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中国防痨杂志 ›› 2025, Vol. 47 ›› Issue (8): 1038-1043.doi: 10.19982/j.issn.1000-6621.20250064

• 论著 • 上一篇    下一篇

初治重症肺结核患者早期危险因素分析及预测模型的构建

薛玉1, 郭树彬2, 雷轩1, 张静1, 李文胜1, 刘岩1, 李欢1, 刘志峰1, 王伟3(), 文力1()   

  1. 1首都医科大学附属北京胸科医院急诊科,北京101149
    2首都医科大学附属北京朝阳医院急诊科,北京100020
    3首都医科大学附属北京胸科医院国家结核病临床实验室,北京101149
  • 收稿日期:2025-02-24 出版日期:2025-08-10 发布日期:2025-08-01
  • 通信作者: 文力,Email: drli1025@163.com; 王伟,Email: wangwei010@aliyun.com

Construction and analysis of early warning and prediction model for risk factors of initially treated severe pulmonary tuberculosis

Xue Yu1, Guo Shubin2, Lei Xuan1, Zhang Jing1, Li Wensheng1, Liu Yan1, Li Huan1, Liu Zhifeng1, Wang Wei3(), Wen Li1()   

  1. 1Department of Emergency, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
    2Department of Emergency, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China
    3National Clinical Laboratory on Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
  • Received:2025-02-24 Online:2025-08-10 Published:2025-08-01
  • Contact: Wen Li, Email: drli1025@163.com; Wang Wei, Email: wangwei010@aliyun.com

摘要:

目的: 探索初治重症肺结核患者的流行病学特点,分析发生重症的危险因素,为临床早期识别初治重症肺结核患者并改善预后提供依据。方法: 选取2024年1—6月首都医科大学附属北京胸科医院收治的217例初治肺结核患者作为研究对象,根据重症肺结核诊断标准分为初治重症组(107例)和初治非重症组(110例)。收集研究对象一般人口学信息、基础疾病、实验室检查结果、细菌学检测结果等资料。比较两组间各项指标的差异,采用多因素logistic回归模型分析初次诊断尚未开始治疗即发生重症肺结核的危险因素,并建立风险预测模型,绘制受试者工作特征(receiver operator characteristic, ROC)曲线,分析此模型对初治重症肺结核患者的预测价值。结果: 多因素logistic回归分析显示,心率、白蛋白、中性粒细胞与淋巴细胞比值、血钠、呼吸窘迫为初治肺结核患者发生重症的独立影响因素。心率增快(OR=1.205,95%CI:1.010~1.436)、中性粒细胞与淋巴细胞比值增加(OR=2.247,95%CI:1.133~4.455)和发生呼吸窘迫(OR=26.899,95%CI:1.713~289.780),肺结核患者出现重症的风险增加;白蛋白水平升高(OR=0.487,95%CI:0.270~0.876)和血钠水平升高(OR=0.489,95%CI:0.257~0.928),肺结核患者出现重症的风险降低。ROC曲线分析显示,5种因素联合检测时曲线下面积为0.995,预测初治重症肺结核患者的敏感度和特异度分别为96.2%和98.2%。结论: 心率、呼吸窘迫、白蛋白、中性粒细胞与淋巴细胞比值、血钠为初治肺结核患者发生重症的影响因素,且五者联合对初治重症肺结核患者的早期筛查和预防具有良好的预测价值。

关键词: 危重病, 结核, 肺, 因素分析, 统计学, 模型, 结构

Abstract:

Objective: To investigate the epidemiological characteristics of initially treated severe pulmonary tuberculosis, analyze its risk factors and establish a prediction model, which provides evidence for early clinical identification of initially treated severe pulmonary tuberculosis and improvement of clinical outcomes. Methods: A total of 217 patients with initially treated pulmonary tuberculosis admitted to Beijing Chest Hospital, Capital Medical University, between January 2024 to June 2024 were divided into two groups according to the diagnostic criteria for severe pulmonary tuberculosis: the initially treated severe group (107 patients) and the initially treated non-severe group (110 patients). The information including baseline data, basic diseases, laboratory tests and bacteriological evidence was retrospectively collected. The differences in clinical data between two groups were compared. Multivariate logistic regression analysis was performed to analyze the risk factors for severe pulmonary tuberculosis before treatment initiation, establish the risk prediction model and plot a receiver operator characteristic (ROC) curve to evaluate the predictive value of this model for initially treated severe tuberculosis patients. Results: Multivariate logistic regression analysis showed that heart rate, albumin, neutrophile-lymphocyte ratio (NLR), sodium, respiratory distress were independent risk factors for the initial treated severe pulmonary tuberculosis. An increased heart rate was associated with an increased risk of severe pulmonary tuberculosis (OR=1.205, 95%CI: 1.010-1.436). An increase in the ratio of NLR significantly increased the risk of disease (OR=2.247, 95%CI: 1.133-4.455). Respiratory distress was the strongest risk factor, with an OR as high as 26.899 (95%CI: 1.713-289.780). Higher albumin levels were associated with a reduced risk of severe disease (OR=0.487, 95%CI: 0.270-0.876), as were higher blood sodium levels (OR=0.489, 95%CI: 0.257-0.928). ROC curve analysis showed that the area under the curve was 0.995 when the five risk factors were combined, and the sensitivity and specificity of predicting the initial severe pulmonary tuberculosis were 96.2% and 98.2%, respectively. Conclusion: Heart rate, respiratory distress, albumin, NLR, sodium were independent risk factors for the initial treatment severe pulmonary tuberculosis. Moreover, the combination of these five factors can effectively predict the occur of severe pulmonary tuberculosis.

Key words: Critical illness, Tuberculosis, pulmonary, Factor analysis, statistical, Models, structural

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