Use of a Digital Inhaler to Assess COPD Disease Variability and Identify Impending Acute COPD Exacerbations: A Pilot Study

使用数字吸入器评估慢性阻塞性肺疾病(COPD)疾病变异性并识别即将发生的急性COPD加重:一项初步研究

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Abstract

RATIONALE: Studies have shown that digital inhalers, using remote monitoring data, can improve medication adherence and clinical outcomes, such as prediction of impending asthma exacerbations. There is limited research on the clinical utility of physiologic inhalation parameters and inhaler medication use data captured by a digital inhaler to identify impending acute exacerbations of chronic obstructive pulmonary disease (AECOPDs). OBJECTIVES: The objective was to determine variation in digital inhaler-measured physiologic and inhaler use metrics in ambulatory chronic obstructive pulmonary disease (COPD) patients in advance of an AECOPD. METHODS: This phase 4, open-label, 3-month pilot study was conducted at 2 U.S. centers. Participants used the ProAir Digihaler for primary rescue medication during the study. Participants were contacted monthly for COPD disease assessments. Inhaler metric variations leading up to an AECOPD were evaluated. RESULTS: The ProAir Digihaler measured key inhalation metrics (mean [standard deviation]) including peak inspiratory flow (PIF) (67.6 [20.3]L/min), inhalation volume (1.40 [0.60]L), and recorded inhaler use from 9649 inhalations among 40 participants. Statistically significant reductions were observed in inhalation volume (1.4L versus 1.1L), inhalation duration (1875msec versus 1492.1msec), and time to peak (500msec versus 376.3msec) (p<0.02 for all comparisons) during the 14 days preceding an AECOPD. There were no significant changes observed in PIF (67.2 versus 63.3, p=0.1) and number of inhalations per day (2.7 versus 3.7, p=0.2). CONCLUSION: Physiologic data captured by a digital inhaler may serve as a valuable remote patient monitoring tool to help support the identification of early or impending AECOPDs among ambulatory COPD patients and monitor COPD disease variability.

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