Abstract 13531: Uptake of SGLT2i and Outcomes in Patients With Diabetes and Chronic Heart Failure: A Community-Based Cohort and a Specialized Clinic Cohort
Bibliographic record
Abstract
Introduction: Sodium/glucose cotransporter 2 inhibitors (SGLT2i) have an established benefit in people with diabetes mellitus (DM) and chronic heart failure (HF). We aimed to evaluate the uptake and impact of these agents in two cohorts: a community-based cohort of all adults with DM and HF in Alberta who had an echocardiogram and a cohort of people with DM and HF being cared for in a specialized heart failure clinic (HFC). Methods: We identified the community-based cohort using validated ICD code-based case definitions for DM and HF (physician claims, outpatient, hospitalization databases) with an echocardiogram study (available from two major centres) from 2015 (when SGLT2i were available provincially) to March 2022. In addition, we identified the HFC cohort by chart review of patients seen in the Mazankowski Alberta Heart Institute HFCconsented between February 2018 and August 2021 with HF and DM and followed them until August 2022. We examined the association between SGLT2i use and all-cause mortality and/or cardiovascular (CV)-related hospitalizations using Cox proportional hazard models adjusted for clinical covariates and time-varying SGLT2i use. Results: In 12,150 people with DM and HF in the community-based cohort, 2,321 (19.1%) were dispensed an SGLT2i compared to 208 (39.2%) of the 530 patients with DM and HF followed in the HFC. SGLT2i was associated with less CV-related hospitalization and all-cause mortality (the composite outcome) (aHR 0.65 [95%CI 0.58 - 0.73]) in the community but no difference (aHR 0.88 [95% CI 0.64 - 1.21] in the HFC. SGLT2i use was associated with less all-cause mortality (aHR 0.50 [95% CI 0.44 - 0.57]) in the community but no difference (aHR 0.81 [95% CI 0.54 - 1.20]) in the HFC. Conclusion: Despite robust randomized trial evidence of clinical benefit, the uptake of SGLT2i even in people with DM and HF remains low. Although uptake is higher in a specialized HFC overall the rate is below optimal. Multifaceted Strategies (targeted to healthcare professionals, patients, and policymakers) to guide risk identification and raise awareness on the clinical benefits of these agents are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".