MON-LB029 The Influence of SGLT-2 Inhibitors and Other Glucose-Lowering Therapies on All-Cause Mortality Risk and Cardiovascular Outcomes in Older Patients with Newly Treated Type 2 Diabetes: A Population-Based Cohort Study
Bibliographic record
Abstract
Background: SGLT-2 inhibitors (SGLT-2i) have been associated with decreased all-cause mortality and cardiovascular (CV) morbidity in patients with type 2 diabetes (T2DM) and established CV disease in randomized trials. The objective of this study was to evaluate exposure time to SGLT-2i and other diabetic therapies on all-cause mortality and cardiovascular outcomes in elderly patients with newly diagnosed T2DM. Methods: We conducted a retrospective analysis of patients > 67 years of age who were started on a glucose lowering drug (GLD) between August 1, 2015 and January 1, 2017 using population-based health administrative data. The primary outcome was time to death from any cause. Exposure to all drugs was captured as time-dependent covariates. Secondary outcomes included time to admission to hospital for a cardiovascular outcome. Results: During the study, 36,021 individuals started an GLD. The prevalence of MI and CHF at baseline were low (6.4% vs 9.2% respectively). SGLT-2i were first-line treatment in 3.5% of patients and 7.1% of patients were exposed at any time during the study period. The SGLT-2i group was younger (71.9+/-4.6 yrs vs 74.7+/- 6.2 yrs) with a higher prevalence of MI at baseline. In contrast to other GLDs, death risk decreased as the proportion of observation exposed to SGLT-2i and biguanides increased. The association between individual drug exposures and cardiovascular outcomes was similar. Discussion: In contrast to previous cohort studies, this study examined the independent influence of both SGLT-2i and all other possible GLD individually on mortality and CV risk and based on exposure time. This study suggests that SGLT-2i and biguanides are associated with a decreased risk of all-cause mortality and CV outcomes in patients newly diagnosed with T2DM. Further research is needed to elucidate the mechanism by which SGLT-2i improves mortality and CV outcomes. Unless otherwise noted, all abstracts presented at ENDO are embargoed until the date and time of presentation. For oral presentations, the abstracts are embargoed until the session begins. Abstracts presented at a news conference are embargoed until the date and time of the news conference. The Endocrine Society reserves the right to lift the embargo on specific abstracts that are selected for promotion prior to or during ENDO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".