Abstract
ObjectivesTo evaluate the performance of the predictors in estimating the probability of pulmonary tuberculosis (PTB) when all versus only significant variables are combined into a decision model (1) among all clinical suspects and (2) among smear-negative cases based on the results of culture tests.DesignA cross-sectional study.SettingTwo public referral hospitals in Tigray, Ethiopia.ParticipantsA total of 426 consecutive adult patients admitted to the hospitals with clinical suspicion of PTB were screened by sputum smear microscopy and chest radiograph (chest X-ray (CXR)) in accordance with the Ethiopian guidelines of the National Tuberculosis and Leprosy Program. Discontinuation of antituberculosis therapy in the past 3 months, unproductive cough, HIV positivity and unwillingness to give written informed consent were the basis of exclusion from the study.Primary and secondary outcome measuresA total of 354 patients were included in the final analysis, while 72 patients were excluded because culture tests were not done.ResultsThe strongest predictive variables of culture-positive PTB among patients with clinical suspicion were a positive smear test (OR 172; 95% CI 23.23 to 1273.54) and having CXR lesions compatible with PTB (OR 10.401; 95% CI 5.862 to 18.454). The regression model had a good predictive performance for identifying culture-positive PTB among patients with clinical suspicion (area under the curve (AUC) 0.84), but it was rather poor in patients with a negative smear result (AUC 0.64). Combining all the predictors in the model compared with only the independent significant variables did not really improve its performance to identify culture-positive (AUC 0.84–0.87) and culture-negative (AUC 0.64–0.69) PTB.ConclusionsOur finding suggests that predictive models based on clinical variables will not be useful to discriminate patients with culture-negative PTB from patients with culture-positive PTB among patients with smear-negative cases.
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