Background/Objectives: Sodium-glucose cotransporter 2 (SGLT2) inhibitors provide well-established cardiovascular and renal benefits in heart failure (HF), type 2 diabetes (T2DM), and chronic kidney disease (CKD). Although emerging trials suggest potential value after acute myocardial infarction (AMI), SGLT2 inhibitors currently have no formal indication for AMI, and real-world prescribing patterns in this setting remain uncharacterized. This study aimed to evaluate in-hospital and post-discharge prescribing patterns and clinical predictors of SGLT2 inhibitor initiation among AMI patients eligible for therapy based on guideline-supported indications. Methods: We conducted a retrospective cohort study including 244 consecutive AMI patients hospitalized between January 2023 and July 2024. A total of 180 (73.7%) met guideline-based eligibility criteria for SGLT2 inhibitors. Four multivariable logistic regression models were developed to identify independent predictors of SGLT2 inhibitor prescription. Results: A total of 117 patients (65%) received SGLT2 inhibitors and 63 (35%) remained untreated. Receivers were more frequently male (81% vs. 65%) and exhibited lower left ventricular ejection fraction (LVEF) (38.2 ± 6.7% vs. 42.4 ± 8.3%), larger ventricular volumes, and higher Killip class at presentation. HF patients with preserved ejection fraction (HFpEF) were markedly undertreated (25.9%) compared with mid-range (HFmrEF) (69.8%) or reduced (HFrEF) (73.7%). Across all models, HFpEF was a strong negative predictor of prescribing (OR 0.071-0.081, p Conclusions: In this real-world AMI cohort, SGLT2 inhibitors were prescribed primarily in relation to established indications for HF, T2DM, and CKD, yet their use remained highly variable in the absence of a dedicated recommendation for AMI. Significant therapeutic gaps were observed in HFpEF and high-risk cardiometabolic profiles, underscoring the need for clearer guidance and standardized pathways to support consistent initiation in eligible patients after MI.
Building similarity graph...
Analyzing shared references across papers
Loading...
Suciu et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69a75c8bc6e9836116a25801 — DOI: https://doi.org/10.3390/jcm15031056
Ioana Suciu
Teodora Mateoc-Sirb
Constantin Luca
Journal of Clinical Medicine
Clinical Emergency Hospital Bucharest
Victor Babeș University of Medicine and Pharmacy Timișoara
Institute e-Austria Timisoara
Building similarity graph...
Analyzing shared references across papers
Loading...