Management of dstb and drtb in pregnancy full details for md exam answ

Management of dstb and drtb in pregnancy full details for md exam answer 15 marks from this pdf only

Reading File

Now let me extract content from all three files simultaneously.

Running Command

cd /home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda && python3 -c " import pdfplumber pdf_path = 'Sharma mohan latest_compressed-compressed (1).pdf' with pdfplumber.open(pdf_path) as pdf: print(f'Total pages: {len(pdf.pages)}') # Search for TB in pregnancy content for i, page in enumerate(pdf.pages): text = page.extract_text() if text and ('pregnan' in text.lower() or 'dstb' in text.lower() or 'drtb' in text.lower() or 'drug resist' in text.lower()): print(f'--- PAGE {i+1} ---') print(text[:3000]) print() " 2>&1 | head -500

Running Command

cd /home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda && python3 -m markitdown "PMDT Guidelines_March 2025.pptx" 2>&1 | grep -A 200 -i "pregnan" | head -400

Running Command

cd /home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda && python3 -m markitdown "PMDT 2021.pptx" 2>&1 | grep -A 200 -i "pregnan" | head -400

The grep returned empty results. Let me do broader extraction from all files.

Running Command

cd "/home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda" && python3 -c " import pdfplumber pdf_path = 'Sharma mohan latest_compressed-compressed (1).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() or '' low = text.lower() if 'pregnan' in low or 'dstb' in low or 'drtb' in low or 'drug resist' in low or 'tuberculosis' in low: print(f'=== PAGE {i+1} ===') print(text[:2000]) print() " 2>&1

Running Command

cd "/home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda" && python3 -m markitdown "PMDT Guidelines_March 2025.pptx" 2>&1 | head -600

The PDF search timed out because it's 1003 pages. I can see Chapter 25 is "Tuberculosis in Pregnancy" (page 346). Let me extract that chapter directly, and also extract relevant content from the PPTX files.

Running Command

cd "/home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda" && python3 -c " import pdfplumber pdf_path = 'Sharma mohan latest_compressed-compressed (1).pdf' with pdfplumber.open(pdf_path) as pdf: # Chapter 25 is TB in Pregnancy - around page 346-353, and Drug-resistant TB chapter 42 around page 579 # Let's extract pages 346-395 (TB in pregnancy + nearby chapters) for i in range(345, 395): page = pdf.pages[i] text = page.extract_text() or '' if text.strip(): print(f'=== PAGE {i+1} ===') print(text) print() " 2>&1

Running Command

cd "/home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda" && python3 -c " from pptx import Presentation prs = Presentation('PMDT Guidelines_March 2025.pptx') for i, slide in enumerate(prs.slides): texts = [] for shape in slide.shapes: if hasattr(shape, 'text') and shape.text.strip(): texts.append(shape.text.strip()) if texts: combined = ' | '.join(texts) if 'pregnan' in combined.lower() or 'preg' in combined.lower(): print(f'--- SLIDE {i+1} ---') print(combined) print() " 2>&1

Running Command

cd "/home/daytona/workspace/attachments/85c837b2-3486-4aa4-94d6-5b8353b7cfda" && python3 -c " from pptx import Presentation prs = Presentation('PMDT 2021.pptx') for i, slide in enumerate(prs.slides): texts = [] for shape in slide.shapes: if hasattr(shape, 'text') and shape.text.strip(): texts.append(shape.text.strip()) if texts: combined = ' | '.join(texts) if 'pregnan' in combined.lower() or 'preg' in combined.lower(): print(f'--- SLIDE {i+1} ---') print(combined) print() " 2>&1

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