python3 << 'EOF' import pdfplumber pdf_path = "/tmp/workspace/attachments/085ce7fa-6366-4bac-94bb-42857263f7cf/IM PRELIMS_260719_204802.pdf" with pdfplumber.open(pdf_path) as pdf: print(f"Total pages: {len(pdf.pages)}") # Print first 3 pages to understand structure for i, page in enumerate(pdf.pages[:5]): print(f"\n--- PAGE {i+1} ---") text = page.extract_text() if text: print(text[:2000]) EOF

python3 << 'EOF' import pdfplumber pdf_path = "/tmp/workspace/attachments/085ce7fa-6366-4bac-94bb-42857263f7cf/IM PRELIMS_260719_204802.pdf" all_text = [] with pdfplumber.open(pdf_path) as pdf: for i, page in enumerate(pdf.pages): text = page.extract_text() if text: all_text.append(f"\n=== PAGE {i+1} ===\n{text}") full_text = "\n".join(all_text) # Save to file with open("/tmp/workspace/prelims_full_text.txt", "w", encoding="utf-8") as f: f.write(full_text) print(f"Total characters extracted: {len(full_text)}") print("Saved to /tmp/workspace/prelims_full_text.txt") EOF

python3 << 'EOF' # Let's look at what topics/tags appear in the text to identify chapter markers with open("/tmp/workspace/prelims_full_text.txt", "r") as f: text = f.read() # Search for chapter/topic markers import re # Look for lines with topic hints lines = text.split('\n') for i, line in enumerate(lines): lower = line.lower() if any(kw in lower for kw in ['parasit', 'respiratory', 'pulmo', 'bronchiect', 'lung abscess', 'cystic', 'meningococ', 'gonococ', 'hacek', 'fungal', 'gram neg', 'gram-neg', 'sidapa', 'olokaria', 'set b', 'set c', 'set d']): print(f"Line {i}: {line.strip()}") EOF

python3 << 'EOF' # Let's look at the SET B and SET C structure and find the tags/topics per question with open("/tmp/workspace/prelims_full_text.txt", "r") as f: text = f.read() lines = text.split('\n') # Find the SET markers for i, line in enumerate(lines): if 'SET' in line and ('A' in line or 'B' in line or 'C' in line or 'D' in line): print(f"Line {i}: {line.strip()}") print("\n\n--- Looking for chapter/topic labels in the text ---") # Look for lines that indicate a topic change for i, line in enumerate(lines): strip = line.strip() # Look for standalone topic headers if strip and len(strip) < 100: lower = strip.lower() if any(kw in lower for kw in ['fungal infections', 'parasitic infections', 'meningococ', 'gonococ', 'bronchiect', 'lung abscess', 'cystic fibros', 'hacek', 'respiratory physio', 'gram negative']): print(f"Line {i}: {repr(strip)}") EOF

python3 << 'EOF' # Look at what's near the "Fungal Infections by Dr. Loren" line and look for topic headers with open("/tmp/workspace/prelims_full_text.txt", "r") as f: text = f.read() lines = text.split('\n') # Print context around line 1933 (Fungal Infections header) print("=== Around line 1933 (Fungal Infections header) ===") for i in range(1920, 1970): print(f"{i}: {lines[i]}") print("\n=== Around SET B (line 967) ===") for i in range(960, 1000): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # The PDF contains SET A, SET B, SET C and possibly SET D each with 100 questions. # I need to find questions tagged to specific topics. Let me look at the full structure. # The questions don't have explicit chapter labels - I need to identify by content clues # (tags like -Sidapa, -Olokaria, or explicit topic mentions) # Let me first understand what all the SETs are and their page ranges with open("/tmp/workspace/prelims_full_text.txt", "r") as f: text = f.read() lines = text.split('\n') # Find all SET markers and EXAM headers for i, line in enumerate(lines): strip = line.strip() if ('SET' in strip and len(strip) < 30) or 'PRELIM EXAM' in strip or 'MIDTERM' in strip or 'FINALS' in strip: print(f"Line {i}: {repr(strip)}") EOF

python3 << 'EOF' # The PRELIM exam has SET A (lines 12-966) and SET B (lines 967-1949) # Let me look at the SET B content more carefully - it has 100 questions # And let me see what topic labels appear with each question # First let me understand the structure better - look at how topic tags appear with open("/tmp/workspace/prelims_full_text.txt", "r") as f: text = f.read() lines = text.split('\n') # Look at pages with topic-specific tags for SET A # The exam covers topics on page 1. Let me look for question blocks with topic tags # Let's find a question around the Parasitic infections area print("=== Checking SET B structure - first 50 lines ===") for i in range(967, 1050): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # Now I understand the structure. Questions don't have explicit chapter labels but # I can identify them by content. Let me write a comprehensive extractor that: # 1. Extracts all questions from both SET A and SET B of the PRELIM exam # 2. Tags each question with the chapter based on content keywords with open("/tmp/workspace/prelims_full_text.txt", "r") as f: text = f.read() lines = text.split('\n') # The PRELIM exam is lines 12 to 1949 (SET A + SET B) # Let me look at lines around question numbers that I know are topic-related # From my earlier analysis, let me check around lines 249-400 for Gram Neg II / HACEK / Gonococcal print("=== Lines 240-410 (Gram Negative area) ===") for i in range(240, 415): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # Now I have a good understanding. Let me write a comprehensive extractor # that identifies questions from the 5 target chapters and outputs them # I'll use keyword-based matching on the question content with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() lines = full_text.split('\n') # The PRELIM exam covers lines 12-1949 (SET A line 12-966, SET B lines 967-1949) prelim_lines = lines[12:1950] # Reconstruct the text and parse questions # Questions in SET A are numbered 1-100 and in SET B also 1-100 # Format is: "NUMBER. QUESTION TEXT ANSWER" import re def extract_all_questions_with_context(lines, set_name): """Extract all questions with their full text blocks""" questions = [] i = 0 while i < len(lines): line = lines[i].strip() # Match question numbers: "1.", "22.", "100.", "_8.", etc. match = re.match(r'^[_\-]?