Relationship between post-COVID-19 symptoms and daily physical activity
Bibliographic record
Abstract
Background Exertion-intolerant symptoms common in post-COVID-19 syndrome (PCS), often resembling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), challenge conventional rehabilitation and highlight the need for research into the poorly understood relationship between PCS symptoms and physical activity. Objectives We aimed to investigate the longitudinal associations between PCS symptoms and physical activity (same and following day), while accounting for the presence of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) symptoms. Additionally, to compare the characteristics and outcomes of PCS patients with and without ME/CFS symptoms. Methods Adults with PCS participated in an in-person evaluation that included assessment of dyspnea (Borg scale), fatigue (Fatigue Severity Scale), ME/CFS symptoms screening (DePaul Symptom Questionnaire), and functional capacity. Participants were also instructed to complete a daily PCS symptoms survey and wear a smartwatch for a week to track daily physical activity (step count). Results Eighteen individuals with PCS (78% females, 51 ± 11 years) participated in the study, averaging 4,067 steps per day (95%CI 3,638–4,497) over 117 days of valid data. Individuals with ME/CFS symptoms (n = 11) reported more severe PCS symptoms and had lower functional capacity than those without ME/CFS symptoms. After adjusting for ME/CFS symptoms, greater dizziness was associated with fewer steps on the same [OR 0.94 (95%CI 0.88–0.99), p = 0.026] and following day [OR 0.91 (95%CI 0.84–0.98), p = 0.016]. Lower levels of fatigue [OR 0.69 (95%CI 0.49–0.99), p = 0.043] and chest pain [OR 0.76 (95%CI 0.57–0.99), p = 0.048] were associated with walking ≥5,000 steps on the previous day. Conclusion Regardless of the presence of ME/CFS symptoms, dizziness was negatively associated with physical activity on both the same and following day in PCS individuals. Additionally, lower levels of fatigue and chest pain were linked to walking 5,000 steps or more the previous day. Impact These results provide insights into the relationships between symptoms and daily physical activity in PCS, which can help tailor interventions and improve the management of this condition. This research also highlights the value of using wearable devices and smartphone apps to collect data for monitoring individuals with PCS over time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".