Mixed methods system for the assessment of post-exertional malaise in myalgic encephalomyelitis/chronic fatigue syndrome: an exploratory study

Author:

Stussman BarbaraORCID,Calco Brice,Norato Gina,Gavin Angelique,Chigurupati Snigdha,Nath Avindra,Walitt Brian

Abstract

BackgroundA 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. 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 semistructured qualitative interviews (QIs) at the same intervals as visual analogue scale (VAS) measures after a cardiopulmonary exercise test (CPET).MethodsTen ME/CFS and nine healthy volunteers participated in a CPET. For each volunteer, PEM symptom VAS (12 symptoms) and semistructured 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 ME/CFS volunteer. Performance of QI and VAS data was compared with each other using Spearman correlations.ResultsEach 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. QI and VAS fatigue data corresponded well an hour prior to exercise (pre-CPET, r=0.7) but poorly at peak PEM (r=0.28) and with the change from pre-CPET to peak (r=0.20). When the most bothersome symptom identified from QIs was used, these correlations improved (r=0.0.77, 0.42. and 0.54, respectively) and reduced the observed VAS scale ceiling effects.ConclusionIn this exploratory study, QIs were able to capture changes in PEM severity and symptom quality over time, even when VAS scales failed to do so. Measurement of PEM can be improved by using a quantitative–qualitative mixed model approach.

Funder

National Institute of Neurological Disorders and Stroke

Publisher

BMJ

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