Efficiency of neural respiratory drive for the assessment of bronchodilator responsiveness in patients with chronic obstructive pulmonary disease: an exploratory study.

Abstract

BACKGROUND:

Conventional lung function parameters, such as forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1) and inspiratory capacity (IC) are often used to assess the therapeutic outcomes of bronchodilators, but they lack sensitivity. A novel indicator, namely efficiency of neural respiratory drive (NRD), may objectively evaluate the physiological changes in patients with chronic obstructive pulmonary disease (COPD). We investigated whether this indicator could be used to more accurately assess the responsiveness to inhaled bronchodilators.

METHODS:

Thirty-six subjects with moderate-to-severe COPD were randomized into group A (n=18) and group B (n=18). Participants in group A inhaled 400 µg placebo, 400 µg salbutamol and 80 µg ipratropium in sequence whereas those in group B had the salbutamol and ipratropium reversed. At different time points after administration of placebo or bronchodilators, evaluated indices included FEV1, FVC, IC, root mean square (RMS) of diaphragm electromyogram (EMGdi), and efficiency of NRD [herein defined as the ratio of minute ventilation (VE) to RMS, or VE/RMS].

RESULTS:

FEV1, FVC, IC, RMS, and VE/RMS significantly improved after inhaled bronchodilators and VE/RMS had the largest improvement among five indices. The detection efficiency of VE/RMS was greater than FEV1, FVC, IC (all P<0.05), but not different from RMS. The accuracy and sensitivity of VE/RMS were significantly higher than FEV1, FVC, IC, and RMS (all P<0.05).

CONCLUSIONS:

Efficiency of NRD may be a sensitive tool to evaluate the efficacy of inhaled bronchodilators in COPD.

• Authors: Yun Li, Yin-Huan Li, Shuo Li, Yu-Wen Luo, Rui Xiao, Yu-Xia Huang, Jin-Lun Huang, Yi-Tai Chen, Rong-Chang Zhi, Xin Chen
• Journal: Journal of thoracic disease (J Thorac Dis) Vol. 8 Issue 5 Pg. 958-65 (May 2016) ISSN: 2072-1439 [Print] China
• PMID: 27162672 (Publication Type: Journal Article)