(\d+)[.\)]\s+(.+)', line) if match: qnum = int(match.group(1)) if 1 <= qnum <= 100: # Collect the full question block block = [line] j = i + 1 while j < len(lines): next_line = lines[j].strip() # Stop at the next question number next_q = re.match(r'^[_\-]?(\d+)[.\)]\s+', next_line) if next_q: next_qnum = int(next_q.group(1)) if 1 <= next_qnum <= 100 and abs(next_qnum - qnum) <= 5: break # Stop at page markers if 'PRELIM EXAM' in next_line or '=== PAGE' in next_line: pass # include but continue block.append(lines[j]) j += 1 if j - i > 40: # max block size break questions.append({ 'set': set_name, 'num': qnum, 'block': '\n'.join(block) }) i = j continue i += 1 return questions # Only extract from PRELIM section (lines 12 to 1949 in full text) # SET A: lines 12-966 # SET B: lines 967-1949 set_a_lines = lines[12:967] set_b_lines = lines[967:1950] questions_a = extract_all_questions_with_context(set_a_lines, "SET A") questions_b = extract_all_questions_with_context(set_b_lines, "SET B") print(f"SET A: {len(questions_a)} questions extracted") print(f"SET B: {len(questions_b)} questions extracted") # Print sample for q in questions_a[:3]: print(f"\n[{q['set']} Q{q['num']}]") print(q['block'][:300]) print("---") EOF

python3 << 'EOF' # The extraction is getting less than 100 questions per set - the regex is being too strict # Let me use a different approach - extract all text and manually identify questions by reading page by page # and use content-based classification with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() # CHAPTER KEYWORD MAPPINGS # I'll classify questions based on content keywords CHAPTER_KEYWORDS = { "1. Parasitic Infections": [ 'malaria', 'plasmodium', 'filaria', 'brugia', 'wuchereria', 'schistosom', 'ascaris', 'hookworm', 'amoeba', 'amoebi', 'entamoeba', 'giardia', 'trichomonas', 'toxoplasma', 'taenia', 'cysticercosis', 'microfilariae', 'filariasis', 'dengue', 'parasit', 'leishmania', 'trypanosoma', 'strongyloides', 'flukes', 'trematode', 'nematode', 'intestinal worm', 'soil transmitted', 'chikungunya', 'zika', 'rabies', 'post exposure prophylaxis', 'rig and vaccine', 'rig only' ], "2. Review of Respiratory Physiology / Approach to Respiratory Disease": [ 'spirometry', 'fev1', 'fvc', 'lung volumes', 'tidal volume', 'residual volume', 'total lung capacity', 'vital capacity', 'dlco', 'diffusion capacity', 'v/q', 'ventilation perfusion', 'dead space', 'alveolar', 'compliance', 'obstructive', 'restrictive', 'pulmonary function', 'peak flow', 'flow volume', 'pao2', 'paco2', 'hypoxemia', 'hypercapnia', 'respiratory failure', 'work of breathing', 'surfactant', 'laplace', 'pneumotachograph', 'abg interpretation', 'acid base', 'respiratory acidosis', 'respiratory alkalosis', 'approach to respiratory', 'signs of respiratory', 'sputum analysis', 'chest x-ray interpretation', 'cxr', 'pulmonary physiology', 'intrapulmonary shunt', 'anatomic dead space', 'physiologic dead space' ], "3. Bronchiectasis / Lung Abscess / Cystic Fibrosis": [ 'bronchiectasis', 'tram track', 'signet ring', 'cylindrical', 'saccular bronchi', 'lung abscess', 'anaerobic', 'putrid sputum', 'foul smelling sputum', 'cystic fibrosis', 'cftr', 'sweat chloride', 'sweat test', 'meconium ileus', 'pseudomonas aeruginosa cystic', 'delta f508', 'ivacaftor', 'lumacaftor', 'aspiration pneumonia', 'thick-walled cavity', 'air-fluid level', 'recurrent sinopulmonary', 'kartagener', 'immotile cilia', 'primary ciliary' ], "4. Gram Negative II - Meningococcal, Gonococcal, HACEK": [ 'meningococ', 'neisseria meningitidis', 'waterhouse-friderichsen', 'gonococ', 'gonorrhea', 'gonorrhoea', 'neisseria gonorrhoeae', 'urethral discharge', 'hacek', 'haemophilus', 'aggregatibacter', 'cardiobacterium', 'eikenella', 'kingella', 'gram-negative intracellular diplococci', 'disseminated gonococcal', 'meningococcal vaccine', 'porin', 'outer membrane protein', 'pili fimbriae', 'pelvic inflammatory', 'purulent conjunctivitis', 'ophthalmia neonatorum', 'ceftriaxone gonorrhea', 'azithromycin gonorrhea', 'doxycycline chlamydia co-infection' ], "5. Fungal Infections": [ 'fungal', 'fungi', 'candida', 'aspergill', 'cryptococ', 'histoplasma', 'coccidioid', 'mucor', 'rhizopus', 'sporothrix', 'blastomyces', 'tinea', 'dermatophyt', 'fluconazole', 'itraconazole', 'voriconazole', 'amphotericin', 'caspofungin', 'antifungal', 'cryptococcal meningitis', 'india ink', 'galactomannan', 'beta-d-glucan', 'pneumocystis', 'pcp', 'aspergillosis', 'candidiasis', 'vulvovaginal candidiasis', 'invasive fungal', 'dimorphic fungi', 'athlete\'s foot', 'ringworm', 'onychomycosis', 'mucormycosis' ] } # Now process the text page by page to extract question blocks # with better parsing import re def classify_question(text): """Classify a question block into a chapter""" text_lower = text.lower() scores = {} for chapter, keywords in CHAPTER_KEYWORDS.items(): score = sum(1 for kw in keywords if kw.lower() in text_lower) if score > 0: scores[chapter] = score if scores: return max(scores, key=scores.get), max(scores.values()) return None, 0 # Parse the full prelim text (lines 12-1949) to extract individual question blocks lines = full_text.split('\n') prelim_lines = lines[12:1950] prelim_text = '\n'.join(prelim_lines) # Split into question blocks using a comprehensive pattern # Questions start with number followed by period/dot and space # Also handle _8. , _29. etc. question_pattern = re.compile(r'(?:^|\n)([_\-]?