Glucagon-like peptide-1 receptor agonists in patients with heart failure with reduced ejection fraction – real world outcomes

Glucagon-like peptide-1 receptor agonists in patients with heart failure with reduced ejection fraction – real world outcomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Glucagon-like peptide-1 receptor agonists in patients with heart failure with reduced ejection fraction – real world outcomes Yoav Hammer, Ronen Arbel, Talish Razi, Doron Netzer, Jean Marc Weinstein, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6768681/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Background : The evidence regarding the effect of glucagon-like peptide-1 receptor agonists (GLP-1 RA) in patients with heart failure with reduced ejection fraction (HFrEF) is limited and conflicting, with some studies suggesting a favorable effect and some not. The aim of the study was to examine the safety and efficacy of GLP-1 RA therapy in a large national database of patients with HFrEF. Methods : In this observational retrospective cohort, data was obtained from the electronic medical records of Clalit Health Services, the largest health care organization in Israel. Between the years 2014 -2024, using a 1:1 matching, patients with HFrEF who were treated with GLP-1 RA were compared with those who were not. Outcomes included heart failure (HF) hospitalization and death. A subgroup analysis by body mass index (BMI), age, sex, HbA1C level and concomitant medications was conducted as well. Results : Out of 22,411 patients with HFrEF, 3023 initiated GLP-1 RA therapy after the diagnosis of HF was made. After a 1:1 nearest-neighbor matching, 3858 patients were matched and included in the study, with 1939 and 1919 patients in the GLP-1 RA group and the control group, respectively. Mean age of the cohort was 69, 33% female, and mean BMI was 29.9 kg/m 2 . While therapy with beta blockers and ACEI/ARB/ARNI was common within the cohort, only a third of the cohort was treated with SGLT2 inhibitors or mineralocorticoid receptor antagonists. Median follow-up time of the study was 30 months (17.06, 43.0). In a multivariable model which included multiple demographic and clinical variables, patients who were treated with GLP-1 RA were less likely to experience the primary outcome of death or HF hospitalization (HR 0.6, 0.53 – 0.68, p<0.001) compared with the control group. The subgroup analysis revealed a robust favorable effect of GLP-1 RA across the entire spectrum of patients with HFrEF. Conclusion : In this large cohort study of patients with HFrEF, GLP-1 RA therapy in addition to standard guideline directed medical therapy was associated with a lower rate of death and HF hospitalization. Future randomized trials are needed to confirm these results. Health sciences/Medical research/Outcomes research Health sciences/Health care/Prognosis/Disease-free survival Figures Figure 1 Figure 2 Introduction Although the pharmacological field in patients with heart failure with reduced ejection fraction (HFrEF) had greatly evolved over the past 2 decades, this patient population is still subjected to a relatively high incidence of death, heart failure (HF) hospitalization and reduced quality of life [ 1 ]. Glucagon-like peptide-1 receptor agonists (GLP-1 RA) include several medications which bind to a GLP-1 receptor and thereby promote insulin secretion, inhibit glucagon release and gastric emptying, and induce satiety [ 2 ]. Various GLP-1 RA differ in their structure and therefore differ in their dose, duration of action, mode of administration, and efficacy [ 3 ]. GLP-1 RA therapy has been investigated in several cohorts and was shown to decrease the likelihood of death and major adverse cardiac events as well renal outcomes [ 4 – 9 ]. However, as the prevalence of HF ranged from 9–24% in those studies, evidence regarding the effect of GLP-1 RA in patients with HF in general and HFrEF in particular, is scarce. While the recent publication of the STEP-HFpEF trials have provided evidence regarding the possible beneficial effect of GLP-1 RA in patients with heart failure with preserved ejection fraction (HFpEF) [ 10 , 11 ], there is still no robust evidence regarding the efficacy in those with HFrEF, as only 3 small clinical trials have examined the use of GLP-1 RA in patients with HFrEF [ 12 – 14 ], and none currently in progress. Furthermore, while GLP-1 RA do not feature as recommended therapy in patients with HFrEF per latest published HF guidelines [ 15 , 16 ], a substantial number of patients with HFrEF are