Do Provincial Formulary Restrictions Explain Differential Uptake of Sodium-Glucose Cotransporter-2 Inhibitors in Adults With Diabetes and Cardiovascular Disease in Canada? A Retrospective Cohort Study of Pharmacy Claims
Bibliographic record
Abstract
OBJECTIVES: Ontario listed sodium-glucose cotransporter-2 inhibitors (SGLT2is) as a regular public drug benefit for adults ≥65 years of age, whereas other Canadian provinces providing benefits for SGLT2is have implemented special authorization restrictions. We hypothesized that special authorization led to lower SGLT2i use among older adults with diabetes and cardiovascular disease (CVD) in other provinces (Alberta, Manitoba, New Brunswick, and Saskatchewan) as compared with Ontario. METHODS: We performed a retrospective cohort study of adults with diabetes and CVD who were ≥65 years of age and discharged from hospital between April 1, 2016, and March 31, 2019, in 5 Canadian provinces. Data were obtained from a national discharge database linked with public pharmacy claims. We followed individuals from discharge until March 31, 2019, for SGLT2i uptake. We also examined SGLT2i discontinuation and sulfonylurea uptake as control outcomes. Fine-Gray hazard models were adjusted for comorbidities and area-level sociodemographics. RESULTS: Of 161,249 individuals (average age 78 years, 42% female, median follow-up 1.8 years), 68% were from Ontario and 32% were from other provinces. Cumulative SGLT2i uptake at 6 months was 2.2% in Ontario as compared with 0.7% in other provinces, with an adjusted hazard ratio (aHR) of 2.72 (95% confidence interval 2.56 to 2.94, p<0.001). Ontario residents had similar SGLT2i discontinuation or sulfonylurea uptake compared with other provinces. Other predictors of SGLT2i uptake were identified. CONCLUSIONS: There was an interprovincial disparity in SGLT2i uptake in older adults with diabetes and CVD, among whom SGLT2is are now indicated for cardiorenal benefit. Special authorization restrictions should be flexibly and rapidly reassessed and revised as new evidence of clinical benefits becomes available.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".