Utility of Targeted, Amplicon-Based Deep Sequencing To Detect Resistance to First-Line Tuberculosis Drugs in Botswana.

Multidrug-resistant tuberculosis (TB) is an alarming threat, and targeted deep sequencing (DS) may be an effective method for rapid identification of drug-resistant profiles, including detection of heteroresistance. We evaluated the sensitivity and specificity of targeted DS versus phenotypic drug susceptibility testing (pDST) among patients starting first-line anti-TB therapy in Botswana. Overall, we found high concordance between DS and pDST. Lower sensitivity of DS, which targets established high-confidence resistance variants, was observed for detecting isoniazid resistance among HIV-infected patients.

Diagnosis of pulmonary tuberculosis and assessment of treatment response through analyses of volatile compound patterns in exhaled breath samples.

OBJECTIVES: We determined the performance of a sensor array (an electronic nose) made of 8 metalloporphyrins coated quartz microbalances sensors for the diagnosis and prognosis of pulmonary tuberculosis (TB) using exhaled breath samples. METHODS: TB cases and healthy controls were prospectively enrolled. Signals from volatile organic compounds (VOCs) in breath samples were measured at days 0, 2, 7, 14, and 30 of TB therapy and correlated with clinical and microbiological measurements. RESULTS: Fifty one pulmonary TB cases and 20 healthy HIV-uninfected controls were enrolled in the study. 31 (61%) of the 51 pulmonary TB cases were coinfected with HIV. At day 0 (before TB treatment initiation) the sensitivity of our device was estimated at 94.1% (95% confidence interval [CI], 83.8-98.8%) and specificity was 90.0% (95% CI, 68.3-98.8%) for distinguishing TB cases from controls. Time-dependent changes in the breath signals were identified as time on TB treatment progressed. Time-dependent signal changes were more pronounced among HIV-uninfected patients. CONCLUSION: The identification of VOCs' signals in breath samples using a sensor array achieved high sensitivity and specificity for the diagnosis of TB and allowed following signal changes during TB treatment.

Artificial Intelligence and Amikacin Exposures Predictive of Outcomes in Multidrug-Resistant Tuberculosis Patients.

Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR-TB). We measured amikacin concentrations in 28 MDR-TB patients in Botswana receiving amikacin therapy together with oral levofloxacin, ethionamide, cycloserine, and pyrazinamide and calculated areas under the concentration-time curves from 0 to 24 h (AUC0-24). The patients were followed monthly for sputum culture conversion based on liquid cultures. The median duration of amikacin therapy was 184 (range, 28 to 866) days, at a median dose of 17.30 (range 11.11 to 19.23) mg/kg. Only 11 (39%) patients had sputum culture conversion during treatment; the rest failed. We utilized classification and regression tree analyses (CART) to examine all potential predictors of failure, including clinical and demographic features, comorbidities, and amikacin peak concentrations (Cmax), AUC0-24, and trough concentrations. The primary node for failure had two competing variables, Cmax of <67 mg/liter and AUC0-24 of <568.30 mg · h/L; weight of >41 kg was a secondary node with a score of 35% relative to the primary node. The area under the receiver operating characteristic curve for the CART model was an R(2) = 0.90 on posttest. In patients weighing >41 kg, sputum conversion was 3/3 (100%) in those with an amikacin Cmax of ≥67 mg/liter versus 3/15 (20%) in those with a Cmax of <67 mg/liter (relative risk [RR] = 5.00; 95% confidence interval [CI], 1.82 to 13.76). In all patients who had both amikacin Cmax and AUC0-24 below the threshold, 7/7 (100%) failed, compared to 7/15 (47%) of those who had these parameters above threshold (RR = 2.14; 95% CI, 1.25 to 43.68). These amikacin dose-schedule patterns and exposures are virtually the same as those identified in the hollow-fiber system model.