Examining anti-inflammatory therapies in the prevention of cardiovascular events: protocol for a systematic review and network meta-analysis of randomised controlled trials
Bibliographic record
Abstract
Introduction Inflammation is emerging as an important risk factor for atherosclerotic cardiovascular disease and has been a recent target for many novel therapeutic agents. However, comparative evidence regarding efficacy of these anti-inflammatory treatment options is currently lacking. Methods and analysis This systematic review will include randomised controlled trials evaluating the effect of anti-inflammatory agents on cardiovascular outcomes in patients with known cardiovascular disease. Studies will be retrieved from Medline, Embase, the Cochrane Central Register of Controlled Trials, as well as clinical trial registry websites, Europe PMC and conference abstract handsearching. No publication date or language restrictions will be imposed. Eligible interventions must have some component of anti-inflammatory agent. These include (but are not limited to): non-steroidal anti-inflammatory drugs (NSAIDs), colchicine, prednisone, methotrexate, canakinumab, pexelizumab, anakinra, succinobucol, losmapimod, inclacumab, atreleuton, LP-PLA 2 (darapladib) and sPLA 2 (varespladib). The primary outcomes will include major adverse cardiac events (MACE), and each individual component of MACE (myocardial infarction, stroke and cardiovascular death). Key secondary outcomes will include unstable angina, heart failure, all-cause mortality, cardiac arrest and revascularisation. Screening, inclusion, data extraction and quality assessment will be performed independently by two reviewers. Network meta-analysis based on the random effects model will be conducted to compare treatment effects both directly and indirectly. The quality of the evidence will be assessed with appropriate tools including the Grading of Recommendations, Assessment, Development and Evaluation profiler or Confidence in Network Meta-Analysis tool. Ethics and dissemination Ethics approval is not required for this systematic review. The findings will be disseminated through a peer-reviewed journal. PROSPERO registration number CRD42022303289.
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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 | 0.093 | 0.146 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.030 | 0.036 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.052 | 0.005 |
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".