Chronic fatigue and post-exertional malaise in people living with long COVID
Bibliographic record
Abstract
Abstract Purpose People living with long COVID describe a high symptom burden, and a more detailed assessment of chronic fatigue and post-exertional malaise (PEM) may inform the development of rehabilitation recommendations. The aims of this study were to use validated questionnaires to measure the severity of fatigue and compare this with normative data and thresholds for clinical relevance in other diseases; measure and describe the impact of PEM; and assess symptoms of dysfunctional breathing, self-reported physical activity/sitting time, and health-related quality of life. Methods This was an observational study involving an online survey for adults living with long COVID (data collection from February-April, 2021) following a confirmed or suspected SARS-CoV-2 infection. Questionnaires included the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F) and DePaul Symptom Questionnaire-Post-Exertional Malaise. Results After data cleaning, n =213 participants were included in the analysis. Participants primarily identified as women (85.5%), aged 40-59 (78.4%), who had been experiencing long COVID symptoms for ≥6 months (72.3%). The total FACIT-F score was 18±10 (where the score can range from 0-52, and a lower score indicates more severe fatigue), and 71.4% were experiencing chronic fatigue. Post-exertional symptom exacerbation affected most participants, and 58.7% met the scoring thresholds used in people living with myalgic encephalomyelitis/chronic fatigue syndrome. PEM occurred alongside a reduced capacity to work, be physically active, and function both physically and socially. Conclusion Long COVID is characterized by chronic fatigue that is clinically relevant and is at least as severe as fatigue in several other clinical conditions, including cancer. PEM appears to be a common and significant challenge for the majority of this patient group. Patients, researchers, and allied health professionals are seeking information on safe rehabilitation for people living with long COVID, particularly regarding exercise. Fatigue and post-exertional symptom exacerbation must be monitored and reported in studies involving interventions for people with long COVID.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".