Stussman Barbara, Calco Brice, Norato Gina, Gavin Angelique, Chigurupati Snigdha, Nath Avindra, Walitt Brian
National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, United States.
National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.
medRxiv. 2023 Apr 26:2023.04.24.23288821. doi: 10.1101/2023.04.24.23288821.
A central feature of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is post exertional malaise (PEM), which is an acute worsening of symptoms after a physical, emotional and/or mental exertion. PEM is also a feature of Long COVID. Dynamic measures of PEM have historically included scaled questionnaires which have not been validated in ME/CFS. To enhance our understanding of PEM and how best to measure it, we conducted semi-structured qualitative interviews (QIs) at the same intervals as Visual Analog Scale (VAS) measures after a Cardiopulmonary Exercise Test (CPET).
Ten ME/CFS and nine healthy volunteers participated in a CPET. For each participant, PEM symptom VAS (7 symptoms) and semi-structured QIs were administered at six timepoints over 72 hours before and after a single CPET. QI data were used to plot the severity of PEM at each time point and identify the self-described most bothersome symptom for each patient. QI data were used to determine the symptom trajectory and peak of PEM. Performance of QI and VAS data were compared to each other using Spearman correlations.
QIs documented that each ME/CFS volunteer had a unique PEM experience, with differences noted in the onset, severity, trajectory over time, and most bothersome symptom. No healthy volunteers experienced PEM. Scaled QI data were able to identify PEM peaks and trajectories, even when VAS scales were unable to do so due to known ceiling and floor effects. QI and VAS fatigue data corresponded well prior to exercise (baseline, r=0.7) but poorly at peak PEM (r=0.28) and with the change from baseline to peak (r=0.20). When the most bothersome symptom identified from QIs was used, these correlations improved (r=.0.77, 0.42. and 0.54 respectively) and reduced the observed VAS scale ceiling and floor effects.
QIs were able to capture changes in PEM severity and symptom quality over time in all the ME/CFS volunteers, even when VAS scales failed to do so. Information collected from QIs also improved the performance of VAS. Measurement of PEM can be improved by using a quantitative-qualitative mixed model approach.
肌痛性脑脊髓炎/慢性疲劳综合征（ME/CFS）的一个核心特征是运动后不适（PEM），即身体、情感和/或精神劳累后症状的急性加重。PEM也是长期新冠的一个特征。历史上，PEM的动态测量方法包括未经ME/CFS验证的量表问卷。为了加深我们对PEM及其最佳测量方法的理解，我们在心肺运动试验（CPET）后，按照与视觉模拟量表（VAS）测量相同的时间间隔进行了半结构化定性访谈（QI）。
10名ME/CFS患者和9名健康志愿者参加了CPET。对于每位参与者，在单次CPET前后的72小时内，于六个时间点进行PEM症状VAS（7种症状）和半结构化QI。QI数据用于绘制每个时间点PEM的严重程度，并确定每位患者自述最困扰的症状。QI数据用于确定PEM的症状轨迹和峰值。使用Spearman相关性比较QI和VAS数据的表现。
QI记录显示，每位ME/CFS志愿者都有独特的PEM经历，在发作、严重程度、随时间的轨迹以及最困扰的症状方面存在差异。没有健康志愿者经历PEM。即使由于已知的天花板效应和地板效应VAS量表无法做到，量化的QI数据也能够识别PEM的峰值和轨迹。运动前（基线，r = 0.7）时，QI和VAS疲劳数据相关性良好，但在PEM峰值时相关性较差（r = 0.28），从基线到峰值的变化时相关性也较差（r = 0.20）。当使用从QI中确定的最困扰症状时，这些相关性得到改善（分别为r = 0.77、0.42和0.54），并减少了观察到的VAS量表天花板效应和地板效应。
即使VAS量表无法做到，QI也能够捕捉所有ME/CFS志愿者中PEM严重程度和症状质量随时间的变化。从QI收集的信息也提高了VAS的表现。通过使用定量-定性混合模型方法可以改善PEM的测量。
