Zhi-Yuan Guan1, Yong Feng1, Xiao-Hua Han1. 1. Department of Pediatric Respiratory Medicine, Shengjing Hospital of China Medical University, Shenyang 110004, China. com).
Abstract
OBJECTIVES: To evaluate the value of fractional exhaled nitric oxide (FeNO) combined with impulse oscillometry (IOS) in the diagnosis of asthma in preschool children, and to establish the optimal predictive model. METHODS: A retrospective analysis was performed on 156 children with wheezing, aged 3-5 years, who were admitted from September 2019 to December 2020. These children were divided into an asthma group with 52 children and a non-asthma group with 104 children. The two groups were compared in terms of IOS parameters, FeNO, and clinical data. The multivariate logistic regression analysis was used to establish the optimal predictive model. RESULTS: Compared with the non-asthma group, the asthma group had significantly higher total respiratory system impedance at 5 Hz (Z5), resistance of respiratory system at 5 Hz and 20 Hz (R5 and R20, respectively), resonance frequency, reactance area (AX), and FeNO and a significantly lower reactance difference at 5 Hz (P<0.05). The receiver operating characteristic (ROC) curve analysis showed that Z5, R5, R20, and FeNO had a certain value in the diagnosis of asthma (P<0.05). The multivariate logistic regression analysis established the optimal predictive model of R20+AX+FeNO, with an area under the ROC curve of 0.858 (P<0.05), a sensitivity of 78.8%, and a specificity of 76.9%. CONCLUSIONS: FeNO combined with IOS is helpful for the diagnosis of asthma in preschool children, and the model of R20+AX+FeNO has a certain value in the diagnosis of asthma in these children.
OBJECTIVES: To evaluate the value of fractional exhaled nitric oxide (FeNO) combined with impulse oscillometry (IOS) in the diagnosis of asthma in preschool children, and to establish the optimal predictive model. METHODS: A retrospective analysis was performed on 156 children with wheezing, aged 3-5 years, who were admitted from September 2019 to December 2020. These children were divided into an asthma group with 52 children and a non-asthma group with 104 children. The two groups were compared in terms of IOS parameters, FeNO, and clinical data. The multivariate logistic regression analysis was used to establish the optimal predictive model. RESULTS: Compared with the non-asthma group, the asthma group had significantly higher total respiratory system impedance at 5 Hz (Z5), resistance of respiratory system at 5 Hz and 20 Hz (R5 and R20, respectively), resonance frequency, reactance area (AX), and FeNO and a significantly lower reactance difference at 5 Hz (P<0.05). The receiver operating characteristic (ROC) curve analysis showed that Z5, R5, R20, and FeNO had a certain value in the diagnosis of asthma (P<0.05). The multivariate logistic regression analysis established the optimal predictive model of R20+AX+FeNO, with an area under the ROC curve of 0.858 (P<0.05), a sensitivity of 78.8%, and a specificity of 76.9%. CONCLUSIONS: FeNO combined with IOS is helpful for the diagnosis of asthma in preschool children, and the model of R20+AX+FeNO has a certain value in the diagnosis of asthma in these children.
Authors: F H Guo; S A Comhair; S Zheng; R A Dweik; N T Eissa; M J Thomassen; W Calhoun; S C Erzurum Journal: J Immunol Date: 2000-06-01 Impact factor: 5.422
Authors: Nidhya Navanandan; Katharine L Hamlington; Rakesh D Mistry; Stanley J Szefler; Andrew H Liu Journal: Ann Allergy Asthma Immunol Date: 2020-07-09 Impact factor: 6.347
Authors: Soren Erik Pedersen; Suzanne S Hurd; Robert F Lemanske; Allan Becker; Heather J Zar; Peter D Sly; Manuel Soto-Quiroz; Gary Wong; Eric D Bateman Journal: Pediatr Pulmonol Date: 2010-10-20
Authors: Décio Medeiros; Pedro Castro; Ana Caroline Dela Bianca; Emanuel Sarinho; Jaqueline Figueirôa Araújo; Marco Correia Junior; Jose Angelo Rizzo Journal: Expert Rev Respir Med Date: 2020-09-20 Impact factor: 3.772