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

Author:

Xu Jinhui1,Lu Jian2,Yuan Yunlong3,Duan Lufen1,Shi Lu1,Chen Fang1,Cao Yifei4,Xu Guangjuan1,Feng Zongtai5,Li Lan1,Xue Hongzhi1,Sun Jiantong1,Zhou Qin1,Zhuang Zhiwei4,Tang Lian1

Affiliation:

1. Department of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital , No. 26 Daoqian Street, Gusu District, Jiangsu 215002, Suzhou , China

2. Intensive Care Unit, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital , Suzhou , China

3. Medical Laboratory, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital , Suzhou , China

4. Emergency Intensive Care Unit, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital , Suzhou , China

5. Gusu School, Nanjing Medical University, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital , Suzhou , China

Abstract

Abstract 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.

Funder

Suzhou Science and Technology Project

Jiangsu Pharmaceutical Association

Hospital Pharmacy Research Project

Jiangsu Research Hospital Association for Precision Medication

Wu Jieping Medical Foundation

Gusu Talent Program

Collaborative Innovation Project of Gusu School of Nanjing Medical University

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Pharmacology (medical),Pharmacology,Microbiology (medical)

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