已发表论文

呼出一氧化氮分数、脉冲示波和肺活量参数预测成人慢性咳嗽患者支气管高反应性的价值

 

Authors Chen L, Wu L, Lu D, Zi M, Yu H

Received 29 June 2021

Accepted for publication 3 August 2021

Published 20 August 2021 Volume 2021:14 Pages 1065—1073

DOI https://doi.org/10.2147/JAA.S326879

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 5

Editor who approved publication: Dr Amrita Dosanjh

Purpose: To evaluate the contribution of fractional exhaled nitric oxide (FeNO) and impulse oscillometry (IOS) and spirometric parameters in predicting bronchial hyperresponsiveness (BHR) in adults with chronic cough.
Patients and Methods: In total, 112 patients with chronic cough were enrolled in this prospective diagnostic study. Receiver operating characteristic (ROC) curves were generated to assess the diagnostic efficiency and optimal cut-off values of FeNO and IOS and spirometric parameters in predicting BHR. Optimal combinations of FeNO and IOS and spirometric parameters for BHR prediction were investigated using univariate and multivariate logistic regression models. Bootstrapping was employed for internal validation. Model discrimination and calibration were assessed using indices and calibration plots.
Results: Rhinitis and values of FeNO, IOS parameters (resonant frequency (Fres), reactance at 5 Hz (X5), and integrated area of low-frequency X (AX)) and spirometric parameters (FEV1, PEF, MEF75, MEF50, MEF25, MMEF) were significantly different between patients with BHR and those without BHR (P < 0.05). After adjusting for rhinitis, logistic analyses showed that FeNO combined with Fres, FeNO combined with MMEF, or the combination of FeNO, Fres and MMEF had high predictive value in diagnosing BHR; the areas under the ROC curves (AUCs) of the corresponding three models were 0.914, 0.919 and 0.927, respectively. In addition, the three models displayed good discrimination, with high C-index values and good calibration.
Conclusion: FeNO combined with Fres or MMEF or a combination of these three parameters may be conveniently used as indicators in BHR prediction.
Keywords: maximum mid-expiratory flow, resonant frequency, cough variant asthma, ROC curve, diagnosis