Crespo-Lessmann Astrid, Curto Elena, Mateus Medina Eder Freddy, Palones Esther, Belda Soler Alicia, Sánchez Maza Soraya, Soto-Retes Lorena, Plaza Vicente
Servicio de Neumología y Alergia, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
Institut d'Investigació Biomédica Sant Pau, Barcelona, Spain.
J Asthma Allergy. 2023 Jan 19;16:95-103. doi: 10.2147/JAA.S389402. eCollection 2023.
The objectives of this study were, for patients attending a specialist asthma clinic at a tertiary care hospital, to determine, from sputum induction (SI), proportions of bronchial inflammatory phenotypes, demographic, clinical and functional characteristics of each phenotype, and the most accessible non-invasive inflammatory marker that best discriminates between phenotypes.
Included were 96 patients with asthma, attending a specialist asthma clinic at a tertiary care hospital, who underwent testing as follows: SI, spirometry, fractional exhaled nitric oxide (FeNO), blood eosinophilia, total immunoglobulin E (IgE), and a skin prick test.
SI phenotypes were 46.9% eosinophilic, 33.3% paucigranulocytic, 15.6% neutrophilic, and 4.2% mixed. No significantly different clinical or functional characteristics were observed between the phenotypes. A positive correlation was observed between SI eosinophilia and both emergency visits in the last 12 months (p = 0.041; r = 0.214) and FeNO values (p = 0.000; r = 0.368). Blood eosinophilia correlated with SI eosinophilia (p = 0.001; r = 0.362) and was the best predictor of bronchial eosinophilia, followed by FeNO, and total blood IgE (area under the receiver operating characteristic curve (AUC-ROC) 72%, 65%, and 53%, respectively), although precision was only fair.
In consultations for severe asthma, the most frequent phenotype was eosinophilic. Peripheral blood eosinophilia is a reliable marker for discriminating between different bronchial inflammatory phenotypes, is useful in enabling doctors to select a suitable biologic treatment and so prevent asthma exacerbation, and is a better predictor of bronchial eosinophilia than FeNO and IgE values.
本研究的目的是，针对在一家三级护理医院的专科哮喘诊所就诊的患者，通过痰液诱导（SI）来确定支气管炎症表型的比例、每种表型的人口统计学、临床和功能特征，以及最易获取的能最佳区分各表型的非侵入性炎症标志物。
纳入了96例在一家三级护理医院的专科哮喘诊所就诊的哮喘患者，他们接受了以下检查：SI、肺功能测定、呼出一氧化氮分数（FeNO）、血嗜酸性粒细胞、总免疫球蛋白E（IgE）以及皮肤点刺试验。
SI表型中嗜酸性粒细胞型占46.9%，少粒细胞型占33.3%，中性粒细胞型占15.6%，混合型占4.2%。各表型之间未观察到显著不同的临床或功能特征。在SI嗜酸性粒细胞与过去12个月内的急诊就诊次数（p = 0.041；r = 0.214）以及FeNO值（p = 0.000；r = 0.368）之间均观察到正相关。血嗜酸性粒细胞与SI嗜酸性粒细胞相关（p = 0.001；r = 0.362），并且是支气管嗜酸性粒细胞的最佳预测指标，其次是FeNO和总血IgE（受试者操作特征曲线下面积（AUC-ROC）分别为72%、65%和53%），尽管准确性仅为一般。
在重度哮喘的会诊中，最常见的表型是嗜酸性粒细胞型。外周血嗜酸性粒细胞是区分不同支气管炎症表型的可靠标志物，有助于医生选择合适的生物治疗以预防哮喘加重，并且比FeNO和IgE值更能预测支气管嗜酸性粒细胞。
