Management of complex tuberculosis cases: a focus on drug-resistant tuberculous meningitis
Abstract
Drug-resistant tuberculous meningitis has been reported worldwide. Isoniazid mono-resistance is the most frequent cause of drug-resistant tuberculous meningitis, a life-threatening disease. Extensive drug-resistant tuberculous meningitis has also been reported in some isolated case reports. Areas covered: We reviewed the current literature on drug-resistant tuberculous meningitis, as well as drug-resistant tuberculosis. Expert commentary: Drug-resistant tuberculous meningitis is a life-threatening disease and needs prompt diagnosis and treatment. Xpert MTB/RIF Ultra technology can detect Mycobacterium tuberculosis and rifampicin resistance in cerebrospinal fluid (CSF) even with low numbers of bacilli. The optimum antituberculosis drug regimen for multidrug-resistant tuberculous meningitis is largely unknown as no second-line antituberculosis drug-containing regimen has been tested in a randomized controlled fashion in drug-resistant tuberculous meningitis. A combination of levofloxacin, kanamycin, ethionamide, linezolid, and pyrazinamide would be an appropriate regimen because of excellent CSF profile of most of these drugs. End TB Strategy will help in checking the increasing challenge of drug-resistant tuberculous meningitis as it aims to eliminate all kinds of tuberculosis by the year 2035.
Read the paper
Related studies
- Pharmacokinetic aspects of retinal drug delivery
- A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis
- From Therapeutic Drug Monitoring to Model‐Informed Precision Dosing for Antibiotics
- Capsaicin, a novel inhibitor of the NorA efflux pump, reduces the intracellular invasion of Staphylococcus aureus
- In Vitro Pharmacodynamic Evaluation of the Mutant Selection Window Hypothesis Using Four Fluoroquinolones against Staphylococcus aureus
- Discovery of Potent, Selective Multidrug and Toxin Extrusion Transporter 1 (MATE1, SLC47A1) Inhibitors Through Prescription Drug Profiling and Computational Modeling
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.