\d{1,3}[.\)]\s+)', re.MULTILINE) splits = question_pattern.split(prelim_text) # Rebuild question blocks questions_raw = [] i = 1 while i < len(splits): q_prefix = splits[i].strip() q_body = splits[i+1] if i+1 < len(splits) else '' num_match = re.match(r'(\d+)', q_prefix) if num_match: qnum = int(num_match.group(1)) if 1 <= qnum <= 100: questions_raw.append({ 'num': qnum, 'text': q_prefix + ' ' + q_body }) i += 2 print(f"Total raw question blocks: {len(questions_raw)}") # Classify each chapter_questions = {ch: [] for ch in CHAPTER_KEYWORDS.keys()} unclassified = [] for q in questions_raw: chapter, score = classify_question(q['text']) if chapter and score >= 1: chapter_questions[chapter].append(q) # else: # unclassified.append(q) for ch, qs in chapter_questions.items(): print(f"\n{ch}: {len(qs)} questions") for q in qs[:2]: print(f" Q{q['num']}: {q['text'][:100]}...") EOF

python3 << 'EOF' # The auto-classification is reasonable but some questions are misclassified (e.g. Q3 rabies in Parasitic) # Let me look at what questions ended up in each chapter and also look at the full blocks more carefully # Also let me check for false positives - rabies question should be in Parasitic Infections context with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() import re CHAPTER_KEYWORDS = { "1. Parasitic Infections": [ 'malaria', 'plasmodium', 'filaria', 'brugia', 'wuchereria', 'schistosom', 'ascaris', 'hookworm', 'amoeba', 'amoebi', 'entamoeba', 'giardia', 'trichomonas', 'toxoplasma', 'taenia', 'cysticercosis', 'microfilariae', 'filariasis', 'dengue', 'parasit', 'leishmania', 'trypanosoma', 'strongyloides', 'flukes', 'trematode', 'nematode', 'intestinal worm', 'soil transmitted', 'chikungunya', 'zika', 'rabies', 'post exposure prophylaxis', 'rig and vaccine', 'rig only' ], "2. Review of Respiratory Physiology / Approach to Respiratory Disease": [ 'spirometry', 'fev1', 'fvc', 'lung volumes', 'tidal volume', 'residual volume', 'total lung capacity', 'vital capacity', 'dlco', 'diffusion capacity', 'v/q', 'ventilation perfusion', 'dead space', 'alveolar', 'compliance', 'obstructive', 'restrictive', 'pulmonary function', 'peak flow', 'flow volume', 'pao2', 'paco2', 'hypoxemia', 'hypercapnia', 'respiratory failure', 'work of breathing', 'surfactant', 'laplace', 'pneumotachograph', 'abg interpretation', 'acid base', 'respiratory acidosis', 'respiratory alkalosis', 'approach to respiratory', 'signs of respiratory', 'sputum analysis', 'chest x-ray interpretation', 'cxr', 'pulmonary physiology', 'intrapulmonary shunt', 'anatomic dead space', 'physiologic dead space', 'obstructive pattern', 'restrictive pattern', 'pulmonary fibrosis' ], "3. Bronchiectasis / Lung Abscess / Cystic Fibrosis": [ 'bronchiectasis', 'tram track', 'signet ring', 'cylindrical', 'saccular bronchi', 'lung abscess', 'anaerobic', 'putrid sputum', 'foul smelling sputum', 'foul-smelling', 'cystic fibrosis', 'cftr', 'sweat chloride', 'sweat test', 'meconium ileus', 'pseudomonas aeruginosa cystic', 'delta f508', 'ivacaftor', 'lumacaftor', 'aspiration pneumonia', 'thick-walled cavity', 'air-fluid level', 'recurrent sinopulmonary', 'kartagener', 'immotile cilia', 'primary ciliary', 'hypertonic saline', 'salty', 'chloride transport', 'mucus plug', 'prevotella', 'bacteroides', 'fusobacterium', 'klebsiella lung', 'daily sputum production', 'daily productive cough' ], "4. Gram Negative II - Meningococcal, Gonococcal, HACEK": [ 'meningococ', 'neisseria meningitidis', 'waterhouse-friderichsen', 'gonococ', 'gonorrhea', 'gonorrhoea', 'neisseria gonorrhoeae', 'urethral discharge', 'hacek', 'haemophilus aphrophilus', 'aggregatibacter', 'cardiobacterium', 'eikenella', 'kingella', 'gram-negative intracellular diplococci', 'disseminated gonococcal', 'meningococcal vaccine', 'outer membrane protein', 'pili fimbriae', 'pelvic inflammatory', 'purulent conjunctivitis', 'ophthalmia neonatorum', 'dysuria urethral', 'urethritis', 'cervicitis', 'gonococcal arthritis', 'gram negative diplococci', 'intracellular diplococci', 'porin gonococ', 'doxycycline co-infection', 'trachomatis co-infection' ], "5. Fungal Infections": [ 'fungal', 'fungi', 'candida', 'aspergill', 'cryptococ', 'histoplasma', 'coccidioid', 'mucor', 'rhizopus', 'sporothrix', 'blastomyces', 'tinea', 'dermatophyt', 'fluconazole', 'itraconazole', 'voriconazole', 'amphotericin', 'caspofungin', 'antifungal', 'cryptococcal meningitis', 'india ink', 'galactomannan', 'beta-d-glucan', 'pneumocystis', 'pcp', 'aspergillosis', 'candidiasis', 'vulvovaginal candidiasis', 'invasive fungal', 'dimorphic fungi', 'athlete\'s foot', 'ringworm', 'onychomycosis', 'mucormycosis' ] } def classify_question(text): text_lower = text.lower() scores = {} for chapter, keywords in CHAPTER_KEYWORDS.items(): score = sum(1 for kw in keywords if kw.lower() in text_lower) if score > 0: scores[chapter] = score if scores: return max(scores, key=scores.get), scores return None, {} lines = full_text.split('\n') prelim_lines = lines[12:1950] prelim_text = '\n'.join(prelim_lines) question_pattern = re.compile(r'(?:^|\n)([_\-]?