方法:所有患者在首次就诊时进行标准肺功能及IOS检查,并依据IOS定义的SAD存在与否进行分层(阻抗由5 Hz降至20 Hz [R5-R20]>0.07kPa×s×L-1)。应用单变量和多变量分析及分类树方法分析临床变量和结果之间的横断面关系。
   结果:队列中有62%合并SAD。与非SAD患者相比,合并SAD的患者哮喘控制欠佳、ICS使用剂量较大(p<0.001)。FeNO升高(OR 2.05, 95% CI 1.14-3.70)、女性(OR 2.27, 95% CI 1.29-4.06)、吸烟(OR 3.06, 95% CI 1.60-6.05)、老龄(OR 3.08, 95% CI 1.77-5.49)、哮喘相关夜间憋醒(OR 3.34, 95% CI 1.85-6.17)、超重(OR 3.64, 95% CI 1.99-6.85)以及运动诱导哮喘症状(EIA)(OR 6.39, 95% CI 3.65-11.45)是SAD的独立预测因子。分类树分析确定EIA、超重、哮喘相关夜间憋醒、吸烟、老龄在区分出SAD患者中具有临床使用价值。

(中日友好医院呼吸与危重症医学科一部 张鑫 摘译 林江涛 审校)
(J Allergy Clin Immunol Pract. 2019 Nov 11. pii: S2213-2198(19)30932-8.)

Clinical characterization and predictors of IOSdefined small airway dysfunction in asthma.                       
Cottini M, Licini A, Lombardi C, Berti A.
BACKGROUND: The involvement of small airways has recently gained greater recognition in asthma. Impulse oscillometry (IOS) is a simple and noninvasive method based on the forced oscillation technique, for the detection of small airway dysfunction (SAD).
OBJECTIVE: We aimed to identify the predictors of SAD in an unselected sample of 400 patients with physician-diagnosed asthma.
METHODS: All patients underwent standard spirometry and IOS at the first visit, and were stratified by the presence of SAD defined by IOS (fall in resistance from 5 to 20 Hz [R5-R20]>0.07kPa×s×L-1). Univariable and multivariable analyses and classification-tree method were used to analyze cross-sectional relationships between clinical variables and outcome (SAD).
RESULTS: SAD was present in 62% of the cohort. Subjects with SAD showed a less well-controlled asthma, according to the Global Initiative for Asthma (GINA) definition, and a higher mean inhaled corticosteroid (ICS) dosage use compared to subjects without SAD (both p<0.001). Increased FeNO (OR 2.05, 95% CI 1.14-3.70), female sex (OR 2.27, 95% CI 1.29-4.06), smoking (OR 3.06, 95% CI 1.60-6.05), older age (OR 3.08, 95% CI 1.77-5.49), asthma-related night awakenings (OR 3.34, 95% CI 1.85-6.17), overweight (OR 3.64, 95% CI 1.99-6.85) and exercise-induced asthma symptoms (EIA) (OR 6.39, 95% CI 3.65-11.45) resulted independent predictors of SAD. Classification-tree analysis confirmed that EIA, overweight, asthma-related night awakenings, smoking and older age have potential for clinical use in distinguishing patients with SAD from those without it.
CONCLUSION: We identified predictors of SAD and showed that especially EIA, overweight, asthma-related night awakenings, smoking, and older age were strongly associated with SAD.

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