Plasma Concentrations of Contezolid and Its Efficacy and Safety in Elderly Patients with Multidrug-Resistant Tuberculosis and Renal Insufficiency.
Xiaoqing MaRuoying ZhangXinjun CaiYuying LangHuaichong WangJinmeng LiPublished in: Infection and drug resistance (2024)
As a new generation of oxazolidinone antibacterial drugs, contezolid has been shown to have comparable or even stronger activity than linezolid and has a low risk of adverse reactions such as bone marrow suppression toxicity. However, there are currently very few clinical reports and pharmacokinetic data of contezolid on the anti-tuberculosis therapy. Therefore, we report a case study of the pharmacokinetic study of contezolid in elderly patients with renal insufficiency and tuberculosis. The patient's condition improved after receiving an anti-tuberculosis regimen containing contezolid, with significant absorption of pleural effusion and lung plaques and nodules reduced. During the treatment, the patients' platelet and white blood cell levels fluctuated within normal ranges, but hemoglobin levels significantly decreased and did not recover after discontinuation of contezolid. The trough concentration of contezolid and the concentration at 2, 4, 6, and 10 h after administration were 1.27µg/mL, 3.88µg/mL, 6.32µg/mL, 8.99µg/mL, and 3.14µg/mL, respectively. The plasma concentrations of bedaquiline and cycloserine during the treatment were also monitored. This study demonstrated the efficacy and safety of contezolid in the treatment of multidrug-resistant tuberculosis and analyzed its pharmacokinetic changes in elderly patients with renal insufficiency, providing a reference for the clinical use of contezolid.
Keyphrases
- multidrug resistant
- mycobacterium tuberculosis
- bone marrow
- pulmonary tuberculosis
- hiv aids
- drug resistant
- adverse drug
- emergency department
- middle aged
- end stage renal disease
- acinetobacter baumannii
- newly diagnosed
- stem cells
- mesenchymal stem cells
- ejection fraction
- community dwelling
- single cell
- cystic fibrosis
- big data
- pseudomonas aeruginosa
- machine learning
- methicillin resistant staphylococcus aureus
- red blood cell