\d{1,3}[.\)]\s+)', re.MULTILINE) splits = question_pattern.split(prelim_text) questions_raw = [] i = 1 while i < len(splits): q_prefix = splits[i].strip() q_body = splits[i+1] if i+1 < len(splits) else '' num_match = re.match(r'(\d+)', q_prefix) if num_match: qnum = int(num_match.group(1)) if 1 <= qnum <= 100: questions_raw.append({ 'num': qnum, 'text': (q_prefix + ' ' + q_body).strip() }) i += 2 print(f"Total raw question blocks: {len(questions_raw)}") chapter_questions = {ch: [] for ch in CHAPTER_KEYWORDS.keys()} for q in questions_raw: chapter, scores = classify_question(q['text']) if chapter: chapter_questions[chapter].append({**q, 'scores': scores}) # Print ALL questions per chapter for ch, qs in chapter_questions.items(): print(f"\n{'='*80}") print(f"CHAPTER: {ch}") print(f"Total questions: {len(qs)}") print('='*80) for q in qs: # Clean up the text a bit - remove page markers and extra whitespace clean_text = re.sub(r'PRELIM EXAM \d+ of \d+', '', q['text']) clean_text = re.sub(r'=== PAGE \d+ ===', '', clean_text) clean_text = re.sub(r'\n{3,}', '\n\n', clean_text) print(f"\nQ{q['num']}:") print(clean_text[:600]) print() EOF

python3 << 'EOF' # I notice some misclassifications: # - Q50 in Bronchiectasis section is about Leprosy (M. leprae) - false positive due to "sputum" keyword # - Q7 in Parasitic is about Viral infection (false positive due to "Parasitic infection" being one of the options) # Let me also check for more Gram Neg II / Meningococcal questions that might be missed # and look for more respiratory physiology questions # Let me also check: SET A Q13/14 (E.histolytica/Shigella), Q17 (amoebiasis treatment) # and also look at what's around lines 430-570 for more Gram Neg / Fungal questions with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() lines = full_text.split('\n') print("=== Lines 430-580 ===") for i in range(430, 582): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # Now let me also check lines 580-970 for more Gram Neg/Fungal questions that might be missed # and look at the SET B more carefully for meningococcal/gonococcal/hacek questions with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() lines = full_text.split('\n') print("=== Lines 580-700 ===") for i in range(580, 700): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # Let me check lines 700-970 to find more bronchiectasis/lung abscess/CF questions # and lines 1600-1900 for more gram neg / fungal / meningococcal questions in SET B with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() lines = full_text.split('\n') print("=== Lines 700-970 ===") for i in range(700, 970): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # Now let me compile the definitive list of questions per chapter # Based on my reading through the text, I'll manually curate the correct questions # Let me also check SET B lines 1600-1900 for more gram neg/fungal/meningococcal with open("/tmp/workspace/prelims_full_text.txt", "r") as f: full_text = f.read() lines = full_text.split('\n') print("=== Lines 1600-1900 (SET B later questions) ===") for i in range(1600, 1900): print(f"{i}: {lines[i]}") EOF

python3 << 'EOF' # Write the final organized output output = """ ================================================================================ IM PRELIMS - QUESTIONS BY CHAPTER (SET A + SET B) ================================================================================ ================================================================================ CHAPTER 1: PARASITIC INFECTIONS ================================================================================ --- SET A --- Q3. Type of immunity conferred by human rabies immunoglobulin? A. Passive B. Active C. Innate D. Natural ANSWER: A. Passive (More complete answer: Passive Artificial) Q11. Patient from Agusan has filariasis from Brugia malayi with subperiodic periodicity. A blood sample is needed to identify microfilariae. Which time is the best time to collect? A. Anytime of the day B. Afternoon C. Night time D. Morning ANSWER: C. Night time (Note: Subperiodic = Afternoon) Q12. A patient with filariasis presents with fever and painful swollen inguinal lymph nodes. Which of the following terms BEST describes this clinical presentation? A. Acute adenolymphangitis B. Acute adenolymphangioadenitis C. Lymphedema D. Filarial fever ANSWER: B. Acute adenolymphangioadenitis Q13-14 (Matching): Match each case with the causal agent Options: A. Salmonella sp. | B. E. histolytica | C. Shigella sp. | D. B. cereus | E. E.coli Q13. An 18 year old male returned home from a two-week trip around Asia. 10 days after, the patient developed intermittent abdominal pain with loose stool (1-2 episodes/day) associated with body malaise but with no fever. A few days after, bowel movement increased to 6-8 episodes/day now described as bloody stool with scant fecal material. At OPD, stable vital signs and no