Zhao Hengyu, Xu Zhibin, Wang Xiaohua, Xu Yu, Lu Yi, Chen Jiaqi, Ye Qiaoyu, Li Xuan, Wen Yanhua, Ju Chunrong
State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China.
Department of Scientific Affaires, Hugobiotech Co., Ltd., Beijing, People's Republic of China.
Infect Drug Resist. 2025 Sep 2;18:4527-4537. doi: 10.2147/IDR.S536103. eCollection 2025.
Nocardiosis is an opportunistic infection in lung transplant recipients but is often misdiagnosed or overlooked. This study aimed to identify risk factors and develop an effective predictive model for nocardiosis in this population.
This single-center retrospective study analyzed 679 lung transplant recipients from January 1, 2015, to July 9, 2024. Twenty patients with nocardiosis were compared with 40 matched controls. Feature selection was performed using LASSO regression, and logistic regression identified risk factors. Model performance was assessed via ROC curves, calibration curves, and decision curve analysis.
Decreased CD4 T cells, elevated CD8 T cells, and reduced IgA levels were significantly associated with nocardiosis (P < 0.05). The model incorporating these factors demonstrated strong predictive ability with an area under the ROC curve of 0.955.
CD4 T cells, CD8 T cells, and IgA are independent risk factors for nocardiosis post-lung transplantation. The developed model effectively distinguishes nocardiosis cases, aiding early clinical identification.
诺卡菌病是肺移植受者中的一种机会性感染，但常被误诊或忽视。本研究旨在确定该人群中诺卡菌病的危险因素并建立有效的预测模型。
本单中心回顾性研究分析了2015年1月1日至2024年7月9日期间的679例肺移植受者。将20例诺卡菌病患者与40例匹配的对照进行比较。使用LASSO回归进行特征选择，并通过逻辑回归确定危险因素。通过ROC曲线、校准曲线和决策曲线分析评估模型性能。
CD4 T细胞减少、CD8 T细胞升高和IgA水平降低与诺卡菌病显著相关（P < 0.05）。纳入这些因素的模型显示出较强的预测能力，ROC曲线下面积为0.955。
CD4 T细胞、CD8 T细胞和IgA是肺移植后诺卡菌病的独立危险因素。所建立的模型能有效区分诺卡菌病病例，有助于早期临床识别。
