The validity of medical history, classic symptoms, and chest radiographs in predicting pulmonary tuberculosis - Derivation of a pulmonary tuberculosis prediction model

Study objective: To improve the respiratory isolation policy for patients w ith suspected pulmonary tuberculosis (TB). Design: Prospective, descriptive, French multicenter study. Setting: Emergence of nosocomial outbreaks of TB. Patients: AU consecutive patients admitted with suspicion of pulmonary TB. Measurements and results: Medical history, social factors, symptoms, and ch est radiograph. (CXR) pattern (symptoms and CXR both scored as typical of p ulmonary TB, compatible, negative, or atypical) were obtained on admission. Serial morning sputa were collected. Of the 211 patients, 47 (22.3%) had c ulture-proven pulmonary TB, including 31 (14.7%) with a positive smear, Mea n age was 46.2 years; 52 patients were HIV positive (24.6%). The sensitivit y of the respirator isolation policy was 71.4%, specificity was 51.7%, nega tive predictive value (NPV) was 88.2%, and positive predictive value (PPV) was 26.3%. On univariate analysis, predictive factors of culture-proven pul monary TB were CXR (p < 0.00001), symptoms (p = 0.0004), age (mean, 40.8 ye ars for TB patients vs 47.5 years for non-TB patients; p = 0.04), absence o f HIV infection (89.4% vs 71.3%; p = 0.01), immigrant status (72% vs 55%; p = 0.03), and bacillus Calmette-Guerin status (p = 0.025). On multivariate analysis, CXR pattern (p < 0.00001), HIV infection (p = 0.002), and symptom s (p = 0.009) remained independently predictive. Based on these data, a mod el was proposed using a receiver operating characteristics curve. In the de rivation cohort, the sensitivity and NPV of the model in detecting smear-po sitive pulmonary TB would have been 100%. The specificity and PPV mould hav e been 48.4% and 25%, respectively. The model performed less well when eval uated on two retrospective groups, but its sensitivity remained above that of the current respiratory isolation policy (91.1% and 82.4% for the retrop ective groups vs 71.1% for the current policy). Conclusions: Improved interpretation of clinical and radiologic data availa ble on patient admission could improve adequacy of respiratory isolation. A prediction model is proposed.