Hu Jie, Fan Yinghong, Luo Ronghua, Li Qianqian, Ai Tao, Wang Li
Department of Pediatric Respiratory Medicine, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
J Asthma Allergy. 2025 Mar 7;18:391-402. doi: 10.2147/JAA.S507446. eCollection 2025.
To investigate whether Impulse Oscillometry (IOS) could more effectively monitor children with uncontrolled asthma and evaluate small airway function changes, while establishing a prediction model in combination with fractional exhaled nitric oxide (FeNO) to assist in clinical management and treatment of asthmatic children.
A retrospective study was conducted on 203 asthmatic children who were followed up in our hospital from August 2023 to August 2024. Patients were divided into controlled asthma group (n=80) and uncontrolled asthma group (n=123). Conventional ventilatory parameters, IOS parameters, FeNO levels, and clinical data were analyzed and compared between the two groups. The optimal prediction model was established through multivariate logistic regression.
In the uncontrolled asthma group, the respiratory system impedance at 5 hz (Z5), resistance at 5 hz (R5), the difference between resistance at 5 hz and resistance at 20 hz (R5-R20), resonant frequency (Fres), and FeNO levels were significantly higher compared to the controlled asthma group. The ratio of forced expiratory volume in one second to forced vital capacity (FEV/FVC), forced expiratory flow at 50% (FEF50), forced expiratory flow at 75% (FEF75), and maximal mid-expiratory flow (MMEF) were lower in the uncontrolled group (P<0.05). Receiver operating characteristic curve (ROC) analysis demonstrated that Z5, R5, R5-R20, Fres, and FeNO were valuable in asthma diagnosis (P<0.05), with higher sensitivity in monitoring small airway function compared to MMEF. Multivariate logistic regression analysis established the optimal prediction model combining R5+(R5-R20) +FeNO, with an area under curve (AUC) of 0.915 (P<0.05), sensitivity of 0.831, and specificity of 0. 892.
Compared to conventional pulmonary function tests, IOS effectively identifies uncontrolled status in asthmatic children, particularly in younger patients, with higher sensitivity to small airway function changes. The model comprising R5+(R5-R20) +FeNO demonstrates clinical value in identifying uncontrolled status in asthmatic children.
探讨脉冲振荡法(IOS)能否更有效地监测哮喘控制不佳的儿童并评估小气道功能变化,同时结合呼出一氧化氮分数(FeNO)建立预测模型,以辅助哮喘儿童的临床管理和治疗。
对2023年8月至2024年8月在我院随访的203例哮喘儿童进行回顾性研究。将患者分为哮喘控制组(n = 80)和哮喘未控制组(n = 123)。分析比较两组的常规通气参数、IOS参数、FeNO水平及临床资料。通过多因素logistic回归建立最佳预测模型。
哮喘未控制组5Hz时的呼吸系统阻抗(Z5)、5Hz时的阻力(R5)、5Hz与20Hz时阻力之差(R5 - R20)、共振频率(Fres)及FeNO水平均显著高于哮喘控制组。哮喘未控制组一秒用力呼气容积与用力肺活量之比(FEV/FVC)、50%用力呼气流量(FEF50)、75%用力呼气流量(FEF75)及最大呼气中期流量(MMEF)均较低(P < 0. + 05)。受试者工作特征曲线(ROC)分析表明,Z5、R5、R5 - R20、Fres及FeNO对哮喘诊断有价值(P < 0.05),与MMEF相比,对小气道功能监测的敏感性更高。多因素logistic回归分析建立了结合R5 +(R5 - R20)+ FeNO的最佳预测模型,曲线下面积(AUC)为0.915(P < 0.05),敏感性为0.831,特异性为0.892。
与传统肺功能检查相比,IOS能有效识别哮喘儿童的未控制状态,尤其是对低龄患者,对小气道功能变化的敏感性更高。由R5 +(R5 - R20)+ FeNO组成的模型在识别哮喘儿童未控制状态方面具有临床价值。