Abstract 4367615: The Cardiovascular Paradox of Gout Prophylaxis: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Introduction: Colchicine and NSAIDs are commonly used as flare prophylaxis during urate-lowering therapy (ULT) in gout, a chronic inflammatory condition linked to elevated cardiovascular risk. Oxidative stress and endothelial dysfunction may contribute to major adverse cardiovascular events (MACE). Although colchicine shows cardioprotective effects in non-gout populations and NSAIDs remain widely used despite risks, their effect on MACE in gout patients is unclear. Research Question: Does flare prophylaxis with colchicine or NSAIDs alter the cardiovascular risk profile in patients with gout initiating ULT therapy? Methods: This review followed PRISMA guidelines and was registered in PROSPERO (CRD420251017700). MEDLINE, EMBASE, and CENTRAL were searched through April 2025 for studies of gout patients initiating ULT with flare prophylaxis using colchicine, NSAIDs, or no prophylaxis. Studies involving non-gout crystal arthropathies, isolated hyperuricemia, or prophylaxis without ULT were excluded. The primary outcome was MACE, defined as a composite of all-cause mortality, myocardial infarction, stroke, and coronary revascularization. Log-transformed hazard ratios (HRs) were pooled using a random-effects meta-analysis. Results: Five studies from the UK, US, and Canada were included: three retrospective cohorts, one observational reanalysis of an RCT, and one target trial emulation. To avoid duplication with Cipolletta et al., only the CPRD GOLD subset was extracted from Roddy et al. Across four studies, 148,345 gout patients were included, with Singh et al. reporting 10,195 person-years of follow-up. Among them, 37,168 (25.1%) received colchicine and 19,461 (13.1%) received NSAIDs. Colchicine prophylaxis was not significantly associated with MACE risk compared to no prophylaxis [log(HR) = 0.005; 95% CI: -0.21 to 0.22, Figure 1]. NSAIDs also showed no significant difference [log(HR) = 0.19; 95% CI: -0.18 to 0.57, Figure 2]. Risk was similar between colchicine and NSAID groups [log(HR) = -0.02; 95% CI: -0.32 to 0.28, Figure 3]. Conclusion: Our meta-analysis found that flare prophylaxis with colchicine or NSAIDs did not reduce cardiovascular event risk in gout patients. These findings may contradict recent evidence of colchicine’s cardioprotective effects compared to NSAIDs. Further studies are needed to guide cardiovascular risk management in this high-risk population.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".