IERC within the required timeframe.', sa=6 ) para('5.8.2. Anticipated Risks and Discomforts to Subjects', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'The anticipated physical risk to participants is minimal, limited primarily to the physiologic ' 'exertion of walking at a self-selected pace for six minutes, which is analogous to activities ' 'of daily living. Potential discomforts include transient breathlessness and fatigue, which are ' 'expected and self-limiting. Pre-test safety screening will exclude participants for whom ' 'exercise testing is contraindicated.', sa=6 ) para('5.8.3. Expected Benefits to the Subject and to Others', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para( 'The results of this study are expected to establish whether the preoperative 6MWT independently ' 'predicts PPCs and major complications following major abdominal surgery. If validated, the 6MWT ' 'could provide clinicians with a simple, immediately implementable preoperative risk ' 'stratification tool that enables targeted preventive interventions (prehabilitation, ' 'physiotherapy, anesthesia optimization) in high-risk patients. The study will generate locally ' 'relevant evidence applicable to Filipino patients and similar resource-limited surgical settings.', sa=6 ) para('5.8.4. Protection of Confidentiality', bold=True, align=WD_ALIGN_PARAGRAPH.LEFT, sa=3) para('The following procedures will be strictly adhered to:', sa=4) conf_items = [ 'A. The study shall abide by the Principles of the Declaration of Helsinki (2013) and will be ' 'conducted in accordance with the Guidelines of the International Conference on Harmonization – ' 'Good Clinical Practice (ICH-GCP).', 'B. The Clinical Protocol and all relevant documents shall be reviewed and approved by the SLMC ' 'Institutional Ethics Review Committee (IERC) prior to enrollment of any participant.', 'C. Patient confidentiality shall be maintained by assigning each participant a unique study code. ' 'No identifying information (name, birth date, hospital number) will be included in any study ' 'database or report.', 'D. Data Storage and Security: All study data will be stored in a password-protected, encrypted ' 'file accessible only to the Principal Investigator and Co-Investigators. All study documents ' 'will be retained by the Principal Investigator for a minimum of 5 years after study completion, ' 'after which they will be securely destroyed.', 'E. Inspection of Records: Access to study records is restricted to the Principal Investigator, ' 'Co-Investigators, and duly authorized representatives of the IERC or institutional audit bodies.', 'F. Results will be disseminated only in aggregate, de-identified form through peer-reviewed ' 'publication or scientific conference presentation.', ] for item in conf_items: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.JUSTIFY p.paragraph_format.space_after = Pt(4) p.paragraph_format.left_indent = Inches(0.35) r = p.add_run(item); set_font(r) doc.add_paragraph() # ════════════════════════════════════════════════════════════════════════════ # SECTION 7 – REFERENCES (continuous [1]–[14]) # ════════════════════════════════════════════════════════════════════════════ sec_h('7', 'References') all_refs = [ ('[1]', 'Smetana GW, Lawrence VA, Cornell JE; American College of Physicians. Preoperative ' 'pulmonary risk stratification for noncardiothoracic surgery: systematic review for ' 'the American College of Physicians. Ann Intern Med. 2006 Apr 18;144(8):581-95. ' 'doi: 10.7326/0003-4819-144-8-200604180-00009.'), ('[2]', 'Garg S, Govindaraj V, Dwivedi DP, Raja K, Theerthar EP. Postoperative pulmonary ' 'complications in patients undergoing upper abdominal surgery: risk factors and ' 'predictive models. Monaldi Arch Chest Dis. 2025 Mar 31. ' 'doi: 10.4081/monaldi.2024.2915. PMID: 38526466.'), ('[3]', 'Rose GA, Davies RG, Appadurai IR, Williams IM, Bashir M, Berg RMG. \'Fit for ' 'surgery\': the relationship between cardiorespiratory fitness and postoperative ' 'outcomes. Exp Physiol. 