Abstract 4145147: Prescription of Sodium-glucose cotransporter-2 inhibitors and Glucagon-like peptide-1 receptor agonists among Veterans with diabetes and cardiovascular disease

Background: Sodium-glucose cotransporter-2 inhibitors (SGLT2i) and Glucagon-like peptide-1 receptor (GLP-1) agonists (GLP-1a) improve cardiovascular (CV) health outcomes among individuals with type 2 diabetes and CV disease. US military Veterans have a higher prevalence of both diabetes and CV disease than the general population. Understanding what rates of SGLT2i and GLP-1a prescription are in this population is important for identifying strategies to improve CV outcomes. Methods: Using data from the Veterans Affairs Corporate Data Warehouse data, we identified all Veterans with type 2 diabetes and at least one of the following conditions – coronary artery disease, peripheral arterial disease, cerebrovascular disease/stroke, or congestive heart failure (either reduced or preserved ejection fraction). The study population was limited to people with active care with a primary care, cardiology, or endocrinology provider. We then examined trends in prescription of SGLT2i and GLP-1a from 2017 to 2022. Prescription rates among subgroups of gender and race were also evaluated. Differences between groups were compared using Chi-squared tests. Results: A total of 826,590 Veterans with both diabetes and CV disease were identified. Prescription rates of SGLT2i increased from 1.6% in 2017 to 22.3% in 2022 while GLP-1a rates increased from 2.0% to 12.0%. As of 2022, prescription rates of SGLT2i were similar between men and women (22.2% vs. 22.8%) while rates for GLP-1a were lower among men (11.8% vs. 18.6%, p<0.001). Among race subgroups, prescription rates were similar, but Black Veterans had the lowest rates for both categories of medications compared to white Veterans: 22.1% vs. 22.4%, p=0.03 for SGLT2i and 10.6% vs. 12.4%, p<0.001 for GLP-1a. Conclusions: Although prescription rates of SGLT2i or GLP-1a among Veterans with diabetes and CV disease have rose considerably between 2017 and 2022, as of 2022, a substantial proportion of Veterans with diabetes and CV disease were yet to be prescribed SGLT2i or GLP-1a. There also existed some disparities based on gender and race in prescription rates. Identifying, and removing, barriers towards prescribing these medications is crucial for improving the CV health of Veterans.

Authors

Institutions

Publication Details

Journal
Circulation
Published
2024-11-12
DOI
https://doi.org/10.1161/circ.150.suppl_1.4145147
Primary Topic
Diabetes Treatment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 4145147: Prescription of Sodium-glucose cotransporter-2 inhibitors and Glucagon-like peptide-1 receptor agonists among Veterans with diabetes and cardiovascular disease

Lauren A. Eberly, Jingyi Wu, Sameed Ahmed M. Khatana, Fatima Qaisrani
2 links
Circulation
Diabetes Treatment and Management
article

Abstract 4145147: Prescription of Sodium-glucose cotransporter-2 inhibitors and Glucagon-like peptide-1 receptor agonists among Veterans with diabetes and cardiovascular disease

Lauren A. Eberly, Jingyi Wu, Sameed Ahmed M. Khatana, Fatima Qaisrani
article en

Abstract

Background: Sodium-glucose cotransporter-2 inhibitors (SGLT2i) and Glucagon-like peptide-1 receptor (GLP-1) agonists (GLP-1a) improve cardiovascular (CV) health outcomes among individuals with type 2 diabetes and CV disease. US military Veterans have a higher prevalence of both diabetes and CV disease than the general population. Understanding what rates of SGLT2i and GLP-1a prescription are in this population is important for identifying strategies to improve CV outcomes. Methods: Using data from the Veterans Affairs Corporate Data Warehouse data, we identified all Veterans with type 2 diabetes and at least one of the following conditions – coronary artery disease, peripheral arterial disease, cerebrovascular disease/stroke, or congestive heart failure (either reduced or preserved ejection fraction). The study population was limited to people with active care with a primary care, cardiology, or endocrinology provider. We then examined trends in prescription of SGLT2i and GLP-1a from 2017 to 2022. Prescription rates among subgroups of gender and race were also evaluated. Differences between groups were compared using Chi-squared tests. Results: A total of 826,590 Veterans with both diabetes and CV disease were identified. Prescription rates of SGLT2i increased from 1.6% in 2017 to 22.3% in 2022 while GLP-1a rates increased from 2.0% to 12.0%. As of 2022, prescription rates of SGLT2i were similar between men and women (22.2% vs. 22.8%) while rates for GLP-1a were lower among men (11.8% vs. 18.6%, p<0.001). Among race subgroups, prescription rates were similar, but Black Veterans had the lowest rates for both categories of medications compared to white Veterans: 22.1% vs. 22.4%, p=0.03 for SGLT2i and 10.6% vs. 12.4%, p<0.001 for GLP-1a. Conclusions: Although prescription rates of SGLT2i or GLP-1a among Veterans with diabetes and CV disease have rose considerably between 2017 and 2022, as of 2022, a substantial proportion of Veterans with diabetes and CV disease were yet to be prescribed SGLT2i or GLP-1a. There also existed some disparities based on gender and race in prescription rates. Identifying, and removing, barriers towards prescribing these medications is crucial for improving the CV health of Veterans.

CirculationVol. 150(Suppl_1)
University of Pennsylvania (US)
Good health and well-being
Openalex Percentile: Top 68%
Diabetes Treatment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.