Surgical infections · 2025
Analysis of Linezolid Blood Concentration and Prediction Modeling of Thrombocytopenia in Orthopedic Patients.
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Xu Tiantian, Hu Lianqi, Qi Qihua, Kong Ying, Lai Fengjun, Xin Yue, Peng Hongwei, Zhu Meisong
Аннотация
OBJECTIVE: To analyze the clinical outcomes of linezolid (LZD) blood concentration monitoring in the orthopedic department of our hospital, to explore the risk factors associated with thrombocytopenia caused by LZD, and to establish a prediction model.
METHODS: We retrospectively analyzed orthopedic patients treated with LZD at the First Affiliated Hospital of Nanchang University from January 2021 to December 2024. Eligible patients had concentration testing and complete platelet count data. Univariate and multivariate logistic regression were used to identify risk factors for thrombocytopenia. A nomogram was developed on the basis of independent predictors to predict the probability of thrombocytopenia.
RESULTS: 117 patients were enrolled, of which 18 were evaluated for linezolid-induced thrombocytopenia (LIT). Univariate analysis revealed that age, red blood cell count, albumin, creatinine clearance, and LZD trough concentration were statistically significant in relation to LIT; multifactorial logistic regression analysis indicated that the LZD trough concentration was strongly associated with LIT. On the basis of these risk factors, a nomogram was established using R software, and the area under the curve of the receiver operating characteristic for the subjects in the modeling group was 0.884 (95% confidence interval: 0.800, 0.969). According to the nomogram results, the predicted values of the calibration curves were largely consistent with the actual values.
CONCLUSION: Age, albumin, red blood cell count, LZD trough concentration, and creatinine clearance are all good predictors of LIT. The construction of a nomogram to predict the risk of LIT has greater clinical value, which can be used to guide individualized treatment in the clinical setting.
METHODS: We retrospectively analyzed orthopedic patients treated with LZD at the First Affiliated Hospital of Nanchang University from January 2021 to December 2024. Eligible patients had concentration testing and complete platelet count data. Univariate and multivariate logistic regression were used to identify risk factors for thrombocytopenia. A nomogram was developed on the basis of independent predictors to predict the probability of thrombocytopenia.
RESULTS: 117 patients were enrolled, of which 18 were evaluated for linezolid-induced thrombocytopenia (LIT). Univariate analysis revealed that age, red blood cell count, albumin, creatinine clearance, and LZD trough concentration were statistically significant in relation to LIT; multifactorial logistic regression analysis indicated that the LZD trough concentration was strongly associated with LIT. On the basis of these risk factors, a nomogram was established using R software, and the area under the curve of the receiver operating characteristic for the subjects in the modeling group was 0.884 (95% confidence interval: 0.800, 0.969). According to the nomogram results, the predicted values of the calibration curves were largely consistent with the actual values.
CONCLUSION: Age, albumin, red blood cell count, LZD trough concentration, and creatinine clearance are all good predictors of LIT. The construction of a nomogram to predict the risk of LIT has greater clinical value, which can be used to guide individualized treatment in the clinical setting.