Safety of sodium‐glucose co‐transporter‐2 inhibitors on amputation across categories of baseline cardiovascular disease and diuretics use in patients with type 2 diabetes
Bibliographic record
Abstract
AIM: To assess the risk of amputation associated with sodium-glucose co-transporter-2 inhibitors (SGLT2is) among patients with type 2 diabetes, across categories of baseline cardiovascular disease (CVD) and diuretic use (DU). MATERIALS AND METHODS: We conducted an active comparator, new-user cohort study using Korea's nationwide claims data (2015-2020). The study cohort consisted of patients with type 2 diabetes who initiated SGLT2is or dipeptidyl peptidase-4 inhibitors (DPP4is). Cohort entry was defined by first prescription date. We then classified patients into four discrete subcohorts based on their baseline status of CVD and DU as (1) CVD+/DU+, (2) CVD+/DU-, (3) CVD-/DU+ and (4) CVD-/DU-. We performed 1:1 propensity score (PS) matching within each cohort and estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for the risk of amputation with SGLT2is versus DPP4is using Cox models. RESULTS: We identified 219 900 PS-matched pairs of SGLT2is and DPP4is (CVD+/DU+, n = 11 719; CVD+/DU-, n = 26 092; CVD-/DU+, n = 26 894; and CVD-/DU-, n = 155 195), with well-balanced baseline covariates across all cohorts. Significantly lower risks of amputation with SGLT2is versus DPP4is were found in CVD+/DU+ (HR 0.36, 95% CI 0.14-0.90), CVD+/DU- (0.45, 0.21-0.99) and CVD-/DU- (0.48, 0.33-0.70), but not in CVD-/DU+ (0.54, 0.26-1.12). Consistent trends in estimates were found across various sensitivity analyses. CONCLUSIONS: Initiating SGLT2is against DPP4is did not increase the risk of amputation across patient populations of varying vulnerability. These findings based on routine practice will reassure clinicians of the safety of SGLT2is with regard to amputation risk in selected high-risk patients with type 2 diabetes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".