肺结核合并呼吸衰竭患者死亡风险预测模型的构建研究

doi:10.19871/j.cnki.xfcrbzz.2024.01.006

摘要/Abstract

摘要： 目的分析影响肺结核继发呼吸衰竭患者院内死亡的主要临床危险因素,并构建定量风险预测模型,为临床实践提供参考依据。方法选取2019年3月至2022年6月入住南京医科大学康达学院附属丹阳医院确诊肺结核继发呼吸衰竭患者共105例,根据临床结局分为存活组75例（71.4%）和死亡组30例（28.6%）。分析两组患者一般临床资料,包括性别、年龄、痰涂片阳性率、痰培养阳性率、结核分枝杆菌利福平耐药实时荧光定量核酸扩增检测阳性率、合并疾病、并发症、结核分型、入院肺功能（用力肺活量、潮气量、残气量）、入院动脉血气分析[动脉血氧分压（PaO₂）、二氧化碳分压（PaCO₂）、氧饱和度（SaO₂）、PaO₂/FiO₂]、入院血清C反应蛋白（C-reactive protein,CRP）、白细胞计数、中性粒细胞/淋巴细胞比值（neutrophil/lymphocyte ratio,NLR）、平均动脉压（mean arterial pressure,MAP）、白蛋白及入院急性生理与慢性健康Ⅱ评分（acute physiology and chronic health evaluationⅡ,APACHEⅡ评分）;采用多因素Logistic回归分析筛选可能影响死亡结局的主要危险因素,构建风险预测模型,最后采用受试者操作特征曲线（receiver operator characteristic curve,ROC曲线）评估其诊断效能。结果死亡组较存活组并发症发生率增加,入院用力肺活量降低、PaO₂/FiO₂降低、NLR升高、白蛋白降低（P<0.05）;死亡组细菌耐药率和有创通气率增加,通气时间延长,治疗3d后PaO₂/FiO₂降低,APACHEⅡ评分升高,CRP和NLR升高,白蛋白降低（均P<0.05）。多因素Logistic回归分析得出,PaO₂/FiO₂、NLR、白蛋白、治疗3d后APACHEⅡ评分和CRP是影响死亡结局的主要危险因素（P<0.05）。构建风险预测模型Y=2.563-0.248×PaO₂/FiO₂+0.166×NLR-0.318×白蛋白-0.074×APACHEⅡ评分+0.396×CRP。ROC曲线分析得出Y值预测死亡的准确性为0.856,敏感度82.6%,特异度75.5%,临界值为0.869。结论肺结核继发呼吸衰竭有较高的院内病死率,入院PaO₂/FiO₂和白蛋白降低以及入院NLR、治疗3d后APACHEⅡ评分和CRP升高可能是影响死亡结局的主要危险因素,构建定量预测模型评估死亡风险有较好的准确性和应用价值。

关键词: 肺结核, 呼吸衰竭, 死亡, 危险因素, 风险预测模型

Abstract: Objective The study aimed to analyze the main clinical risk factors of death in patients with pulmonary tuberculosis secondary respiratory failure, and build a quantitative risk prediction model to provide reference for clinical practice. Method A total of 105 patients with pulmonary tuberculosis secondary respiratory failure to Danyang Hospital affiliated to Kangda College of Nanjing Medical University from March 2019 to June 2022 were retrospectively summarized. According to the clinical outcome, they were divided into death group (n=30, 28.6%), and survival group (n=75, 71.4%). The general clinical datas of the two groups were analyzed, including gender, age, sputum smear positive rate, sputum culture positive rate, nucleic acid quantitative detection Xpert MTB/RIF positive rate, comorbid diseases, complications, tuberculosis classification, admission pulmonary function (forced vital capacity, tidal volume, residual gas), admission arterial blood gas analysis[arterial partial pressure of oxygen (PaO₂), partial pressure of carbon dioxide (PaCO₂), oxygen saturation (SaO₂), PaO₂/FiO₂], APACHEⅡ score, C-reactive protein (CRP), white blood cell count, neutrophil/lymphocyte ratio(NLR), mean arterial pressure (MAP), albumin when arriving at hospital; Then, multivariate Logistic regression analysis was used to screen the main risk factors those may affect the death outcome, and the risk prediction model was constructed. Finally, the receiver operating curve (ROC curve) was used to evaluate the diagnostic efficacy. Result Compared with the survival group, the complications in the death group were increased, the hospital forced vital capacity was decreased, PaO₂/FiO₂ was decreased, NLR was increased, and albumin was decreased (P<0.05). In the death group,the bacterial resistance rate and invasive ventilation rate were increased, ventilation time was prolonged, treatment 3d-PaO₂/FiO₂ was decreased, APACHEⅡ score was increased, CRP and NLR were increased, albumin was decreased (P<0.05). Logistic regression model showed that PaO₂/FiO₂, NLR, albumin, APACHEⅡ score and CRP after three-day treatment were the main risk factors to death (P<0.05). The risk prediction model Y=2.563-0.248×(PaO₂/FiO₂)+0.166×NLR-0.318×albumin-0.074×(APACHEⅡ score)+0.396×CRP. ROC analysis showed that the accuracy of Y value for predicting death was 0.856, sensitivity was 82.6%, specificity was 75.5%, and cut-off value was 0.869. Conclusion Pulmonary tuberculosis secondary respiratory failure has a high in-hospital fatality rate. Lower of PaO₂/FiO₂ and albumin, higher of NLR, APACHEⅡ score and CRP after three-day treatment may be the main risk factors affecting death outcome, which has good accuracy and application value to build a quantitative risk prediction model for evaluating death.

Key words: Pulmonary tuberculosis, Respiratory failure, Death, Risk factors, Risk prediction model

中图分类号:

R181.3

符丽娜, 芮立美, 彭建华, 王华权. 肺结核合并呼吸衰竭患者死亡风险预测模型的构建研究[J]. 新发传染病电子杂志, 2024, 9(1): 26-30.

Fu Lina, Rui Limei, Peng Jianhua, Wang Huaquan. Study on the construction of death risk prediction model for pulmonary tuberculosis patients with respiratory failure[J]. Electronic Journal of Emerging Infectious Diseases, 2024, 9(1): 26-30.

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