Abstract
Objectives To 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. Design A cross-sectional study. Setting Two public referral hospitals in Tigray, Ethiopia. Participants A 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 measures A total of 354 patients were included in the final analysis, while 72 patients were excluded because culture tests were not done. Results The 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. Conclusions Our 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.
Original language | English |
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Article number | 037913 |
Number of pages | 9 |
Journal | BMJ Open |
Volume | 10 |
Issue number | 11 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- biochemistry
- infection control
- tuberculosis
- public health
- molecular diagnostics
- VALIDATION
- DIAGNOSIS
- INPATIENTS
- ACCURACY
- CARE