treated with GLP-1 RA for indications other than HF. Therefore, the aim of this study was to examine the effectiveness of GLP-1 RA therapy in patients with HFrEF. Methods Study population – This retrospective cohort study was based on the Clalit Health Services database – the largest health care organization in Israel, which delivers universal healthcare coverage to two thirds of patients older than 65. To be included in the study, patients were required to have diabetes mellitus, a validated ICD-9 HF diagnosis (codes 428.x) and a documented left ventricular ejection fraction (LVEF) ≤ 40%. Next, patients were stratified into 2 groups – the treatment group and the control group. To be included in the treatment group, patients had to be treated with a GLP-1 RA; namely, liraglutide, exenatide, dulaglutide or semaglutide. To note, only patients who had 2 consecutive dispensed prescriptions for one of the GLP-1 RA were included in the treatment group. In order to examine the direct effect of GLP-1 RA on patients already diagnosed with HFrEF, only patients who started GLP-1 RA therapy after the date of systolic HF diagnosis were included in the treatment group. The control group included patients with HFrEF who were not treated with GLP-1 RA. Excluded from the study were patients who were treated with GLP-1 RA before a diagnosis of HFrEF was established, patients with heart failure with preserved EF (HFpEF), patients on hemodialysis, patients who underwent renal transplant, heart transplant or left-ventricular assist device implantation. Data extraction For this study, demographic, social, medical and laboratory data were extracted from the patient’s electronic medical record (EMR). For the purpose of including only patients with HFrEF, ejection fraction was extracted from the patient’s echocardiographic reports. Outcomes The primary outcome of the study was a composite outcome of death and HF hospitalization, which was defined as any hospitalization with a primary diagnosis of heart failure. Secondary outcomes evaluated in this study were all-cause death and HF hospitalization, separately. Data analysis The analysis was done in two stages: First, patients treated with GLP1A were matched 1:1 with untreated subjects. Individual matching of patients was conducted based on sex, age at HF diagnosis, and the year of HF diagnosis. Descriptive statistics were used to characterize the study participants. The index date was the initiation of GLP-1 RA therapy. In the second stage, time-dependent Cox regression analysis was used to assess the association between GLP-1 RA therapy and outcomes adjusting for additional variables: social sector, socio-economic status, BMI, chronic obstructive pulmonary disease (COPD) hypertension (HTN), history of cerebrovascular disease, peripheral arterial disease (PAD), ischemic heart disease (IHD), Hemoglobin A1C, estimated glomerual filtration rate (eGFR), and concurrent medications at baseline - angiotensin converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), mineralocorticoid receptor antagonists (MRA), angiotensin receptor-neprilysin inhibitor (ARNI), beta-adrenergic receptor blockers (BB), dipeptidyl peptidase IV inhibitors (DPP4i), insulin, metformin and sodium-glucose co-transporter-2 inhibitors (SGLT2i). Results Patient population A graphical depiction of the formation of the study cohort is presented in Supplementary Fig. 1. Between the years 2014–2024, a total of 22,411 patients met the inclusion and exclusion criteria of the study. Of these, 3023 were treated with GLP-1 RA (treatment group) and 19,388 were not treated with GLP-1 RA (control group). Out of those 22,411 patients, 1939 pairs were matched. No major differences between the 2 groups were noted with respect to baseline demographic characteristics (Table 1 ). Median age of the study cohort was 69 (63, 76), 67% were males and median follow-up time of the study was 30.8 months for both groups. In general, patients in the GLP-1 RA group tended to have more comorbidities, a higher hemoglobin A1C level and a higher BMI compared with the control group. In terms of medical therapy, patients in the GLP-1 RA group were more likely to be treated with guideline directed medical therapy (GDMT) and anti-diabetic medications. Table 1 – Baseline characteristics Characteristic Overall N = 3,858 GLP-1 RA N = 1,939 Control N = 1,919 p-value Demographic Age, median (IQR) 69 (63, 76) 69 (63, 76) 69 (63, 76) 0.2 Sex, n (%) > 0.9 Male 2,584 (67%) 1,297 (67%) 1,287 (67%) Female 1,274 (33%) 642 (33%) 632 (33%) Demographic