呼出气一氧化氮和血嗜酸性粒细胞对哮喘患者气道高反应性程度的预测价值

Predictive value of exhaled nitric oxide and blood eosinophils on the degree of airway hyperresponsiveness in asthma patients

目的分析呼出气一氧化氮(fraction of exhaled nitric oxide,FeNO)水平和血嗜酸性粒细胞(blood eosinophil,B-Eos)计数对哮喘患者气道高反应性(airway hyperresponsiveness,AHR)程度的预测价值,并探索AHR严重程度的预测模型。方法选择2014年1月至2019年12月于我院首诊为哮喘的患者1347例,将其中520例具有FeNO和B-Eos的纳入主要研究人群。依据乙酰甲胆碱激发试验(methacholine challenge test,MCT)结果,分为重度AHR组(MCT为中度或重度阳性183例和轻度AHR组(MCT为极轻度或轻度阳性337例。然后分析两组差异,用Logistic回归构建预测模型,最后绘制重度AHR风险的列线图和森林图。结果重度AHR组的FeNO和B-Eos均高于轻度AHR组(73 vs.36 ppb、394 vs.243个/μl,P<0.001)。Logistic回归示年龄、性别、FEV_(1)/FVC、B-Eos、FeNO为重度AHR的独立危险因素,将它们纳入回归模型,其灵敏度为49.7%,特异度为87.8%。受试者工作特征曲线示模型的曲线下面积明显高于单独的FeNO或B-Eos(0.797 vs.0.715或0.644,P<0.001)。重度AHR风险的亚组分析示:随着FeNO或B-Eos的增高风险逐步增高(趋势检验P<0.001);女性的风险为男性的1.57倍(P=0.041),而低FEV_(1)/FVC组(<70%)为正常组的3.38倍(P<0.001)。结论在哮喘患者中单独的FeNO或B-Eos对重度AHR具有中等程度的预测效能,通过多因素回归模型构建的列线图可以用于预测重度AHR的概率。

Objective To analyze the predictive value of the fractional of exhaled nitric oxide(FeNO)and blood eosinophil(B-Eos)counts on the severity of airway hyperresponsiveness in asthma patients,then explore a prediction model for the severity of AHR.Methods This study retrospectively collected 1347 patients diagnosed with asthma in our hospital from January 2014 to December 2019,and identified a cohort of 520 patients who had simultaneous completed datasets of FeNO and B-Eos.According to the methacholine challenge test(MCT)results,the population was divided into severe AHR group(MCT is moderate or severely positive,n=183)and mild AHR group(MCT is very mild or slightly positive,n=337).The differences in demographics,lung function,FeNO and B-Eos are analyzed between these two groups.Logistic regression is used to construct a multi-factor regression model,then the risk of severe AHR is displayed by nomogram and forest chart.Results FeNO and B-Eos in the severe AHR group were significantly higher than those in the mild AHR group(73 vs.36 ppb,394 vs.243 cells/μl,P<0.001).Logistic regression showed that age,gender,FEV_(1)/FVC ratio,B-Eos,and FeNO were independent risk factors for severe AHR.The model incorporating these risk factors has a sensitivity of 49.7%and a specificity of 87.8%.The receiver operating characteristic(ROC)curve analysis shows that the AUC of the regression model is significantly higher than that of FeNO or B-Eos alone(0.797 vs.0.715 or 0.644,P<0.001).When comparing the risk of having severe AHR in different subgroups,the adjusted odds ratio(aOR)of having severe AHR elevated progressively with the gradual increase in FeNO or B-Eos(P<0.001).While,the multivariable aOR of having severe AHR was 1.57 for females(P=0.041),3.38 for patients with lower FEV_(1)/FVC ratio(<70%,P<0.001).Conclusion FeNO or B-Eos alone has moderate diagnostic accuracy for predicting severe AHR.The nomogram constructed by the multi-factor regression model can be used to predict the probability of severe AHR.