Management of Mycobacterium bovis Meningitis: The Case for Adjunctive Empirical Therapy
Abstract
Tuberculous meningitis is a devastating manifestation of tuberculosis, disproportionately affecting children and persons with HIV. Despite decades of clinical experience, diagnosis is often delayed and outcomes remain poor. At the US-Mexico border, management is further complicated by the high prevalence of Mycobacterium bovis, a member of the Mycobacterium tuberculosis complex intrinsically resistant to pyrazinamide, one of the few first-line agents with reliable central nervous system penetration. We present a case of M. bovis meningitis in a patient residing near the US-Mexico border, highlighting the diagnostic and therapeutic challenges posed by intrinsic pyrazinamide resistance. Drawing from this case, we review evidence supporting the early use of adjunctive CNS-penetrative antimicrobials during suspected tuberculosis meningitis in regions where M. bovis is endemic.
How strong is the evidence?
Evidence Hub reads this as a case report, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Ferulic acid regulates the AKT/GSK-3β/CRMP-2 signaling pathway in a middle cerebral artery occlusion animal model
- Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure–Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli
- Photochemical behavior of levofloxacin
- Correlation Between Dissolution Profiles of Salt-Form Drugs in Biorelevant Bicarbonate Buffer and Oral Drug Absorption: Importance of Dose/ Fluid Volume Ratio
- Evaluation of the synergistic potential and mechanisms of action for de novo designed cationic antimicrobial peptides
- Synthesis of [11C]levofloxacin
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.