Comparative Effectiveness of Sodium–Glucose Cotransporter-2 Inhibitors for Recurrent Gout Flares and Gout-Primary Emergency Department Visits and Hospitalizations
Bibliographic record
Abstract
BACKGROUND: Sodium-glucose cotransporter-2 inhibitors (SGLT2is) decrease serum urate levels, but whether this translates into prevention of recurrent flares among patients with gout and gout-primary emergency department (ED) visits or hospitalizations is unknown. OBJECTIVE: To compare gout flares and cardiovascular events among patients with gout initiating SGLT2is versus dipeptidyl peptidase 4 inhibitors (DPP-4is), another second-line glucose-lowering agent not associated with serum urate levels or cardiovascular risk. DESIGN: Propensity score-matched, new-user cohort study. SETTING: General population database from 1 January 2014 to 30 June 2022. PARTICIPANTS: Patients with gout and type 2 diabetes. MEASUREMENTS: The primary outcome was recurrent gout flare counts ascertained by ED, hospitalization, outpatient, and medication dispensing records. Secondary outcomes included myocardial infarction and stroke; genital infection (positive control) and osteoarthritis encounter (negative control) were also assessed. Poisson and Cox proportional hazards regressions were used with 1:1 propensity score matching (primary analysis) and overlap weighting (sensitivity analysis). RESULTS: After propensity score matching, the flare rate was lower among SGLT2i initiators than DPP-4i initiators (52.4 and 79.7 events per 1000 person-years, respectively), with a rate ratio (RR) of 0.66 (95% CI, 0.57 to 0.75) and a rate difference (RD) of -27.4 (CI, -36.0 to -18.7) per 1000 person-years. The corresponding RR and RD for gout-primary ED visits and hospitalizations were 0.52 (CI, 0.32 to 0.84) and -3.4 (CI, -5.8 to -0.9) per 1000 person-years, respectively. The corresponding hazard ratio (HR) and RD for myocardial infarction were 0.69 (CI, 0.54 to 0.88) and -7.6 (CI, -12.4 to -2.8) per 1000 person-years; the HR for stroke was 0.81 (CI, 0.62 to 1.05). Those who initiated SGLT2is showed higher risk for genital infection (HR, 2.15 [CI, 1.39 to 3.30]) and no altered risk for osteoarthritis encounter (HR, 1.07 [CI, 0.95 to 1.20]). Results were similar when propensity score overlap weighting was applied. LIMITATION: Participants had concurrent type 2 diabetes. CONCLUSION: Among patients with gout, SGLT2is may reduce recurrent flares and gout-primary ED visits and hospitalizations and may provide cardiovascular benefits. PRIMARY FUNDING SOURCE: National Institute of Arthritis and Musculoskeletal and Skin Diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".