signs of dehydration, with unintentional weight loss which started during onset of symptoms about a week ago. ANSWER: B. E. histolytica Q14. An 18 year old male developed fever with watery diarrhea (2-3 episodes/day) three days after returning from a trip around Asia. The next day, he noticed worsening of cramped abdominal pain and change of stool characteristics to small-volume, mucopurulent, bloody stool. At OPD, stable vital signs and no signs of dehydration. ANSWER: C. Shigella Q15. A 45-year-old patient presents with fever, chills, and cough 1-2 months after freshwater exposure in an endemic area. P.E. presents with hepatosplenomegaly. Labs show eosinophilia. A. Acute schistosomiasis B. Ascariasis C. Hookworm D. Filariasis ANSWER: A. Acute Schistosomiasis Q16. A 30-year-old patient from Davao de Oro is referred due to seizure. Working impression is schistosomiasis. What species is likely associated with seizures? A. Japonicum B. Intercalatum C. Mansoni D. Haematobium ANSWER: A. Japonicum Q17. An 18 year old male student returned from his 2-week trip around Asia. Ten days after arrival, he developed intermittent abdominal pain with loose stools (1-2 episodes/day) and malaise, but no fever. Over the next few days, 6-8 episodes/day of small volume of bloody stool with minimal fecal material. Stable vital signs but with signs of dehydration. He also noticed unintentional weight loss over a week ago after symptoms started. What is the DOC? A. Fluoroquinolones B. Azithromycin C. Metronidazole D. Ceftriaxone ANSWER: B. Azithromycin (Note: This case is Amoebiasis - DOC = Metronidazole. Some sets marked B. Azithromycin for the Shigella version of this case) Q18. Eosinophilic pneumonitis on CXR, clinical signs of unproductive cough, substernal burning, and occasional fever. What parasitic infection is most likely? A. Ascariasis B. Schistosomiasis C. Filariasis D. Amoebiasis ANSWER: A. Ascariasis Q26. What is the primary pre-exposure rabies prophylaxis schedule? A. 0, 3, 7 B. 0, 3, 7, 14 C. 0, 7, 14 D. 0, 7, 21 ANSWER: D. 0, 7, 21 Q44. A patient is suffering from dengue. Which of the following is a warning sign? A. Abdominal pain B. Arthralgia C. Positive tourniquet D. Fever ANSWER: A. Abdominal pain --- SET B --- Q4. A 25-year-old female presents with a 5-day history of fever associated with headache, myalgia, distal symmetrical polyarthralgia. What is the diagnosis? A. Dengue with warning signs B. Zika virus infection C. Chikungunya D. Measles infection ANSWER: C. Chikungunya Q5. A 25-year-old male patient sought consultation at the OPD ER due to open wound. He was bitten by a stray dog while walking around the village. What is your post-exposure prophylaxis? A. Observe patient B. Give RIG only C. Give vaccine only D. Give RIG and vaccine ANSWER: D. Give RIG and vaccine (Category 3 exposure) Q6. In malaria, the onset of clinical symptoms corresponds to which event in the parasite's life cycle? A. Increase in parasite density in the peripheral blood B. Increase in hepatic merozoites within hepatocytes C. Inflammatory response triggered by blood parasites in hepatocytes and bloodstream D. Activation of hypnozoites in the liver ANSWER: A. Increased parasite density in peripheral bloodstream Q7. Which malarial species has an affinity to older RBCs? A. P. falciparum B. P. vivax C. P. ovale D. P. malariae ANSWER: D. P. malariae Q8. Which of the following laboratory results is NOT typically observed in malaria infection? A. Normocytic normochromic anemia B. Proteinuria C. Thrombocytopenia D. Elevated ESR and CRP ANSWER: B. Proteinuria Q9. Not included in laboratory examination results for dengue: A. Normocytic normochromic anemia B. Proteinuria C. Thrombocytopenia D. Elevated ESR/CRP ANSWER: B. Proteinuria Q16. What is the usual incubation period of rabies before the onset of clinical disease? A. 2 to 7 days B. 10 to 30 days C. 20 to 90 days D. 90 to 180 days ANSWER: C. 20 to 90 days Q17. Which of the following is true on dengue fever? A. Malnutrition is protective B. Males are equally affected as females C. Patients above 12 yo are more susceptible D. All of the statements ANSWER: A. Malnutrition is protective Q19. A 30-year-old female patient presented with a history of 5-day abrupt-onset fever, chills, myalgia, and headache. Muscle pain is most intense on the calves and lower back. The patient is febrile and appears ill with conjunctival redness but no rash and retroorbital pain. VS is normal. Lab result showed Hgb: 125 g/L, WBC: 5000 (Neutro: 55%, Lympho: 40%), plt: 145000, and mildly elevated liver enzymes. A. Dengue without warning signs B. Chikungunya C. Malaria D. Leptospirosis E. Typhoid fever ANSWER: D. Leptospirosis Q20. A female patient with a 4-day history of fever (38.5–39.3°C) reports retro-orbital pain, myalgia, and generalized weakness. She has loss of appetite but no nausea or abdominal pain. Physical examination: Temperature 39.5°C; faint maculopapular rash on the trunk; scant petechiae on the forearm; no splenomegaly and no abdominal tenderness. What is the most likely diagnosis? A. Dengue without warning signs B. Chikungunya C. Malaria D. Typhoid ANSWER: A. Dengue without warning signs Q56. In malaria infection, the symptomatic stage begins with which event? A. Increased parasite density in peripheral bloodstream B. Increase in liver-stage