Lee Seung-Eun, Rudd Matthew, Kim Tae-Hwa, Oh Ji-Yoon, Lee Ji-Hyang, Jover Lola, Small Peter M, Chung Kian Fan, Song Woo-Jung
Department of Internal Medicine, Pusan National University School of Medicine, Pusan National University Yangsan Hospital, Yangsan, Korea.
Department of Mathematics and Computer Science, The University of the South, Sewanee, TN, USA.
Lung. 2023 Dec;201(6):555-564. doi: 10.1007/s00408-023-00647-1. Epub 2023 Oct 13.
This study evaluated the feasibility and utility of longitudinal cough frequency monitoring with the Hyfe Cough Tracker, a mobile application equipped with cough-counting artificial intelligence algorithms, in real-world patients with chronic cough.
Patients with chronic cough (> 8-week duration) were monitored continuously for cough frequency with the Hyfe app for at least one week. Cough was also evaluated using the Leicester Cough Questionnaire (LCQ) and daily cough severity scoring (0-10). The study analyzed adherence rate, the correlation between objective cough frequency and subjective scores, day-to-day variability, and patient experience.
Of 65 subjects consecutively recruited, 43 completed the study. The median cough monitoring duration was 13.9 days, with a median adherence of 91%. Study completion was associated with baseline cough severity, and the adherence rate was higher in younger subjects. Cross-sectional correlation analyses showed modest correlations between objective and subjective cough measures at the group level. However, in time series correlation analyses, correlations between objective and subjective measures widely varied across individuals. Cough frequency had greater day-to-day variability than daily cough severity scores in most subjects. A patient experience survey found that 70% of participants found the cough monitoring helpful, 86% considered it acceptable, and 84% felt it was easy to use.
Monitoring cough frequency longitudinally for at least one week may be feasible. The substantial day-to-day variability in objective cough frequency highlights the need for continuous monitoring. Grasping the implications of daily cough variability is crucial in both clinical practice and clinical trials.
本研究评估了使用Hyfe咳嗽追踪器（一款配备咳嗽计数人工智能算法的移动应用程序）对现实世界中的慢性咳嗽患者进行纵向咳嗽频率监测的可行性和实用性。
使用Hyfe应用程序对慢性咳嗽（持续时间>8周）患者的咳嗽频率进行至少一周的连续监测。还使用莱斯特咳嗽问卷（LCQ）和每日咳嗽严重程度评分（0-10）对咳嗽进行评估。该研究分析了依从率、客观咳嗽频率与主观评分之间的相关性、每日变异性以及患者体验。
在连续招募的65名受试者中，43名完成了研究。咳嗽监测的中位持续时间为13.9天，中位依从率为91%。研究完成情况与基线咳嗽严重程度相关，年轻受试者的依从率更高。横断面相关性分析显示，在组水平上，客观和主观咳嗽指标之间存在适度相关性。然而，在时间序列相关性分析中，客观和主观指标之间的相关性在个体间差异很大。在大多数受试者中，咳嗽频率的每日变异性大于每日咳嗽严重程度评分。一项患者体验调查发现，70%的参与者认为咳嗽监测有帮助，86%的人认为可以接受，84%的人觉得使用方便。
纵向监测咳嗽频率至少一周可能是可行的。客观咳嗽频率的显著每日变异性凸显了持续监测的必要性。在临床实践和临床试验中，了解每日咳嗽变异性的影响至关重要。
