Early experiences of rehabilitation for patients post-COVID to improve fatigue, breathlessness exercise capacity and cognition
Bibliographic record
Abstract
Introduction: COVID-19 can lead to a number of lasting symptoms such as breathlessness, fatigue and ability to engage in activities of daily living. The European Respiratory Society taskforce identified the need for rehabilitation to aid recovery for patients with lasting symptoms of COVID-19. Methods: Ethical approval was gained for this study (reference 17/EM/0156). Patients were referred post discharge or by their GP. The six week, twice supervised rehabilitation programme comprised of aerobic and strength training and education using www.yourcovidrecovery.nhs.uk. The outcomes were: Incremental and Endurance Shuttle Walking Test (ISWT/ESWT), Functional Assessment of Chronic Illness Therapy- Fatigue Score (FACIT), COPD Assessment Test (CAT), Montreal Cognitive Assessment (MoCA), Hospital Anxiety and Depression Scale and the EuroQual Thermometer (EQ5D). Results: 30 patients were analysed following a COVID-19 rehabilitation programme (52% male, mean [SD] age 58[16] years, length of stay 10[14] days). There were statistically significant improvements in the ISWT mean [SD] 112[105]m, ESWT 544[377], FACIT 5[7], CAT 3[6], MoCA 2[2] and EQ5D 8[19]. There were no significant improvements in the HADS however baseline scores were low (mean[SD] 6[4]). Conclusion: Patients post COVID-19 demonstrated improvements in symptoms, fatigue, cognition and exercise capacity following a rehabilitation programme.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".