Prediction Models for Prevalent Pulmonary Tuberculosis in Adults
Van Wyk, S.S., Lin, H.H. and Claassens, M.M., 2017. A systematic review of prediction models for prevalent pulmonary tuberculosis in adults. The International Journal of Tuberculosis and Lung Disease, 21(4), pp.405-411.
Many presumptive TB cases are not identified promptly, leading to diagnostic and treatment delays. Studies focused on developing models using clinical predictors such as history, physical examination, and chest radiography (CXR) to estimate PTB probability; more advanced imaging technologies were excluded due to lack of availability in high TB burden settings. Exclusion criteria for studies involved settings like inpatients, specific populations (e.g., TB contacts, pregnant women, drug users), to reduce heterogeneity. Only six studies met these criteria, developing and validating models to improve PTB detection using additional factors like CD4 count, BMI, and duration on antiretroviral therapy (ART). Addition of the tuberculin skin test (TST) to the WHO symptom screen significantly improved sensitivity for detecting PTB. Development of clinical scores using various predictors to facilitate screening in routine and low-resource settings. Models showed potential for improving diagnostic accuracy by incorporating additional information to WHO recommendations. Highlighted the need for a low-cost, easily applicable TB risk score to enhance screening accuracy and feasibility in high TB burden, low-resource settings. Current reliance on the WHO symptom screen due to the absence of better alternatives.
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