Effects of physical activity on the severity of illness and mortality in COVID-19 patients: A systematic review and meta-analysis
Bibliographic record
Abstract
Purpose: This systematic review and meta-analysis investigated the association between Physical activity (PA) before Coronavirus Disease 2019 (COVID-19) infection and the severity of illness and mortality in COVID-19 patients. Methods: A comprehensive search was undertaken to identify retrospective and nonrandomized controlled trial studies comparing the severity and mortality of COVID-19 infection among COVID-19 patients who had previously reported their participation in PA with those who had not. The databases searched were PubMed, Cochrane Library, Scopus, Science Direct, EMBASE, OPENGREY.EU, and ClinicalTrials.gov . The risk of bias was assessed using the Newcastle-Ottawa Scale. A random-effects model was used for determining pairwise meta-analyses. The protocol was registered with PROSPERO (CRD42021262548). Results: Eighteen studies met the inclusion criteria (5 cross-sectional, 12 cohort, and 1 case-control studies). All 1 618 680 subjects were adults. PA significantly decreased the risk of death in COVID-19 patients (odds ratio [OR] 0.34; 95% confidence interval [CI], 0.19–0.62; p < 0.001) and the risk of severe outcomes (OR 0.60; 95% CI, 0.48–0.76; p < 0.001). Subgroup analysis showed that PA for ≥150 min/wk at a moderate intensity or ≥75 min/wk at a vigorous intensity reduced the risks of severity and mortality. Vigorous PA reduced mortality risk, whereas moderate to vigorous PA reduced the risks of severity and mortality. Conclusion: PA before infection might reduce severity and mortality in COVID-19 patients, especially PA ≥ 150 min/wk of moderate activity or ≥75 min/wk of vigorous activity. However, careful interpretations should be considered due to the difference in PA patterns and severity definitions among included studies. This finding implies that engaging in regular PA, even in different patterns, has beneficial effects on the severity and mortality of COVID-19 patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".