Remote data collection to detect asthma exacerbations: A decentralized approach to clinical research in asthma.

IF 2.7 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Journal of Clinical and Translational Science Pub Date : 2026-02-10 eCollection Date: 2026-01-01 DOI:10.1017/cts.2026.10697
Allison J Burbank, Jeremy Owens, Andre Espaillat, Claire E Atkinson, Stephen A Schworer, Katherine M Whaylen, Kelly Chason, Michelle L Hernandez
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引用次数: 0

Abstract

Background: Decentralized trial designs can improve accessibility and continuity of research participation by enabling remote data collection. This manuscript describes our team's experiences with remote data collection to identify acute asthma exacerbations in a clinical study as well as practical insights that support the continued optimization of remote methodologies.

Methods: In this 12-month observational study, adolescents aged 12-21 years with persistent asthma and ≥1 exacerbation in the prior 24 months completed an initial in-person visit followed by monthly virtual visits. Participants used home spirometry, app-based symptom tracking, smart inhalers to monitor lung function and short-acting beta agonist (SABA) use, and self-collection of nasal epithelial lining fluid (NELF) samples. Exacerbations were defined a priori by symptom/SABA thresholds or ≥20% FEV1 decline.

Results: Forty participants enrolled; 73% completed all visits. Median adherence to performance of daily spirometry and symptom surveys was 44% and 38%, respectively. Seventy-eight percent experienced ≥1 exacerbation. Of 132 alerts, 80% represented true exacerbations, primarily due to ≥20% FEV1 decline; erroneous alerts were linked to software errors and poor spirometry technique. Sixty-six NELF sample sets were collected and 50 were analyzed. Cytokine concentrations did not differ significantly between clinic-collected and self-collected samples. Technical challenges included device connectivity issues, erroneous alerts, and shipping delays.

Conclusions: Decentralized study designs with remote data collection requires further study as a means of conducting clinical research in asthma that increases participant accessibility, representation and generalizability of trial results. This approach presents numerous challenges and requires further optimization to address adherence, technical complexity, and staff burden while maintaining scientific rigor.

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远程数据收集以检测哮喘恶化:哮喘临床研究的分散方法。
背景:分散的试验设计可以通过远程数据收集来提高研究参与的可及性和连续性。这份手稿描述了我们团队的经验,远程数据收集,以确定急性哮喘恶化的临床研究,以及实际的见解,支持远程方法的持续优化。方法:在这项为期12个月的观察性研究中,12-21岁的持续性哮喘且在过去24个月内≥1次发作的青少年完成了首次亲自访问,随后每月进行虚拟访问。参与者使用家庭肺活量测定法、基于应用程序的症状跟踪、智能吸入器监测肺功能和短效β受体激动剂(SABA)的使用,以及自行收集鼻上皮衬里液(NELF)样本。病情加重的先验定义是症状/SABA阈值或FEV1下降≥20%。结果:40名受试者入组;73%的患者完成了所有的就诊。每日肺活量测定和症状调查的中位依从性分别为44%和38%。78%的患者≥1次加重。在132个警报中,80%代表真正的恶化,主要是由于FEV1下降≥20%;错误的警报与软件错误和糟糕的肺活量测定技术有关。共收集了66组NELF样本,分析了50组样本。细胞因子浓度在临床收集和自我收集的样本之间没有显著差异。技术挑战包括设备连接问题、错误警报和运输延迟。结论:分散的研究设计和远程数据收集需要进一步的研究作为开展哮喘临床研究的手段,以增加参与者的可及性、代表性和试验结果的普遍性。这种方法提出了许多挑战,需要进一步优化,以解决依从性、技术复杂性和人员负担,同时保持科学的严谨性。
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来源期刊
Journal of Clinical and Translational Science
Journal of Clinical and Translational Science MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
2.80
自引率
26.90%
发文量
437
审稿时长
18 weeks
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