Drummond M Bradley, Hemphill Caleb C, Hill Tanisha, Boe Amanda, Yu Daisy, Ohar Jill A
Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States.
Teva Branded Pharmaceutical Products Research and Development, Inc., Parsippany, New Jersey, United States.
Chronic Obstr Pulm Dis. 2025 May 27;12(3):250-259. doi: 10.15326/jcopdf.2024.0555.
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).
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.
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.
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) (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, =0.1) and number of inhalations per day (2.7 versus 3.7, =0.2).
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.
研究表明，利用远程监测数据的数字吸入器可提高用药依从性和临床疗效，如预测即将发生的哮喘加重。关于数字吸入器获取的生理吸入参数和吸入器用药数据在识别慢性阻塞性肺疾病（COPD）急性加重（AECOPD）方面的临床效用，研究有限。
目的是确定在AECOPD发生前，动态慢性阻塞性肺疾病（COPD）患者中数字吸入器测量的生理指标和吸入器使用指标的变化。
这项4期、开放标签、为期3个月的试点研究在美国的2个中心进行。研究期间，参与者使用ProAir Digihaler作为主要急救药物。每月联系参与者进行COPD疾病评估。评估了导致AECOPD的吸入器指标变化。
ProAir Digihaler测量了关键吸入指标（平均值[标准差]），包括吸气峰流速（PIF）（67.6[20.3]L/分钟）、吸入量（1.40[0.60]L），并记录了40名参与者9649次吸入的吸入器使用情况。在AECOPD发生前14天内，吸入量（1.4L对1.1L）、吸入持续时间（1875毫秒对1492.1毫秒）和达到峰值的时间（500毫秒对376.3毫秒）出现了具有统计学意义的下降（所有比较的P值均为0.02）。PIF（67.2对63.3，P = 0.1）和每日吸入次数（2.7对3.7，P = 0.2）未观察到显著变化。
数字吸入器获取的生理数据可作为一种有价值的远程患者监测工具，有助于识别动态COPD患者中的早期或即将发生的AECOPD，并监测COPD疾病的变异性。
