• Rulan Griesel, Annemie Stewart, Helen van der Plas, Welile Sikhondze, Molebogeng X Rangaka, Mark P Nicol, Andre P Kengne, Marc Mendelson, and Gary Maartens.
• Division of Clinical Pharmacology, University of Cape Town, South Africa.
• Clin. Infect. Dis. 2018 Apr 17; 66 (9): 1419-1426.

BackgroundThe World Health Organization (WHO) algorithm for the diagnosis of tuberculosis in seriously ill human immunodeficiency virus (HIV)-infected patients lacks a firm evidence base. We aimed to develop a clinical prediction rule for the diagnosis of tuberculosis and to determine the diagnostic utility of the Xpert MTB/RIF assay in seriously ill HIV-infected patients.MethodsWe conducted a prospective study among HIV-infected inpatients with any cough duration and WHO-defined danger signs. Culture-positive tuberculosis from any site was the reference standard. A priori selected variables were assessed for univariate associations with tuberculosis. The most predictive variables were assessed in a multivariate logistic regression model and used to establish a clinical prediction rule for diagnosing tuberculosis.ResultsWe enrolled 484 participants. The median age was 36 years, 65.5% were female, the median CD4 count was 89 cells/µL, and 35.3% were on antiretroviral therapy. Tuberculosis was diagnosed in 52.7% of participants. The c-statistic of our clinical prediction rule (variables: cough ≥14 days, unable to walk unaided, temperature >39°C, chest radiograph assessment, hemoglobin, and white cell count) was 0.811 (95% confidence interval, .802-.819). The classic tuberculosis symptoms (fever, night sweats, weight loss) added no discriminatory value in diagnosing tuberculosis. Xpert MTB/RIF assay sensitivity was 86.3% and specificity was 96.1%.ConclusionsOur clinical prediction rule had good diagnostic utility for tuberculosis among seriously ill HIV-infected inpatients. Xpert MTB/RIF assay, incorporated into the updated 2016 WHO algorithm, had high sensitivity and specificity in this population. Our findings could facilitate improved diagnosis of tuberculosis among seriously ill HIV-infected inpatients in resource-constrained settings.

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