Protocol for a systematic review of the associations between inflammatory markers and lung function, muscle force and exercise capacity in people with COPD
Bibliographic record
Abstract
INTRODUCTION: The prevalence of chronic obstructive pulmonary disease (COPD) has been on the rise, with acute exacerbation of COPD associated with the highest burden and multiple pulmonary and systemic consequences. People with COPD have been found to have an abnormal response of systemic inflammation. To date, although limited, there are studies that suggest negative associations between inflammatory markers and important clinical outcomes such as exercise capacity and muscle force. This protocol aims to systematically review the evidence for (i) the associations between inflammatory markers and lung function, muscle force and exercise capacity and (ii) the influence of other factors (eg, hospitalisation, exercise programme) on the level of inflammatory markers in people with COPD. METHODS AND ANALYSIS: Scopus, PubMed, Cochrane, Web of Science and ProQuest will be searched from database inception to February 2023 using PEO search strategy (Population: adults with COPD; Exposure: inflammatory markers; Outcomes: lung function, muscle force and exercise capacity). Four reviewers working in pairs will independently screen articles for eligibility and extract data that fulfilled the inclusion criteria. Depending on the design of the included studies, either Cochrane risk-of-bias version 2 or the Newcastle-Ottawa Scale tools will be used to rate the methodological quality of the included studies. Effect sizes reported in each individual study will be standardised to Cohen's d and a random effects model will be used to calculate the pooled effect size for the association. ETHICS AND DISSEMINATION: Ethical approval is unnecessary as this study will only use publicly available data. The findings will be disseminated through publication in peer-reviewed journals and conferences. PROSPERO REGISTRATION NUMBER: CRD42022284446.
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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 | 0.088 | 0.133 |
| Meta-epidemiology (narrow) | 0.008 | 0.007 |
| Meta-epidemiology (broad) | 0.024 | 0.020 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.123 | 0.016 |
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".