Effect of Physical Activity/Exercise Interventions on Immune Parameters, and Inflammatory Markers for Proxy Conditions Among Adults Prone to COVID-19: A Systematic Review Protocol
Bibliographic record
Abstract
Abstract BackgroundOlder individuals (over 60 years) with hypertension, diabetes, cardiovascular disease, chronic respiratory disease, and cancer are at the highest risk of contracting and dying from Coronavirus (COVID-19). Compromised immunity (both innate and adaptive) and increased inflammatory response (cytokine-storm syndrome) are predictors for high mortality among this population group. Exercise/physical activity seems to be a plausible way to decrease both the risk of transmission and mortality, and improve health outcomes among this population since there is no available treatment for COVID-19. The study will investigate the effectiveness of physical activity/exercise in improving the immune parameters and reducing the inflammatory biomarkers in proxy conditions that make individuals susceptible to COVID-19.MethodsThe Preferred Reporting Items for systematic reviews and Meta-Analyses Protocol (PRISMA-P) 2015 will guide this review. We will search ten databases (until August 2020) to include randomized control trials articles that explored the effectiveness of physical activity/exercise in improving immune parameters and reducing inflammatory biomarkers in proxy conditions (hypertension, diabetes, cardiovascular disease, chronic respiratory disease and cancer). Two review authors will independently screen citations (title and abstract), extract data (using standardized forms), assess the risk of bias (using Cochrane risks of bias) and quality of data (using GRADE). Homogenous studies will be analyzed using the fixed-effect model of meta-analysis, while a narrative synthesis will be conducted for heterogeneous studies.DiscussionThere are no specific physical activity/exercise parameters (frequency, intensity, type of exercise and time- FITT) for interventionists to use when developing high-quality RCT for individuals vulnerable to COVID-19. Therefore, it is important to review the literature to identify and highlight the exercise FITT parameters that increase the immune outcomes and reduce inflammatory biomarkers for proxy conditions that make individuals susceptible to COVID-19. It is also important to identify the specific exercise regimen suitable and beneficial for each proxy group.Systematic review registrationPROSPERO CRD42020196907
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.036 | 0.055 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.020 | 0.020 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.060 | 0.006 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".