OP0156 INITIATION OF SODIUM-GLUCOSE COTRANSPORTER-2 INHIBITORS AND RECURRENT GOUT FLARES IN GOUT PATIENTS WITH TYPE 2 DIABETES: A GENERAL POPULATION-BASED COHORT STUDY
Bibliographic record
Abstract
Background Gout flares may increase risk of cardiovascular events.[1] Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are associated with lower risk of incident gout (primary prevention); however, their role in recurrent flares among gout patients (secondary prevention), and their cardiovascular risk remains unknown. Objectives To assess rate of recurrent gout flares in prevalent gout patients with type 2 diabetes initiating SGLT2i versus dipeptidyl peptidase-4 inhibitors (DPP4i), two second-line glucose-lowering agents for type 2 diabetes. Methods This new-user, active comparator cohort study used administrative health data covering nearly all residents of British Columbia, Canada from Jan 2014 to June 2022, including all dispensed prescriptions, regardless of funder. Primary outcome was recurrent gout flare counts, ascertained by emergency department (ED), hospitalization, outpatient, and medication dispensing records.[1] We also restricted to flares requiring hospitalization or ED visit, and stratified by sex, age, gout intensity (presence of ≥1 gout-coded encounter or colchicine dispensing over past year) and diuretic and urate-lowering therapy (ULT) use. Myocardial infarction and stroke were secondary outcomes. We also assessed genital infection as positive control and osteoarthritis as negative control. Poisson and Cox proportional hazards models were used with 1:1 propensity matching. Results We included 8150 gout patients with type 2 diabetes (mean age 66, 71% male, 59% with cardiovascular disease). Flare rate was lower among SGLT2i initiators (52.4 events per 1000 person-years) than DPP4i initiators (79.7 events per 1000 person-years): rate ratio (RR) 0.66 (95% CI: 0.57, 0.75) and rate difference (RD) -27.4 (-36.0, -18.7). RR and RD for flares requiring hospitalization or ED visit were 0.52 (0.32, 0.84) and -3.4 (-5.8, -0.9), respectively. Results were consistent regardless of sex or age (Table 1). RR was also consistent regardless of baseline gout intensity or diuretic or ULT use, though absolute RD was higher in patients with greater gout intensity: -71.6 [-111.1, -32.1] vs. 20.8 [-28.8, -12.7] per 1000 person-years, respectively. Hazard ratio (HR) and RD were 0.69 (0.54, 0.88) and -7.6 (-12.4, -2.8) per 1000 person-years for myocardial infarction; HR, 0.81 (0.62, 1.05) for stroke. For control outcomes, SGLT2i initiators had higher risk of genital infection, while there was no difference in risk of osteoarthritis (Table 1). Conclusion For gout patients, SGLT2i may offer pleiotropic cardiovascular and recurrent flare frequency benefits. Reference [1] Cipolletta et al. JAMA 2022 Acknowledgements: NIL. Disclosure of Interests Natalie McCormick: None declared, Chio Yokose: None declared, Jie Wei: None declared, Leo Lu: None declared, Deborah Wexler Consultant of: Served on Data Monitoring Committees for Novo Nordisk , J. Antonio Aviña-Zubieta: None declared, Mary De Vera: None declared, Yuqing Zhang: None declared, Hyon Choi Consultant of: Ironwood, Selecta, Horizon, Takeda, Kowa, and Vaxart., Grant/research support from: Ironwood and Horizon.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".