Use of sodium‐glucose cotransporter‐2 inhibitors among older adults with type 2 diabetes mellitus in British Columbia
Bibliographic record
Abstract
AIMS: Clinical guidelines recommend sodium-glucose cotransporter-2 inhibitors (SGLT2is) for individuals with type 2 diabetes mellitus (T2DM) and established or high risk of cardiorenal disease. This study examined real-world SGLT2i use patterns among older adults with T2DM in British Columbia, Canada. MATERIALS AND METHODS: We conducted a drug utilisation study on all individuals aged ≥75 years with T2DM in British Columbia between January 1, 2016, and December 31, 2023, using administrative healthcare databases. We examined prevalence, incidence, characteristics of incident users, and discontinuation. RESULTS: The prevalence of SGLT2i use increased gradually from 2.0% in the first half of 2016 to 14% in the second half of 2022, then more sharply to 21% in the second half of 2023, with comparable prevalence in individuals with and without cardiorenal disease (20% vs. 22% in 2023). SGLT2i initiation increased from 1.3 to 2.8 per 1000 individuals between 2016 and 2022, spiked to 5.4 per 1000 individuals in January 2023, and then stabilised. Of the 14 320 SGLT2i initiators between 2021 and 2023, 62% had cardiorenal disease, most used other glucose-lowering drugs concomitantly (particularly metformin [68%], sulfonylureas [39%], and insulins [19%]), and 62% were started on treatment by a general practitioner. Additionally, 17% discontinued treatment within a year. CONCLUSIONS: SGLT2i use among older adults with T2DM in British Columbia increased steadily from 2016 to 2022, followed by a spike in 2023, aligned with the expansion in publicly funded drug coverage. By the end of 2023, around one in five used SGLT2is, regardless of cardiorenal disease status.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".