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Purpose: The purpose of this retrospective observational study conducted in patients with hepatic impairment was to assess the variability of linezolid trough concentrations, to determine the risk factors for linezolid overexposure, and to investigate the effect of linezolid overexposure on linezolid-induced thrombocytopenia. Methods: All enrolled patients received a standard dose (600 mg every 12 h) of linezolid and underwent therapeutic drug monitoring. The Child–Pugh-Turcotte score was used to divide patients into three groups: mild, moderate, and severe hepatic impairment. The risk factors for linezolid overexposure (Cmin > 8 mg/L) and linezolid-induced thrombocytopenia were examined using logistic regression. And the Kaplan–Meier curve was used to describe the association between linezolid overexposure and linezolid-induced thrombocytopenia. Results: Seventy-seven patients were included, 37 (48.1%) of whom experienced linezolid overexposure. Patients with severe hepatic impairment had a substantially higher median Cmin of linezolid than those with mild (20.7 mg/L vs 5.51 mg/L, P < 0.001) or moderate (20.7 mg/L vs 6.70 mg/L, P = 0.001) hepatic impairment. Severe hepatic impairment was significantly associated with linezolid overexposure (OR 7.037, 95%CI 1.426–34.727, P = 0.017). After linezolid treatment, linezolid-induced thrombocytopenia occurred in 32 (41.6%) patients, and Cmin > 8 mg/L was a significant predictor of linezolid-induced thrombocytopenia (OR 3.024, 95%CI 1.083–8.541, P = 0.035). Conclusion: Patients with hepatic impairment who received standard doses of linezolid are at greater risk of linezolid overexposure, which may lead to a higher incidence of linezolid-induced thrombocytopenia. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment and to explore a method to predict linezolid exposure.Patients with hepatic impairment who received linezolid were recruited. A population pharmacokinetic model (PPK) was then built using NONMEM software. And based on the final model, virtual patients with rich concentration values was constructed through Monte Carlo simulations (MCS), which were used to build machine learning (ML) models to predict linezolid exposure levels. Finally, we investigated the risk factors for thrombocytopenia in patients included.A PPK model with population typical values of 3.83 L/h and 34.1 L for clearance and volume of distribution was established, and the severe hepatic impairment was identified as a significant covariate of clearance. Then, we built a series of ML models to predict the area under 0 -24 h concentration-time curve (AUC0-24) of linezolid based on virtual patients from MCS. The results showed that the Xgboost models showed the best predictive performance and were superior to the methods for estimating linezolid AUC0-24 based on though concentration or daily dose. Finally, we found that baseline platelet count, linezolid AUC0-24, and combination with fluoroquinolones were independent risk factors for thrombocytopenia, and based on this, we proposed a method for calculating the toxicity threshold of linezolid.In this study, we successfully constructed a PPK model for patients with hepatic impairment and used ML algorithm to estimate linezolid AUC0-24 based on limited data. Finally, we provided a method to determine the toxicity threshold of linezolid.Methods: To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment and to explore a method to predict linezolid exposure.Patients with hepatic impairment who received linezolid were recruited. A population pharmacokinetic model (PPK) was then built using NONMEM software. And based on the final model, virtual patients with rich concentration values was constructed through Monte Carlo simulations (MCS), which were used to build machine learning (ML) models to predict linezolid exposure levels. Finally, we investigated the risk factors for thrombocytopenia in patients included.A PPK model with population typical values of 3.83 L/h and 34.1 L for clearance and volume of distribution was established, and the severe hepatic impairment was identified as a significant covariate of clearance. Then, we built a series of ML models to predict the area under 0 -24 h concentration-time curve (AUC0-24) of linezolid based on virtual patients from MCS. The results showed that the Xgboost models showed the best predictive performance and were superior to the methods for estimating linezolid AUC0-24 based on though concentration or daily dose. Finally, we found that baseline platelet count, linezolid AUC0-24, and combination with fluoroquinolones were independent risk factors for thrombocytopenia, and based on this, we proposed a method for calculating the toxicity threshold of linezolid.In this study, we successfully constructed a PPK model for patients with hepatic impairment and used ML algorithm to estimate linezolid AUC0-24 based on limited data. Finally, we provided a method to determine the toxicity threshold of linezolid.Results: To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment and to explore a method to predict linezolid exposure.Patients with hepatic impairment who received linezolid were recruited. A population pharmacokinetic model (PPK) was then built using NONMEM software. And based on the final model, virtual patients with rich concentration values was constructed through Monte Carlo simulations (MCS), which were used to build machine learning (ML) models to predict linezolid exposure levels. Finally, we investigated the risk factors for thrombocytopenia in patients included.A PPK model with population typical values of 3.83 L/h and 34.1 L for clearance and volume of distribution was established, and the severe hepatic impairment was identified as a significant covariate of clearance. Then, we built a series of ML models to