1. Section C Maranion – Mendoza

2. Subjective Pertinent PositivePertinent Negative 28 y/o female CC: Hemoptysis Chronic cough No weight change No change in eating habits 2 months PTC: Coughing intermittently (last 2 mos) Cough = productive of scanty whitish to yellowish sputum Occasionally took ginger ale  afforded temporary relief 1 month PTC: Intermittent low grade fever, malaise and night sweats Recently: back pains, blood-streaked sputum

3. 28 y/o female Chronic cough & Hemoptysis Cough = productive of scanty whitish to yellowish sputum Intermittent low grade fever, malaise and night sweats back pains No weight change

4. DiagnosisTreatmentPossible HarmPrognosis 1.Clinical impression 2.Most probable diagnosis 3.Critical appraisal of an article about a diagnostic test 1.Clinical impression 2.Most probable diagnosis 3.Critical appraisal of an article about a diagnostic test

5. Karmi Margaret Marcial Michelle Matematico Evangelyn Grace Matias Marienelle Maulion

6.  Bronchiectasis  Lung Cancer  Tuberculosis Chief complaint: Hemoptysis Page _______

7. T. B. (The Patient )BronchiectasisLung CancerPulmonary Tuberculosis 28 y/o, femaleHigher incidence adolescence and early adulthood. Higher incidence in 25-34 y/o female Chronic cough(yellow sputum) persistent or recurrent cough and purulent sputum production cough, hemoptysis, post-obstructive pneumonitis (fever and productive cough). Cough (purulent Sputum) HemoptysisHemoptysis occurs in 50 to 70% of cases Hemoptysis (can be massive) Blood streaking of the sputum is frequently documented Low grade feverFeverFever (often low-grade and intermittent) Malaise, Night sweatsGeneral malaise and weakness, Night sweats (-) weight loss / change in eating habits Weight lossWeight loss and anorexia Probability50%30%60%

8. 10%80% 60% TB 10%80% 50% Bronchiectasis 10%90% 30% Lung CA 0%100% 10%80% 60% TB

9. Script page  In this scenario, we consider the probability the probability of ____% that the patient has TB.  We also consider institutional care for these patients if the probability is _______%  Maybe home intervention if probability is _____%

12. Page _______

15.  What is the accuracy of HRCT or CXR in diagnosis of pulmonary tuberculosis?

16. ***

17.  Was there an independent, blind comparison with a reference standard?  Yes. The pulmonologist and radiologist who independently interpreted the HRCTs were unaware of the patients’ clinical condition.

18.  Was the diagnostic test evaluated in an appropriate spectrum of patients (like those in whom we would use it in practice?)  Yes. In a 2500-bed medical center in Southern Taiwan, the study group of 157 with suggestive CXR consisted of 33 women and 124 men with an age range of 20 to 83 years.

19.  Was the reference standard applied regardless of the diagnostic test result?  Yes. Sputum culture and AFB smear microscopy were performed in diagnosing active PTB prior to subjecting the patients to HRCT.

20.  Was the test validated in a second, independent group of patients?  No. Chest X-ray and HRCT were performed on the same set patients.

21.  What is the sensitivity?  CXR: 57%  HRCT: 89%  What is the specificity?  CXR: 28%  HRCT:85%  Can you calculate a likelihood ratio, or is there one already calculated?  Yes. It can be calculated in CXR and HRCT

22. Page _______

23.  Sensitivity = 57%  Specificity = 28%  LR+ = 0.80  LR- = 1.52 (+) Dse(-) DseTotal Xray (+)326698 Xray (-)242650 Total5692148

25.  Positive Post-Test Probability = 55%  Negative Post-Test Probability = 70% 10%80% 60% TB 55%70%

26. Page _______

27.  Sensitivity = 89%  Specificity = 85%  LR+ = 5.81  LR- = 0.13 (+) Dse(-) DseTotal HRCT (+)561369 HRCT (-)77279 Total6385148

29.  Positive Post-Test Probability = 90%  Negative Post-Test Probability = 16% XrayHRCT 10%80% 60% TB 55% (+) 70% (-) 90% (+) 19% (+)

30.  In our practice, is the test:  Available? Yes. It is available in USTH.  Affordable? No. HRCT plain costs P 8000; with contrast P15,275.  Accurate? Yes. The accuracy of the test based on the pulmonologist’s interpretation is 86% and radiologist’s interpretation is 90%.  Precise? Yes.

31.  Can we generate a reasonable pre-test probability in our clinical scenario?  Yes. The pre-test probability was generated based on the manifestation of the patient.  Are the study patients similar to our own?  Yes. The study patients are similar on our own, using the patient’s age and gender as the basis.  Has anything changed since the study was published?  None.

32.  Will the resultant post-test probabilities change our management?  Yes. It will lead the physician decide to give the treatment or not.

33. Jhudielle Medenilla Kristianne Rachelle Medina Carmelou Mae Mejino

34. Ivy Melgarejo Alvin Mendoza Donne Paolo Mendoza

35. Ma. Cristina Maranion Eric John Marayag Pamela Marcelo