Sodium‐glucose co‐transporter‐2 inhibitors versus dipeptidyl peptidase‐4 inhibitors and the risk of heart failure: A nationwide cohort study of older adults with diabetes mellitus
Bibliographic record
Abstract
AIMS: To analyse the rate of heart failure hospitalization for older adults prescribed a sodium-glucose co-transporter-2 (SGLT2) inhibitor. MATERIALS AND METHODS: The study cohort included adults aged 66 years and older diagnosed with diabetes mellitus in Ontario, Canada, between July 2015 and March 2019, who received either an SGLT2 inhibitor or a dipeptidyl peptidase-4 (DPP-4) inhibitor. The primary outcome was a composite of heart failure hospitalization and all-cause mortality. Secondary outcomes included diabetic ketoacidosis and hypoglycaemia. RESULTS: A total of 29 916 adults prescribed an SGLT2 inhibitor were compared with 29 916 adults prescribed a DPP-4 inhibitor. The mean age was 72 years, 60% were men, the baseline glycated haemoglobin concentration was 8.2% and the baseline creatinine was 89 μmol/L. The incidence rate of the primary outcome was 19/1000 person-years for adults prescribed an SGLT2 inhibitor compared to 38/1000 person-years in those prescribed a DPP-4 inhibitor. This resulted in a hazard ratio (HR) of 0.49 (95% confidence interval [CI] 0.45, 0.54) and a rate difference (RD) of 19 fewer events per 1000 person-years (RD -19 [95% CI -22, -17]). Patients prescribed an SGLT2 inhibitor also had a lower rate of hypoglycaemia (HR 0.61 [95% CI 0.46, 0.81); RD -1.6 [95% CI -2.4, -0.8]), but a higher rate of diabetic ketoacidosis (HR 1.84 [95% CI 1.26, 2.70]; RD 1.0 [95% CI 0.4, 1.6]). CONCLUSIONS: Older adults prescribed an SGLT2 inhibitor had a lower rate of heart failure hospitalization or death, and a lower rate of hypoglycaemia, but an increased rate of diabetic ketoacidosis compared to older adults prescribed a DPP-4 inhibitor.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".