Update of SEPAR guideline «Diagnosis and Treatment of Drug-Resistant Tuberculosis».
Abstract
Abstract New evidence and knowledge about the clinical management of drug-resistant tuberculosis (TB) in the last 3 years, makes it necessary to update the recent guideline published by SEPAR in 2017, mainly in relation to new diagnostic methods, drug classification, and regimens of treatment recommended to treat patients with isoniazid-resistance TB, rifampicin resistance TB and multidrug-resistant TB. With respect to tuberculosis diagnosis, we recommend the use of rapid molecular assays that also help to detect mutations associated with resistance. In relation to the treatment of multidrug-resistant TB we prioritize effective all-oral shorter treatment regimens including bedaquiline, a fluoroquinolone (levofloxacin or moxifloxacin), bedaquiline and linezolid, instead of the previously recommended short-course treatment with aminoglycosides and other less effective and more toxic drugs. The design of these regimens (initial schedule and changes in the regimen if necessary) should be made in accordance with drug-resistant TB experts; the treatment should be the responsibility of personnel with experience in the treatment of TB and in TB units guaranteeing the follow-up of the treatment and the management of drugs adverse effects.
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.