OBJECTIVE To investigate the risk factors for exceeding the threshold of therapeutic drug monitoring(TDM) with linezolid and construct a visual model for predicting the risk of exceeding the threshold, in order to optimize personalized clinical use of linezolid.

METHODS According to the inclusion and exclusion criteria, hospitalized patients treated with linezolid in Zhongshan Hospital Affiliated with Xiamen University from June 2023 to October 2024 were screened and subjected to TDM. The plasma drug concentration was detected using HPLC. Patients with a concentration range of 2−8 mg·L⁻¹ were classified as the standard group, and patients with a concentration of ≥ 8 mg·L⁻¹ were classified as the over threshold group. Clinical data of two patient groups were collected, including age, gender, height, weight, underlying diseases, medication use, relevant supportive treatment, inflammatory indicators, blood routine, liver and kidney function, etc. Univariate analysis and multivariate analysis were employed to screen and identify feature predictive variables, and a column chart model was constructed. Receiver operating characteristic(ROC) curves, calibration curves, decision curves and clinical impact curves were used to evaluate the nomogram model, and clinical practice cases were listed.

RESULTS A total of 180 patients(282 TDMs) were included in this study. The standard group had 153 TDMs(109 for males and 44 for females), while the over threshold group had 129 TDMs(87 for males and 42 for females). Multivariate analysis showed that age(OR=1.052, 95% CI: 1.026−1.078), hemoglobin(OR=0.965, 95% CI: 0.934−0.998), and hypoalbuminemia(OR=2.440, 95% CI: 1.192−4.996) were independent risk factors for exceeding the TDM threshold of linezolid. Based on the independent risk factors mentioned above, a nomogram model was constructed, and the results showed that the AUC of the ROC curve was 0.7721(95% CI: 0.718−0.826). The calibration curve results showed that the predicted values of the model fit well with the actual results(Bootstrap self sampling method repeated 1000 times, with an average absolute error of 0.015), indicating the good reliability and specificity of the column chart model. The results of the model decision curve analysis indicated that predicting linezolid TDM exceeding the threshold had a high net benefit. Clinical practice cases showed that the prediction success rate reached 80.00%.

CONCLUSION The TDM exceeding the threshold risk prediction model for linezolid constructed in this study has good reliability and clinical applicability, which can help quickly identify high-risk patients in clinical practice and provide scientific basis for the rapid development of individualized linezolid administration plans.