what are next steps for this mi patient according to standard indian guidelines
python3 -c " import pdfplumber with pdfplumber.open('/home/daytona/workspace/attachments/6bdd3ff2-cccd-4afd-ac4c-ccac0cd34a7a/Yogeshbhai angiography .pdf') as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): text = page.extract_text() print(f'--- PAGE {i+1} ---') print(text) print() "
CSI CARDIOLOGICAL SOCIETY INDIA guidelines STEMI NSTEMI ACS management 2024 2025
python3 -c " from pypdf import PdfReader import sys reader = PdfReader('/home/daytona/workspace/attachments/6bdd3ff2-cccd-4afd-ac4c-ccac0cd34a7a/Yogeshbhai angiography .pdf') print(f'Pages: {len(reader.pages)}') for i, page in enumerate(reader.pages): text = page.extract_text() print(f'--- PAGE {i+1} (chars: {len(text) if text else 0}) ---') if text: print(text[:2000]) # Check for images if '/XObject' in page['/Resources']: xobj = page['/Resources']['/XObject'].get_object() for name, obj in xobj.items(): o = obj.get_object() print(f' Image found: {name}, subtype: {o.get(\"/Subtype\")}') "
python3 -c " import fitz # PyMuPDF doc = fitz.open('/home/daytona/workspace/attachments/6bdd3ff2-cccd-4afd-ac4c-ccac0cd34a7a/Yogeshbhai angiography .pdf') print(f'Pages: {len(doc)}') for page_num in range(len(doc)): page = doc[page_num] # Try text extraction first text = page.get_text() print(f'--- PAGE {page_num+1} TEXT ({len(text)} chars) ---') print(text[:3000] if text else '(empty)') "
python3 -c " import subprocess # Try using pdf2image / tesseract for OCR result = subprocess.run(['pdftoppm', '-r', '200', '-jpeg', '/home/daytona/workspace/attachments/6bdd3ff2-cccd-4afd-ac4c-ccac0cd34a7a/Yogeshbhai angiography .pdf', '/tmp/angio_page'], capture_output=True, text=True) print('STDOUT:', result.stdout) print('STDERR:', result.stderr) print('RC:', result.returncode) import os files = os.listdir('/tmp/') print('Files in /tmp:', [f for f in files if 'angio' in f]) "
python3 -c " import subprocess import os # Run OCR on each page for i in range(1, 4): img_path = f'/tmp/angio_page-{i}.jpg' out_path = f'/tmp/angio_text_{i}' result = subprocess.run(['tesseract', img_path, out_path, '-l', 'eng'], capture_output=True, text=True) print(f'Page {i} OCR RC:', result.returncode, result.stderr[:200]) # Read the results for i in range(1, 4): txt_path = f'/tmp/angio_text_{i}.txt' if os.path.exists(txt_path): with open(txt_path) as f: content = f.read() print(f'\\n=== PAGE {i} ===') print(content[:3000]) "
https://www.csi.org.in/frontend/assets/assets/guidelines/ste…
PCI chronic total occlusion RCA STEMI inferior wall secondary prevention India
| Vessel | Finding |
|---|---|
| LMCA | Normal |
| LAD Ostium | 80% stenosis |
| Mid LAD | 70% stenosis |
| Distal LAD | 70% stenosis |
| LCX | Normal |
| RCA (Proximal) | 100% occlusion (Total) - receiving Grade II collaterals from LAD |
| Drug Class | Drug | Target/Notes |
|---|---|---|
| Antiplatelet 1 | Aspirin 75-150 mg OD | Lifelong |
| Antiplatelet 2 | Clopidogrel 75 mg OD or Ticagrelor 90 mg BD | Minimum 12 months post-PCI (DAPT) |
| Statin | Atorvastatin 40-80 mg or Rosuvastatin 20-40 mg | LDL <70 mg/dL (or <55 mg/dL if high-risk) |
| Beta-blocker | Metoprolol succinate 25-200 mg OD or Bisoprolol 2.5-10 mg OD | Especially with mild LVD |
| ACEI/ARB | Ramipril 2.5-10 mg OD or Perindopril 4-8 mg | Post-MI + LVD = mandatory |
| Timeframe | Action |
|---|---|
| 1-2 weeks post-PCI | Wound check (radial access site), medication tolerability review |
| 1 month | Lipid profile, renal function, BP review |
| 3 months | ECG, Echo to reassess LV function post-RCA revascularization |
| 6 months | Review DAPT, reassess LAD (FFR/iFR or repeat angio if symptomatic) |
| 12 months | Consider DAPT de-escalation if no events |