Design and validation of an energy level diary for fatigue management in patients with post-COVID syndrome

Abstract

Background: Post-COVID syndrome (PCS) is a frequent condition with an incidence of 7.8-10.6 per 100 unvaccinated and 3.5-5.3 events per 100 vaccinated persons. Cognitive and motor fatigue are common clinical manifestations, limiting patients' occupational, educational, and social activities severely.

Objective: This study aimed to develop a diary to keep record of daily changes in energy levels of patients with PCS to adapt their rehabilitation program.

Material and methods: We conducted a prospective observational study at two German rehabilitation centers in a codesign approach with repeated feedback loops. Daily energy changes were analyzed and validated using the Multidimensional Fatigue Inventory-20 (MFI-20).

Results: The final diary revealed that morning and evening energy levels of patients with PCS differed significantly, with 49.6 ± 18.6% and 33.4 ± 19.7%, respectively (p ≤ 0.0001, on admission). Energy levels decreased by ∼5% with active therapy and increased by ∼5% with passive therapy (p < 0.0001). A comparison with MFI-20 at discharge showed good negative correlation (r = -0.5358, p < 0.0001), and patient interviews revealed that most patients (N = 19; 95%) rated the diary as "useful for self-reflection" and "helpful tool to learn the process of pacing."

Discussion/conclusion: This diary is a valid and user-friendly tool to detect and control the effects of daily therapy during the rehabilitation of patients with PCS. It will facilitate individual planning and adaptation of therapies in PCS and other fatigue groups and may help to implement an effective relation of exercise load to load capacity (pacing) for optimal coping with the disease and an improved handling of daily activities in patients' lives.

Clinical trial registration: Clinicaltrials.gov, identifier (NCT06883500).

Keywords: chronic fatigue syndrome; diary approach; neurorehabiliation; post-COVID syndrome; post-COVID-19.

Figure 1

Expert consensus on diary creation, validation, and clinical application. The process of design, validation, and testing of clinical applicability was structured in three phases involving both an expert panel and affected patients. Phase 1 (A/B) Comprised monthly interdisciplinary expert meetings and initial patients’ feedback. Diary Version 1 asked for changes in FL, but daily variations were not reflected, and patients rejected Version 1. Final result: Version 2 reflects intraday changes in energy levels. Phase 2: Qualitative content analysis and usability assessment of Version 2 using structured patient interviews. Final result: sufficient representation of intraday changes in EL, positive patient feedback. Phase 3: Validation and testing of clinical application. Correlation of mean daily energy levels with results of the Multifunctional Fatigue Inventory-20. Investigation of the effects of therapy sessions on energy levels. Result: good correlation with energy level, useful to monitor and control effects of individual therapy sessions. PROM, patient-reported outcome measure; FL, fatigue level; EL, energy level. White box: activity in expert consensus/codesign. Black box: results of expert consensus process.

Figure 2

The post-COVID-19 syndrome (PCS) energy diary registers changes in patients’ daily energy levels during rehabilitation. Energy levels of PCS patients (N = 66) are given (A) over the entire rehabilitation process per day (morning vs. evening), (B) in comparison between all morning and evening ratings and separated by (C) sex (female, N = 44; male, N = 22) and (D) median age (>54 years, N = 31; ≤ 54 years, N = 35). Energy levels of patients with coronary artery disease (CAD; N = 11) are given (E) over the entire rehabilitation process per day (morning vs. evening) and (F) in comparison between all morning and evening ratings. Comparison between morning and evening ratings reveals that the fatigue diary documents the loss of energy during the day, as well as energy restoration overnight (p < 0.0001), for both PCS and CAD patients. No differences in morning and evening energy levels were seen from admission to discharge (both p > 0.05). Significant difference in morning and evening ratings was seen, independent of sex and age (all p < 0.0001). Data are presented as the mean of individual data points (with 95% confidence interval) or as mean ± SD. Two-way repeated-measures ANOVA was performed to analyze morning and evening ratings (averaged across all patients) over the entire rehabilitation process as well as for subgroup analyses. Comparison of morning and evening ratings was performed using paired t-test. The trend line was modeled using linear regression slopes.

Figure 3

Diary energy levels correlate with Multidimensional Fatigue Inventory-20 (MFI-20) scores. Fatigue of PCS patients was assessed by MFI-20 (score 0–100, higher values = higher fatigue) at admission (A–D) and before discharge (E–H) and compared with mean daily energy levels assessed by the fatigue diary (N = 58). Each data point represents an individual measurement. Correlations were performed using Spearman rank correlation. The trend line indicates linear regression.

Figure 4

The post-COVID-19 syndrome (PCS) energy diary indicates changes in patients’ energy level subsequent to therapy. (A–D) Energy levels before and after individual patient's therapies (N = 33) were compared by type of therapy. (E) A representative daily progression is depicted with therapies and respective changes in energy level. On average, active therapies reduced energy levels by ∼5% while passive therapies regenerated energy levels to a similar extent. A larger energy drain (∼20%) was seen after cardiopulmonary exercise testing (CPET). In total, PCS patients performed 1,926 active, 337 passive, and 488 cognitive therapies during a mean of 29.9 ± 5.7 rehabilitation days. Active therapies included all physical and respiratory therapies, passive therapies included relaxation therapies, and cognitive therapies included cognitive training, disease education, and talks. CPET was listed separately to analyze the effect of strenuous physical activity on energy levels. Data are presented as mean ± SD and were analyzed using paired t-test.