Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK.
Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
BMC Musculoskelet Disord. 2022 Aug 13;23(1):770. doi: 10.1186/s12891-022-05723-w.
People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging. This mobile health (mHealth) study explored the viability of using a smartphone app to collect patient-reported symptoms with contemporaneous Dried Blood Spot Sampling (DBSS) for inflammation.
Over 30 days, thirty-eight participants (12 RA, 13 OA, and 13 FM) used uMotif, a smartphone app, to report fatigue, pain and mood, on 5-point ordinal scales, twice daily. Daily DBSS, from which C-reactive Protein (CRP) values were extracted, were completed on days 1-7, 14 and 30. Participant engagement was determined based on frequency of data entry and ability to calculate within- and between-day symptom changes. DBSS feasibility and engagement was determined based on the proportion of samples returned and usable for extraction, and the number of days between which between-day changes in CRP which could be calculated (days 1-7).
Fatigue was reported at least once on 1085/1140 days (95.2%). Approximately 65% of within- and between-day fatigue changes could be calculated. Rates were similar for pain and mood. A total of 287/342 (83.9%) DBSS, were returned, and all samples were viable for CRP extraction. Fatigue, pain and mood varied considerably, but clinically meaningful (≥ 5 mg/L) CRP changes were uncommon.
Embedding DBSS in mHealth studies will enable researchers to obtain serial symptom assessments with matched biological samples. This provides exciting opportunities to address hitherto unanswerable questions, such as elucidating the mechanisms of fatigue fluctuations.
风湿性疾病患者会经历疲劳的波动，这些波动很麻烦。引起波动的原因有疼痛、情绪和炎症等，这些原因相互影响，互为因果，要确定这些潜在原因之间的关系，需要进行连续评估，但这在方法学上具有挑战性。本项移动健康（mHealth）研究旨在探索使用智能手机应用程序收集患者报告的症状，并同时进行即时干血斑采样（DBS）以评估炎症的可行性。
在 30 天内，38 名参与者（12 名类风湿关节炎患者、13 名骨关节炎患者和 13 名纤维肌痛患者）使用智能手机应用程序 uMotif，每天两次在 5 点定序量表上报告疲劳、疼痛和情绪。在第 1-7 天、第 14 天和第 30 天，完成每日的 DBS，从中提取 C 反应蛋白（CRP）值。根据数据输入的频率和计算日内和日间症状变化的能力，确定参与者的参与度。根据返回和可用于提取的样本比例以及可以计算 CRP 日间变化的天数（第 1-7 天），确定 DBS 的可行性和参与度。
在 1140 天（95.2%）中至少报告了一次疲劳。大约 65%的日内和日间疲劳变化可以计算。疼痛和情绪的比例相似。共收到 287/342（83.9%）的 DBS，所有样本均适用于 CRP 提取。疲劳、疼痛和情绪变化很大，但临床意义上（≥5mg/L）的 CRP 变化并不常见。
在 mHealth 研究中嵌入 DBS 将使研究人员能够获得连续的症状评估和匹配的生物样本。这为解决迄今无法回答的问题提供了令人兴奋的机会，例如阐明疲劳波动的机制。
