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

Author:

Modongo Chawangwa,Pasipanodya Jotam G.,Magazi Beki T.,Srivastava Shashikant,Zetola Nicola M.,Williams Scott M.,Sirugo Giorgio,Gumbo Tawanda

Abstract

ABSTRACTAminoglycosides 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,Cmaxof <67 mg/liter and AUC0–24of <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 R2= 0.90 on posttest. In patients weighing >41 kg, sputum conversion was 3/3 (100%) in those with an amikacinCmaxof ≥67 mg/liter versus 3/15 (20%) in those with aCmaxof <67 mg/liter (relative risk [RR] = 5.00; 95% confidence interval [CI], 1.82 to 13.76). In all patients who had both amikacinCmaxand AUC0–24below 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.

Funder

HHS | National Institutes of Health (NIH)

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Pharmacology (medical),Pharmacology

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