The Value of Fractional Exhaled Nitric Oxide and Impulse Oscillometric and Spirometric Parameters for Predicting Bronchial Hyperresponsiveness in Adults with Chronic Cough

Abstract

Lichang Chen,1,* Lingling Wu,1,* Dongzhu Lu,1 Mei Zi,2 Huapeng Yu1 1Department of Respiratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, The Third People’s Hospital of Shenzhen, Shenzhen, People’s Republic of China*These authors contributed equally to this workCorrespondence: Huapeng YuDepartment of Respiratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, People’s Republic of ChinaTel [phone]Fax [phone]Email [email protected]: 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

Keywords

• maximum mid-expiratory flow
• resonant frequency
• cough variant asthma
• roc curve
• diagnosis