merozoites in the hepatocytes C. Inflammatory reaction to blood-stage parasites in the liver and bloodstream D. Increased hypnozoites in the liver ANSWER: A. Increased parasite density in peripheral bloodstream Q58. Which of the following lab results are NOT observed in patients with malarial infection? A. Normocytic normochromic anemia B. Proteinuria C. Thrombocytopenia D. Elevated ESR and CRP ANSWER: B. Proteinuria Q60. Based on Harrison's, the drug of choice for severe malaria: A. Mefloquine B. Chloroquine C. Artesunate D. Quinine ANSWER: C. Artesunate Q61. A patient from Agusan is suspected of having filariasis due to Brugia malayi with a subperiodic periodicity. A blood sample is needed to detect microfilaria. What is the best time to collect the blood sample? A. Any time of day B. Morning C. Afternoon D. Night time ANSWER: C. Afternoon (subperiodic = afternoon) Q62. A patient diagnosed with filaria presents with fever, painful, swollen inguinal lymph nodes. What term best describes this clinical presentation? A. Acute lymphangitis B. Acute lymphangioadenitis C. Lymphedema D. Filarial fever ANSWER: B. Acute lymphangioadenitis Q65. A 45-year-old male develops fever, chills, and cough 1-2 months after freshwater exposure to an endemic area. Physical examination reveals hepatosplenomegaly, and laboratory tests show eosinophilia. What is the most likely diagnosis? A. Acute Schistosomiasis B. Ascariasis C. Filariasis D. Hookworm infection ANSWER: A. Acute Schistosomiasis Q66. 30M from Davao De Oro, presented with seizures. Working diagnosis is Schistosomiasis. Which species presents with seizure? A. Japonicum B. Mansoni C. Intercalatum D. Haematobium ANSWER: A. Japonicum Q67. 18M from a 2-week trip to Asia. After 10 days, presented with abdominal pain with loose stools (1-2 eps/day) with malaise but no fever. Over next few days, bowel movement increased to 6-8 eps/day, now small bloody stool with minimal fecal material. On OPD, vital signs stable but with clinical signs of dehydration, and unintentional weight loss. Drug of choice? A. Penicillin B. Fluoroquinolone C. Metronidazole D. Ceftriaxone ANSWER: C. Metronidazole (Amoebiasis) Q68. Chest imaging shows eosinophilic pneumonitis with nonproductive cough, occasional fever. What is the most likely etiology? A. Ascariasis B. Strongyloidiasis C. Amoebiasis ANSWER: A. Ascariasis Q69. A 30-year-old pregnant patient is diagnosed with ascariasis. Which medication should you give? A. Pyrantel pamoate B. Mebendazole C. Albendazole D. Metronidazole ANSWER: A. Pyrantel Pamoate Q76. Rabies pre-exposure prophylaxis schedule: A. Day 0, 3, 7 B. Day 0, 3, 7, 14 C. Day 0, 7, 14 D. Day 0, 7, 21 ANSWER: D. Day 0, 7, 21 Q94. A patient is suffering from dengue with warning sign. Which of the following is most likely present? A. Abdominal pain B. Arthralgia C. Positive tourniquet D. Fever ANSWER: A. Abdominal pain ================================================================================ CHAPTER 2: REVIEW OF RESPIRATORY PHYSIOLOGY / APPROACH TO PATIENTS WITH DISEASE OF THE RESPIRATORY TRACT ================================================================================ --- SET A --- Q32. A 72-year-old woman developed idiopathic pulmonary fibrosis after severe COVID-19 infection. Which condition correlates? A. Restrictive, chest wall B. Restrictive, parenchyma C. Restrictive, neuromuscular D. Restrictive, pleural ANSWER: B. Restrictive, parenchyma Q34 / Q84. What lung volume study is definitive for restrictive ventilatory defect? A. Low TLC B. Low FVC C. Low FEV1 D. Low FEV1/FVC ANSWER: A. Low TLC Q40. The ER resident noted pleural effusion on the PA CXR. What other view is most useful to determine that pleural fluid is freely flowing? A. Lateral B. Apicolordotic C. AP D. Lateral decubitus ANSWER: D. Lateral decubitus (shows displacement of fluid = freely flowing) Q81. If you were to percuss a lung with mid to basal pleural effusion, where do you expect egophony? A. Apical lung fields B. Base of lungs C. Contralateral lung D. Topmost portion of pleural fluid ANSWER: D. Topmost portion of pleural fluid Q82. 72-year-old man had IPF (Idiopathic Pulmonary Fibrosis) that became clinically apparent 3 months after severe COVID-19 infection. What pulmonary category of disease is this? A. Restrictive, chest wall B. Restrictive, parenchyma C. Restrictive, neuromuscular D. Restrictive, pleural disease ANSWER: B. Restrictive, parenchyma Q83. 32-year-old man with known peanut allergy. Which PE findings suggest an impending upper airway obstruction and constitutes an emergency? A. Stridor B. Audible wheezing C. Whispered pectoriloquy D. Velcro-like crackles ANSWER: A. Stridor Q85. A female had silicone breast implants. A few days later, she developed shortness of breath. What is the nature of the problem? A. Ventilatory restriction due to chest wall abnormality B. Ventilatory restriction due to increased elastic recoil C. Ventilatory obstruction due to increased elastic recoil D. Ventilatory obstruction due to chest wall abnormality ANSWER: A. Ventilatory restriction due to chest wall abnormality Q86. A 67-year-old woman with long-standing RA since her early 30s presents with progressive dyspnea and a nonproductive cough. Chest examination showed "Velcro-like" inspiratory crackles. What best confirms the diagnosis? A. Chest X-ray