predict the area under 0 -24 h concentration-time curve (AUC0-24) of linezolid based on virtual patients from MCS. The results showed that the Xgboost models showed the best predictive performance and were superior to the methods for estimating linezolid AUC0-24 based on though concentration or daily dose. Finally, we found that baseline platelet count, linezolid AUC0-24, and combination with fluoroquinolones were independent risk factors for thrombocytopenia, and based on this, we proposed a method for calculating the toxicity threshold of linezolid.In this study, we successfully constructed a PPK model for patients with hepatic impairment and used ML algorithm to estimate linezolid AUC0-24 based on limited data. Finally, we provided a method to determine the toxicity threshold of linezolid.Conclusion: To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment and to explore a method to predict linezolid exposure.Patients with hepatic impairment who received linezolid were recruited. A population pharmacokinetic model (PPK) was then built using NONMEM software. And based on the final model, virtual patients with rich concentration values was constructed through Monte Carlo simulations (MCS), which were used to build machine learning (ML) models to predict linezolid exposure levels. Finally, we investigated the risk factors for thrombocytopenia in patients included.A PPK model with population typical values of 3.83 L/h and 34.1 L for clearance and volume of distribution was established, and the severe hepatic impairment was identified as a significant covariate of clearance. Then, we built a series of ML models to predict the area under 0 -24 h concentration-time curve (AUC0-24) of linezolid based on virtual patients from MCS. The results showed that the Xgboost models showed the best predictive performance and were superior to the methods for estimating linezolid AUC0-24 based on though concentration or daily dose. Finally, we found that baseline platelet count, linezolid AUC0-24, and combination with fluoroquinolones were independent risk factors for thrombocytopenia, and based on this, we proposed a method for calculating the toxicity threshold of linezolid.In this study, we successfully constructed a PPK model for patients with hepatic impairment and used ML algorithm to estimate linezolid AUC0-24 based on limited data. Finally, we provided a method to determine the toxicity threshold of linezolid. [ABSTRACT FROM AUTHOR]

Purpose: The substantial variability in the antiplatelet efficacy of clopidogrel has raised major concerns. Molecular epidemiological research suggests that ABCB1 C3435T polymorphism may be associated with clopidogrel response, but results remain controversial. To derive a more precise evaluation of the associations between ABCB1 C3435T polymorphism and the clinical efficacy of clopidogrel, we have conducted a PRISMA-compliant meta-analysis. Methods: The PubMed and EMBASE databases were searched for eligible studies up to 25 October 2016. The odds ratio (OR), the standard mean difference (SMD) and 95% confidence interval (CI) were applied to assess the strength of the relationship. Results: Overall, 28 related studies involving 23,243 patients were analyzed. No association was found between the ABCB1 polymorphisms and the primary outcome. In the subgroup analysis, the C3435T mutation significantly reduced platelet activity as tested by the LTA assay in the dominant (SMD −0.140, 95% CI −0.272 to −0.009, P = 0.036) and heterozygous (SMD −0.154, 95% CI −0.290 to −0.017, P = 0.027) models, but the result lacked robustness in the sensitivity analysis. A significant association between the C3435T polymorphism and bleeding risk was also observed with low heterogeneity in the dominant (OR 1.805, 95% CI1.124-2.900, P =0.015, I = 0%), homozygous (OR 1.952, 95% CI 1.055-3.611, P = 0.033, I = 13.2%) and heterozygous (OR 1.793, 95% CI 1.091-2.946, P = 0.021, I = 0%) models in Asian patients. Conclusions: The results of the meta-analysis suggest that ABCB1 C3435T polymorphism may increase the risk of bleeding in Asian patients treated with clopidogrel. The implied relationship needs to be verified in future basic genetic pharmacology studies. [ABSTRACT FROM AUTHOR]

Purpose: The optimal therapy involving linezolid or vancomycin for suspected methicillin-resistant Staphylococcus aureus (MRSA) nosocomial pneumonia (NP) remains controversial. This study compared the efficacy and safety of linezolid and vancomycin therapies in patients with NP. Methods: A systematic review of randomized controlled trials with meta-analyses performed by searching PubMed, EMBASE, MEDLINE, and the Cochrane Central Register of Controlled Trials. We screened for relevant randomized controlled studies in which patients with NP were enrolled and linezolid and vancomycin therapies were compared. Results: Nine trials involving 2618 pneumonia patients were reviewed. Linezolid was not found to be superior to vancomycin for clinical cure when categories of pathogen were not considered and in a subgroup of NP patients with MRSA infection [relative risk (RR) = 1.16, 95 % confidence interval (CI) = 0.95-1.43, P = 0.15]. Compared with vancomycin, linezolid has no difference in the overall microbiological eradication rate (RR = 1.12, 95 % CI = 0.96-1.30, P = 0.15) and specific MRSA eradication rate (RR = 1.16, 95 % CI = 0.93-1.45, P = 0.19) in NP patients. In addition, nephrotoxicity was more frequent with vancomycin (RR = 0.50, 95 % CI = 0.31-0.81, P = 0.005), but no differences between the treatments were found for all-cause mortality, thrombocytopenia, gastrointestinal effects, and drug discontinuation due to adverse events. Conclusion: These results suggest that linezolid is not superior to vancomycin with respect to both clinical and microbiological cure rates in patients with MRSA NP. [ABSTRACT FROM AUTHOR]