目的 探讨耐多药肺结核患者发生利奈唑胺相关神经系统不良反应的影响因素，构建神经系统不良反应风险预测模型。 方法 采用前瞻性队列研究方法，选取广州市胸科医院2023年4月至2024年1月含利奈唑胺化疗方案治疗的耐药肺结核患者作为研究对象，共120例，收集患者的临床资料、不良反应及空腹、服药后2 h的利奈唑胺血药浓度。采用单因素分析和多因素logistic回归分析利奈唑胺相关神经系统不良反应的影响因素，并构建利奈唑胺相关神经系统不良反应预测模型，采用ROC评价该模型的预测效能及校准能力。 结果 复治（OR = 2.540，P = 0.028）、合并空洞（OR = 4.092，P = 0.021）、贫血（OR = 10.921，P = 0.005）、C_min ≥ 0.766 5 mg/L（OR = 6.813，P < 0.001）是发生利奈唑胺相关神经系统不良反应的独立危险因素，基于以上4个因素建立的预测模型AUC为0.851（95% CI：0.774 ~ 0.929），约登指数为0.590时，其敏感度为66.7%，特异度为92.3%，预测模型有较好的校准能力（Hosmer-lemeshow χ² = 8.719， P = 0.273）。 结论 C_min ≥ 0.766 5 mg /L、合并空洞、复治、贫血的MDR/RR-TB患者发生利奈唑胺相关神经系统不良反应的风险可能较高，基于上述4个指标构建的风险预测模型对利奈唑胺相关神经系统不良反应发生具有较高的预测价值。

Objective To investigate the determinants of linezolid-associated neurological adverse reactions in patients with multidrug-resistant tuberculosis and develop a risk prediction model for such adverse events. Methods A prospective cohort study design was employed to select 120 patients with drug-resistant pulmonary tuberculosis who received a chemotherapy regimen containing linezolid at Guangzhou Chest Hospital from April 2023 to January 2024 as the study population. Clinical data， adverse reactions， and plasma concentration of linezolid were collected during fasting and at 2 hours post-medication. Univariate analysis and multivariate logistic regression were conducted to identify factors influencing linezolid-related neurological adverse reactions. Furthermore， a prediction model for such adverse reactions was developed， and its predictive efficacy and calibration ability were evaluated using ROC analysis. Results Re-treatment（OR = 2.540，P =0.028）， coexistence of cavities （OR = 4.092，P =0.021）， anemia （OR = 10.921，P = 0.005）， and C_min ≥ 0.7665 mg/L （OR = 6.813，P < 0.001） are independent risk factors for the occurrence of linezolid-related neurological adverse reactions. The prediction model， based on these four factors， exhibits an AUC of 0.851 （95% CI：0.774 ~ 0.929）， accompanied by a Youden index of 0.590， a sensitivity of 66.7%， and a specificity of 92.3%. Moreover， the prediction model demonstrates excellent calibration ability. （Hosmer-lemeshow χ² = 8.719， P = 0.273）. Conclusion In MDR/RR-TB patients， the presence of cavitation， retreatment， and anemia may confer a heightened risk of linezolid-related neurological adverse reactions. A risk prediction model incorporating these four indicators demonstrates significant predictive value for the occurrence of such adverse events.