PA B. Low dose non-contrast CT C. MRI D. High resolution non-contrast CT ANSWER: D. High resolution non-contrast CT Q87. A 24/M was admitted for femoral fracture from vehicular crash and was advised surgical orthopedic intervention but refuses. On the following day, he had sudden dyspnea and desaturations. What test would you use to confirm pulmonary pathology? A. Fibrin degradation B. Pulmonary angiography C. D-dimer D. Computed tomography pulmonary angiography ANSWER: D. Computed tomography pulmonary angiography Q88. A 36-year-old male psychiatric patient was brought to the ER after aspirating siling labuyo. What is the next appropriate step? A. Pleuroscopy B. Thoracoscopy C. Bronchoscopy D. Mediastinoscopy ANSWER: C. Bronchoscopy --- SET B --- Q82. A 75-year-old woman suffers from IPF. What is the nature of the illness? A. Restrictive, chest wall B. Obstructive, chest wall C. Restrictive, parenchyma D. Obstructive, upper airway ANSWER: C. Restrictive, parenchyma ================================================================================ CHAPTER 3: BRONCHIECTASIS / LUNG ABSCESS / CYSTIC FIBROSIS ================================================================================ --- SET A --- Q21 / Q71 (SET A). 51-year-old fisherman drinks gin most nights of the week, has fever and cough presenting foul-smelling sputum. Chest X-ray shows cavitary lesion with air-fluid level in the superior segment of the right lower lobe. What is the most likely etiologic agent? A. Mycobacterium pneumoniae B. Prevotella species C. Pseudomonas aeruginosa D. Streptococcus pneumoniae ANSWER: B. Prevotella species (Foul-smelling sputum + alcoholism + fever = Primary lung abscess) Q72. A preschool teacher with tricuspid valve endocarditis came in the ER complaining of productive cough with greenish phlegm associated with fever and chest pain. Chest X-ray shows thick-walled cavitation. What is the most likely etiologic agent? A. Anaerobes B. Fusobacterium necrophorum C. S. aureus D. Pseudomonas aeruginosa ANSWER: C. S. aureus Q73 / Q23. Which clinical feature is characteristic of an anaerobic lung abscess? A. Foul-smelling purulent sputum B. Sudden onset of hemoptysis C. Fulminant course with high fever D. Chronic indolent presentation with night sweats ANSWER: A. Foul-smelling purulent sputum Q74 / Q24. Who is the most at risk of developing anaerobic lung abscess? A. A 24-year-old male, fast food service crew member with gingivitis B. A 32-year-old seamstress with tricuspid valve endocarditis C. A 50-year-old truck driver with COPD on inhaled corticosteroids D. A 61-year-old female with impaired consciousness due to stroke ANSWER: D. A 61-year-old female with impaired consciousness due to stroke (risk for aspiration) Q75. Which finding indicates percutaneous drainage or surgical intervention in a lung abscess? A. 5 cm lung abscess on the 2nd day of antibiotic use B. 6.5 cm lung abscess after 7 days of antibiotics with no relief C. CT scan showing air-fluid cavity ANSWER: B. 6.5 cm lung abscess after 7 days of antibiotics with no relief Q76 / Q26. A 27-year-old female law student presented with chronic cough, salty-tasting skin, and recurrent sinus infections. HRCT showed tram track and signet ring appearance predominantly seen in the upper lobe. What is the diagnosis? A. Cystic fibrosis B. Post-TB bronchiectasis C. Primary ciliary dyskinesia D. Alpha-1 antitrypsin deficiency ANSWER: A. Cystic fibrosis ("Salty" skin + signet ring and tram track = Bronchiectasis in CF) Q27. 39-year-old bartender with long-standing bronchiectasis, daily sputum production, recurrent exacerbations, persistent infection with Pseudomonas. Immune tests normal, no symptoms of reflux. What is the adjunctive treatment with MOST benefit? A. Antifungal therapy B. Inhaled bronchodilator C. Inhaled hypertonic saline D. Oral prednisone ANSWER: C. Inhaled hypertonic saline Q28. 55-year-old female office clerk with persistent cough and brown sputum plugs. Radiology showed tram tracks, elevated IgE, positive aspergillus-specific IgE. Where are the bronchiectasis changes located? A. Diffuse in lower lobe B. Focal upper lobe C. Mid lobe D. Central airways ANSWER: D. Central airways (ABPA = central bronchiectasis) Q29. A 36-year-old female presents with a productive cough and recurrent pneumonia on her left upper lobe. The best diagnostic tool: A. Bronchoscopy B. Sputum AFB or TB Gene Xpert C. Sweat chloride testing D. Quantitative IgG level ANSWER: A. Bronchoscopy Q80 / Q30. A 19-year-old engineering student with cystic fibrosis was started with a CFTR modulator, which helps in gating mutations. It helps in: A. Viscosity of mucus B. Pancreatic secretion C. Chloride transport and lung function ANSWER: C. Chloride transport and lung function --- SET B --- (Questions from SET B that repeat or are the same cases as SET A above are not duplicated. Additional unique items below:) Q22. A 40-year-old female with tricuspid valve endocarditis presents with fever and green purulent sputum. Chest X-ray shows thick-walled cavity. What is the etiologic agent? A. Anaerobes B. Fusobacterium necrophorum C. Staphylococcus aureus D. Pseudomonas aeruginosa ANSWER: C. Staphylococcus aureus Q30 (SET B). An engineering patient was diagnosed with cystic fibrosis and was given CFTR gating modulators. What is its therapeutic