Establishment and validation of a risk prediction model incorporating concentrations of linezolid and its metabolite PNU142300 for linezolid-induced thrombocytopenia.

BACKGROUND: Linezolid-induced thrombocytopenia is the main factor restricting the clinical application of linezolid. OBJECTIVES: To investigate the relationship between PNU-14230 concentration and linezolid-induced thrombocytopenia and further develop and validate a risk model for predicting linezolid-induced thrombocytopenia. METHODS: A regression model was constructed to predict the occurrence of linezolid-induced thrombocytopenia, and further externally validated. The predictive performance was evaluated by receiver operating characteristic curve and Hosmer-Lemeshow test. Linezolid Cmin and PNU-142300 concentrations were compared for different kidney function groups. The Kaplan-Meier method was used to estimate the difference in cumulative incidence of linezolid-induced thrombocytopenia among different kidney function patients. RESULTS: In the derivation (n = 221) and validation (n = 158) cohorts, 28.5% and 24.1% of critically ill patients developed linezolid-induced thrombocytopenia. Logistic regression analysis indicated that the independent risk factors were linezolid Cmin, PNU-142300 concentration, baseline platelet count, renal insufficiency (RI) and continuous venovenous haemofiltration (CVVH). The AUC for the risk model was 0.901, and the model was good (P = 0.633). The model also showed good discrimination (AUC 0.870) and calibration (P = 0.282) in the external validation cohort. Compared with normal kidney function patients, patients with RI and CVVH had higher linezolid Cmin and PNU-142300 concentrations (P < 0.001) and higher cumulative incidence of linezolid-induced thrombocytopenia (P < 0.001). CONCLUSIONS: PNU142300 concentration, as well as linezolid Cmin, might identify patients at risk of linezolid-induced thrombocytopenia. The risk prediction model had good predictive performance for linezolid-induced thrombocytopenia development. Concentrations of linezolid and PNU-142300 accumulated in patients with RI and CVVH.

Dose optimisation of linezolid in critically ill patients based on a population pharmacokinetic model: A two-centre prospective interventional study.

OBJECTIVES: This study evaluated the intervention effect of clinical pharmacist-mediated optimisation of a linezolid regimen using a population pharmacokinetic (PPK) model. METHODS: Patients treated with linezolid in two medical centres from January 2020 to June 2021 were retrospectively included in the control group; those treated from July 2021 to June 2022 were prospectively enrolled in the intervention group. Clinical pharmacists optimised the dosage regimen according to a published linezolid PPK model in the intervention group. An interrupted times series approach was used to analyse the data. The incidence of linezolid-induced thrombocytopenia (LIT), target attainment of pharmacokinetic/pharmacodynamic parameters and other adverse drug reactions (ADRs) were compared between the two groups. RESULTS: In total, 77 and 103 patients were enrolled in the control and intervention groups, respectively. The intervention group had a lower incidence of LIT and other ADRs than the control group (10.7% vs. 23.4%, P = 0.002; 1.0% vs. 7.8%, P = 0.027). The intervention group exhibited a considerably lower trough concentration (Cmin) and area under the concentration-time curve/MIC ratio (AUC24/MIC) (P = 0.001 and P < 0.001). Cmin and AUC24/MIC rates within the target range were substantially higher in the intervention group (49.6% vs. 20.0%, adjusted P < 0.05; 48.1% vs. 25.6%, adjusted P < 0.05). CONCLUSION: Interventions by clinical pharmacists reduced the incidence of LIT and other ADRs. Implementation of model-informed precision dosing (MIPD) for linezolid markedly increased the Cmin and AUC24/MIC rates within the target range. We recommend MIPD-guided linezolid dose reduction for patients with renal impairment.

Dose Optimization of Teicoplanin for Critically Ill Patients With Renal Dysfunction and Continuous Renal Replacement Therapy: Experience From a Prospective Interventional Study.

Background: Due to the lack of updated information on teicoplanin (TEI) for continuous renal replacement therapy (CRRT), no exact dosage regimen has been recommended. The aim of this study was to optimize the dosage regimen of TEI in renal dysfunction patients with or without CRRT, evaluate the influence factors of the eradication of Gram-positive bacteria, and evaluate the effect of CRRT on the clearance of TEI. Methods: Patients with renal dysfunction receiving TEI treatment in the ICU were prospectively recruited and divided into CRRT and non-CRRT groups. Logistic regression analysis was used to screen the factors affecting the eradication of Gram-positive bacteria. The filtrate concentration of the CRRT group was measured at the time of TEI Cmin, and the filtration coefficient of TEI was calculated to evaluate the effect of CRRT on the clearance of TEI. Results: A total of 106 patients were included, 40 cases in the CRRT group and 66 cases in the non-CRRT group. After giving high-loading doses of TEI, 75.8 and 70% of TEI Cmin in the non-CRRT and CRRT groups reached the range of 10-30 mg/L before the 3rd dose, respectively. The risk of G+ bacteria being uneradicated was higher while the APACHEⅡscore was higher than 22.5. The albumin level before the start of TEI administration and before the 6th-8th dose was lower than 32.8 g/L and 29.3 g/L, respectively, and Cmin before the 3rd dose and 6th-8th dose was lower than 13.2 mg/L and 17.1 mg/L, respectively, with the duration of TEI therapy shorter than 10.5 days. The correlation coefficient (r) was 0.6490 between Cmin before the 3rd dose and the albumin level (p < 0.001). The filtration coefficient of TEI was 10.7 ± 2.4% at Cmin and 11.1 ± 2.5% at Cmax. The GFR had no correlation with the filtration coefficient (r = -0.06204; r = -0.08059). The clearance of TEI in CRRT patients was negatively correlated with the albumin level (r = -0.6305, p = 0.0013). Conclusion: The early stage of the albumin level can significantly affect the initial Cmin and clinical efficacy of TEI, and also had effect on the clearance of TEI by CRRT. The filtration coefficient of TEI was stable, even with a higher ultrafiltration rate.