Author(s): HAYES, L., SANAL-HAYES, N.E.M., MAIR, J.L., DELLO IACONO, A., INGRAM, J., MCLAUGHLIN, M., ORMEROD, J., CARLESS, D., HILLIARD, N., MEACH, R., SCULTHORPE, N.F., Institution: LANCASTER UNIVERSITY, Country: UNITED KINGDOM, Abstract-ID: 485

INTRODUCTION:
A common symptom management strategy in long COVID is energy management [1]. Energy management is used to help people manage their ‘energy envelope’ to limit incidence of post-exertional malaise (PEM) [2]. However, a platform that warns participants of potential PEM, informed by granular biofeedback, using validated instruments, was non-existent to date. Therefore, the aim of this trial was to determine if activity tracking combined with just-in-time messages helped people with long COVID reduce PEM over six months. We hypothesised a priori that a just-in-time intervention to assist energy management (intervention group) would reduce PEM compared to usual care (control).
METHODS:
Following ethical approval, and informed consent, 250 participants were randomised 1:1 into intervention or control. All participants downloaded the study app (“Pace Me”), while only the intervention were provided with an activity tracker (Fitbit Charge 5, Fitbit Inc., San Francisco, CA, USA) and downloaded the FitBit app. The intervention version of the app included energy management support and data collection instruments, whilst the control version included only data collection. Intervention group participants had a personalised daily activity allowance, initially set to <30 minutes of activity >60% of their age-predicted heart rate maximum and received notifications if they exceeded 50%, 75%, and 100% of their allowance. Notifications included an alert message and support tips. The primary outcome was PEM assessed using the DePaul Symptom Questionnaire - PEM (DSQ-PEM) [3], pre- and post-intervention.
RESULTS:
The DSQ-PEM sum of the intervention group was 48 (95% CI 44-53) at baseline and 46 (95% CI 41-51) post-intervention. The control group value was 47 (95% CI 42-52) at baseline and 44 (95% CI 39-49) at follow-up (interaction effect p=.614, η²p=.002; trivial). Additionally, the number of individuals classified as positive for PEM (i.e. discrete yes/no) decreased from baseline to follow-up (p=.004). There were 118 participants with no change, 31 who improved, and 12 who worsened. No between-group effects were observed at baseline (p=.411) or follow-up (p=.155).
CONCLUSION:
A just-in-time intervention using a wearable activity tracker was no more effective than control at reducing PEM in people with long COVID. A regression to the mean may have occurred, whereby people with long COVID recovered naturally, and this is supported by our categorical analysis observing several people went from PEM positive to PEM negative over six months.


REFERENCES
1 NICE. Myalgic encephalomyelitis (or encephalopathy)/chronic fatigue syndrome: diagnosis and management. chronic fatigue syndrome. 2021;87.
2 Goudsmit et al. Disabil Rehabil. 2012;34:1140–7. doi: 10.3109/09638288.2011.635746
3 Cotler J et al. Diagnostics. 2018;8:66. doi: 10.3390/diagnostics8030066