2022 Aug;107(8):780-95. doi: 10.1113/EP090156. PMID: 35579479.'), ('[4]', 'Soares SMTP, Nucci LB. Association between early pulmonary complications after ' 'abdominal surgery and preoperative physical capacity. Physiother Theory Pract. 2021 ' 'Jul;37(7):852-9. doi: 10.1080/09593985.2019.1650404. PMID: 31402737.'), ('[5]', 'Magalhaes CBA, Nogueira IC, Marinho LS, Daher EF, Garcia JHP, Viana CFG. Exercise ' 'capacity impairment can predict postoperative pulmonary complications after liver ' 'transplantation. Respiration. 2017;94(6):538-44. doi: 10.1159/000479008. ' 'PMID: 28738386.'), ('[6]', 'Inoue T, Ito S, Kanda M, Niwa Y, Nagaya M, Nishida Y. Preoperative six-minute walk ' 'distance as a predictor of postoperative complication in patients with esophageal ' 'cancer. Dis Esophagus. 2020 Mar 5;33(3):doz050. doi: 10.1093/dote/doz050. ' 'PMID: 31111872.'), ('[7]', 'Hattori K, Matsuda T, Takagi Y, Nagaya M, Inoue T, Nishida Y. Preoperative ' 'six-minute walk distance is associated with pneumonia after lung resection. ' 'Interact Cardiovasc Thorac Surg. 2018 Feb 1;26(2):208-13. ' 'doi: 10.1093/icvts/ivx310. PMID: 29049742.'), ('[8]', 'Makker PGS, Koh CE, Solomon MJ, Steffens D. Preoperative functional capacity and ' 'postoperative outcomes following abdominal and pelvic cancer surgery: a systematic ' 'review and meta-analysis. ANZ J Surg. 2022 Jul;92(7-8):1732-40. ' 'doi: 10.1111/ans.17577. PMID: 35253333.'), ('[9]', 'Argillander TE, Heil TC, Melis RJF, van Duijvendijk P, Klaase JM, van Munster BC. ' 'Preoperative physical performance as predictor of postoperative outcomes in patients ' 'aged 65 and older scheduled for major abdominal cancer surgery: a systematic review. ' 'Eur J Surg Oncol. 2022 Mar;48(3):575-84. doi: 10.1016/j.ejso.2021.09.019. ' 'PMID: 34629224.'), ('[10]', 'STARSurg Collaborative and TASMAN Collaborative. Evaluation of prognostic risk models ' 'for postoperative pulmonary complications in adult patients undergoing major abdominal ' 'surgery: a systematic review and international external validation cohort study. ' 'Lancet Digit Health. 2022 Jul;4(7):e498-e507. ' 'doi: 10.1016/S2589-7500(22)00069-3. PMID: 35750401.'), ('[11]', 'Boden I, Reeve J, Jernas A, Denehy L, Fagevik Olsen M. Preoperative physiotherapy ' 'prevents postoperative pulmonary complications after major abdominal surgery: a ' 'meta-analysis of individual patient data. J Physiother. 2024 Jul;70(3):195-202. ' 'doi: 10.1016/j.jphys.2024.02.012. PMID: 38472053.'), ('[12]', 'Dankert A, Dohrmann T, Loser B, Zapf A, Zollner C, Petzoldt M. Pulmonary function ' 'tests for the prediction of postoperative pulmonary complications. Dtsch Arztebl Int. ' '2022 Feb 18;119(7):99-106. doi: 10.3238/arztebl.m2022.0074. PMID: 34939921.'), ('[13]', 'Otadi K, Malmir K. Normative reference values for the six-minute walk test in older ' 'adults: a systematic review and meta-analysis. Arch Gerontol Geriatr. 2026 ' 'Jan;128:106026. doi: 10.1016/j.archger.2025.106026. PMID: 41027267.'), ('[14]', 'Yeung MT, Chan MY, Huang KS, Chen TJ, Chia CP, Fong MM. Normative reference values ' 'and regression equations to predict the 6-minute walk distance in the Asian adult ' 'population aged 21-80 years. Hong Kong Physiother J. 2022 Dec;42(2):69-78. ' 'doi: 10.1142/S1013702522500111. PMID: 37560171.'), ] for num, txt in all_refs: ref_entry(num, txt) # Footer doc.add_paragraph() fp = doc.add_paragraph() fp.alignment = WD_ALIGN_PARAGRAPH.RIGHT fp.paragraph_format.space_before = Pt(24) r = fp.add_run('Protocol Version 01 dated ________________') set_font(r, size=10) out = '/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Complete.docx' doc.save(out) print(f'Saved: {out}') PYEOF python3 /tmp/workspace/6mwt-proposal/build_complete.py

python3 -c " from docx import Document doc = Document('/tmp/workspace/6mwt-proposal/6MWT_Research_Proposal_Complete.docx') # Quick structural check sections_found = [] for p in doc.paragraphs: t = p.text.strip() if t and any(t.startswith(x) for x in ['2.','3.','3.1','3.2','3.3','4.','4.1','4.2','5.','5.1','5.2','5.3','5.4','5.5','5.6','5.7','5.8','7.']): sections_found.append(t[:80]) for s in sections_found: print(s) print() print(f'Total paragraphs: {len(doc.paragraphs)}') print(f'Total tables: {len(doc.tables)}') "