Abstract:
Background 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).
Methods 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.
Results 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.
Conclusion 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.
Disclaimer This research/work/investigator was supported (in part) by the Division of Intramural Research of the National Institutes of Health, NINDS. The content is solely the responsibility of the author(s) and does not necessarily represent the official views of the National Institutes of Health.
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