effect? A. Improve viscosity B. Increase pancreatic secretion C. Increase chloride secretion D. Risk for pseudomonas infection ANSWER: C. Increase Chloride Secretion & Improve Lung Function ================================================================================ CHAPTER 4: GRAM NEGATIVE INFECTIONS II - MENINGOCOCCAL, GONOCOCCAL, HACEK ================================================================================ --- SET A --- Q21 (SET A). Which of the following organisms most commonly causes endocarditis in patients with HACEK? [Matching - What valve is affected?] A. Cardiobacterium hominis B. Eikenella sp. C. Haemophilus species D. Kingella kingae (Question refers to: Which HACEK organism commonly affects the mitral/aortic valve?) Q22 (SET A). A 20-year-old male was examined due to dysuria and urethral discharge. Gram stain showed Gram-negative intracellular diplococci. Aside from prescribing the primary drug, doxycycline may be added for which of the following reasons? A. Synergistic effect with the primary drug B. Additive effect with the primary drug C. Frequent occurrence of co-infection with C. trachomatis D. Frequent occurrence of co-infection with M. hominis ANSWER: C. Frequent occurrence of co-infection with C. trachomatis Q32 (SET A). Which of the following valve(s) is/are commonly affected in patients with HACEK endocarditis? A. Mitral and Aortic B. Tricuspid and Mitral C. Aortic and Pulmonic D. Pulmonic and Tricuspid ANSWER: A. Mitral and Aortic Q33 (SET A). Most abundant gonococcal surface protein associated with immune evasion? A. Pili B. H8 C. Porin D. Lipooligosaccharide ANSWER: C. Porin Q52 (SET A). Most common/predominant manifestation of gonorrhea in men: A. Acute urethritis B. Acute epididymitis ANSWER: A. Acute urethritis --- SET B --- Q71 (SET B). Among the HACEK organisms, which bacteria primarily infects the aortic valve? A. Haemophilus B. Aggregatibacter C. Cardiobacterium D. Eikenella E. Kingella ANSWER: C. Cardiobacterium (HACEK Summary: H = Mitral | A = Mitral + Prosthetic | C = Aortic | E = Human bite wounds | K = Bone/joints in children) Q72 (SET B). A 20-year-old male with dysuria, gram-negative intracellular diplococci. Why is azithromycin added to the primary drug? A. Synergistic effect B. Additive effect C. Frequent co-infection with C. trachomatis D. Frequent co-infection with M. hominis E. Frequent co-infection with U. urealyticum ANSWER: C. Frequent co-infection with C. trachomatis Q83 (SET B). What meningococcal surface membrane protein is most abundant and has the ability to evade host adaptive immune response? A. Pili B. Porin C. Lipooligosaccharide D. H.8 ANSWER: B. Porin (Harrison's 22nd ed., p. 1254) ================================================================================ CHAPTER 5: FUNGAL INFECTIONS ================================================================================ --- SET A --- Q34 (SET A). What are the major risk factors in developing Aspergillosis? A. Advanced age and male sex B. Neutropenia and glucocorticoid use C. Neutropenia and diabetes mellitus D. COPD and asthma ANSWER: B. Neutropenia and glucocorticoid use Q48 (SET A). In patients with vulvovaginal candidiasis, what is the treatment of choice? A. Amphotericin B B. Topical azole C. Clotrimazole D. Fluconazole ANSWER: B. Topical azole (Amphotericin B is IV/not appropriate for uncomplicated; Fluconazole is an alternative but topical azole is first-line) Q65 (SET A). Which fungal infection is seen in patients with COVID in countries like India, presenting with facial pain, leading to proptosis? A. Mucormycosis B. Invasive aspergillosis C. Histoplasmosis D. Sporotrichosis ANSWER: A. Mucormycosis --- SET B --- Q12 (SET B). What is the most common pathogen causing nosocomial UTI among patients in the ICU? A. E. coli B. Nosocomial gram-negative bacilli C. Enterococci D. Candida ANSWER: D. Candida Q14 (SET B). What is the predominant cell indicated for the protection against Candida and Aspergillus infection? A. Neutrophil B. Eosinophil C. Lymphocyte D. Monocyte ANSWER: A. Neutrophil Q15 (SET B). Which fungal infection is common among patients with COVID-19, in countries like India, causing eye and retroorbital pain extending to ethmoid sinuses, leading to EOM dysfunction and proptosis? A. Mucormycosis B. Invasive aspergillosis C. Histoplasmosis D. Sporotrichosis ANSWER: B. Invasive aspergillosis (most likely answer per reviewer) Q84 (SET B). What are major risk factors for developing aspergillosis? A. Advancing age and male sex B. Neutropenia and glucocorticoid use C. Neutropenia and DM D. COPD and asthma ANSWER: B. Neutropenia and glucocorticoid use (Harrison's 22nd ed., p. 1713) Q98 (SET B). In patients with vulvovaginal candidiasis, what is the treatment of choice? A. Fluconazole B. Amphotericin B C. Topical azole D. Clotrimazole ANSWER: A. Fluconazole (Note: Per Candidiasis portion, Dr. Loren's Trans 2024 Kairos - Fluconazole is indicated here) ================================================================================ END OF CHAPTER-SEPARATED QUESTIONS ================================================================================ """ with open("/tmp/workspace/prelims_by_chapter.txt", "w") as f: f.write(output) print("Done! Saved to /tmp/workspace/prelims_by_chapter.txt") print(f"Total characters: {len(output)}") EOF