Physical exercise as a treatment for persisting symptoms post covid infection
Bibliographic record
Abstract
Abstract Background and purpose Subsequent to the health problems of the acute phase of SARS-CoV-2 infection, the long-term consequences of SARS-CoV-2 infection are affecting large numbers of patients worldwide. To date, no evidence-based treatment is available for the increasing number of patients with persisting symptoms post COVID 19 infection. We hypothesized that physical exercise may represent a safe and effective treatment option post COVID. Methods We performed a systematic search of the literature that revealed a lack of randomized training studies in patients post COVID. Based on these findings a prospective randomized controlled study with open-label and blinded endpoint evaluation was designed. 272 patients with symptoms of fatigue persisting over 6 weeks post COVID infection were screened. Patients with cardiovascular findings were excluded. 44 patients consented and were randomized to four weeks of supervised personalized strength endurance training for 4 weeks or usual care (Fig.1). The mean age was 42.7±13.4 years, and 61% were females. Results The individualized combined training was very well tolerated by the participants and the exercise compliance (quality of training) was high at 96.7 ± 2.0 %. There were no adverse events related to the training. Spirometric analysis showed a significantly higher increase in VO2peak (exercise: 10.0±12.7% vs. control: 0.1±8.9%, p<0.01) and oxygen-pulse (exercise: 9.8±10.8% vs. control: 0.0±13.9%, p<0.05) indicating the training effects of the intervention (Fig.2). Parameters of the Multidimensional Fatigue inventory-20 (MFI-20), the McGill Quality of Life Questionnaire (MQOL), and the Post-COVID-19 Functional Status (PCFS) were significantly improved after 4 weeks in both groups. The improvements in fatigue and quality of life were not statistically different between the training and usual care groups. Conclusion An individualized exercise program is a safe and well-tolerated treatment option in patients with persisting symptoms post-Covid. These patients significantly improve in physical performance after 4 weeks compared to patients without exercise intervention. Fatigue and quality of life improve over time in individuals that are willing to participate in a training study irrespective of allocation to the training group.Fig. 1:Flow diagram of the inclusion process in the PCTS studyFig. 2:Changes in relative oxygen uptake, oxygen pulse, and MFI-20 of the exercise and the control group between T0: baseline visit and T1: after exercise intervention or after the corresponding period in the control group. The red line represents the mean.*: p<0.05; **: p<0.01 ***: p<0.001, ****: p<0.0001, #: p<0.05 percentual change between groups.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".