sector, n (%) 0.3 Jews- General 2,900 (75%) 1,459 (75%) 1,441 (75%) Arabs 958 (25%) 480 (25%) 478 (25%) Socioeconomic score* 5.00 (4.0, 7.0) 5.00 (4.0, 7.0) 5.00 (4.0, 7.0) 0.7 Clinical characteristics Year started on GLP-1 RA therapy > 0.9 2014–2018 722 (19%) 362 (19%) 360 (19%) 2019–2024 3,136 (81%) 1,577 (81%) 1,559 (81%) BMI group (kg/m 2 ) < 0.001 18.5–25 598 (16%) 119 (6.1%) 479 (25%) 25–30 1,352 (35%) 594 (31%) 758 (39%) 30–40 1,595 (41%) 1,006 (52%) 589 (31%) 40+ 313 (8.1%) 220 (11%) 93 (4.8%) BMI, median (IQR) 29.9 (26.6, 34.2) 31.6 (28.3, 35.8) 28.1 (25.0, 31.8) < 0.001 COPD 731 (19%) 371 (19%) 360 (19%) 0.8 Hypertension 3,249 (84%) 1,701 (88%) 1,548 (81%) < 0.001 History of CVA/TIA 388 (10%) 160 (8.3%) 228 (12%) < 0.001 PVD 643 (17%) 341 (18%) 302 (16%) 0.12 Coronary heart disease 2,890 (75%) 1,502 (77%) 1,388 (72%) < 0.001 HbA1c 7.60 (6.50, 9.10) 8.50 (7.50, 9.70) 6.80 (6.20, 7.78) 60 1,923 (52%) 908 (47%) 1,015 (57%) eGFR (ml/min/1.73 m2), median (IQR) 62 (41, 84) 57 (38, 82) 66 (45, 86) < 0.001 Medical therapy ACEi/ARB 2,633 (68%) 1,389 (72%) 1,244 (65%) < 0.001 ARNI 517 (13%) 274 (14%) 243 (13%) 0.2 MRA 1,389 (36%) 793 (41%) 596 (31%) < 0.001 Beta-blockers 2,993 (78%) 1,604 (83%) 1,389 (72%) < 0.001 SGLT2 inhibitors 1,282 (33%) 841 (43%) 441 (23%) < 0.001 DPP4 inhibitors 818 (21%) 530 (27%) 288 (15%) < 0.001 Insulin 1,069 (28%) 762 (39%) 307 (16%) < 0.001 Metformin 2,379 (62%) 1,346 (69%) 1,033 (54%) < 0.001 Values are presented as n (%) unless stated otherwise. GLP-1 RA: glucagon-like peptide-1 receptor agonists; BMI: body mass index; COPD: chronic obstructive pulmonary disease; PVD: peripheral vascular disease; TIA: transient ischemic attack; CVA: cerebrovascular accident; HbA1C: hemoglobin A1c; eGFR: estimated glomerular filtration rate; ACEI: angiotensin converting enzyme inhibitors; ARB: angiotensin receptor blocker; ARNI: Angiotensin receptor-neprilysin inhibitor; MRA: mineralocorticoid receptor antagonist; SGLT2: soluble glucose transporter-2; DPP4: dipeptidyl peptidase-4. * See definition in supplementary file attached. Clinical outcomes Treatment with GLP-1 RA was associated with a lower rate of the composite outcome of death or HF hospitalization (Fig. 1 ). GLP1-A therapy was associated with a reduction in the primary outcome of death or HF hospitalization HR of 0.60 [0.53–0.68], p < 0.001), compared to the control group. A detailed description of the multivariable model results is presented in Table 2 . Older age, higher BMI, concurrent therapy with insulin, a higher glycated hemoglobin, a lower glomerular filtration rate and history of other comorbidities (COPD, history of peripheral vascular disease, hypertension) were all associated with a higher hazard for experiencing the combined outcome. With regards to GDMT, concomitant treatment (in addition to GLP-1 RA therapy) with ACE inhibitors, angiotensin receptor blockers, beta blockers and SGLT2 inhibitors were all shown to reduce the likelihood of the primary outcome. Of all GDMT examined in the multivariable model, treatment with SGLT2 inhibitors in addition to GLP-1 RA provided the lowest hazard for experiencing the primary outcome (HR 0.78 [0.68–0.90], p 0.001) and HF hospitalization (HR 0.66 [0.56–0.79], compared with the control group. A detailed results of the secondary study outcomes (death or HF hospitalization, separately) are provided in Table 2 . Table 2 – Multivariable model for the primary combined outcome of death or heart failure hospitalization, and for the secondary separate outcomes of death and heart failure hospitalization. Characteristic Combined outcome Death HF hospitalization HR 95% CI P value HR 95% CI P value HR 95% CI P value GLP-1 RA therapy 0.6 0.53, 0.68 < 0.001 0.66 0.56, 0.79 < 0.001 0.54 0.46, 0.63 < 0.001 Age 1.02 1.01, 1.03 < 0.001 1.01 1.00, 1.01 0.3 1.04 1.03, 1.04 0.9 Sector 0.7 0.2 0.11 Jews- General — — — — — — Arabs 1.02 0.88, 1.17 1.17 0.97, 1.40 0.86 0.72, 1.02 Socioeconomic score * 0.94 0.91, 0.97 < 0.001 0.93 0.89, 0.97 < 0.001 0.96 0.92, 1.0 0.025 BMI 1.01 1.00, 1.02 0.038 1.02 1.01, 1.03 0.004 0.99 0.98, 1.01 0.3 Year started on GLP-1 RA therapy 2014–2018 Ref Ref Ref Ref Ref Ref 2019–2024 1.02 0.99, 1.05 0.3 0.99 0.95, 1.03 0.5 1.06 1.02, 1.10 0.003 COPD 1.42 1.26, 1.60 < 0.001 1.31 1.11, 1.54 0.001 1.48 1.28, 1.71 < 0.001 Hypertension 1.21 1.00, 1.45 0.042 1.24 0.98, 1.57 0.063 1.17 0.93, 1.47 0.2 CVA/TIA 1.31 1.12, 1.53 0.001 1.12 0.90, 1.40 0.3 1.51 1.27, 1.81 < 0.001 PVD 1.48 1.30, 1.69 < 0.001 1.48 1.25, 1.76 < 0.001 1.5 1.29, 1.75 < 0.001 Coronary disease 0.95 0.84, 1.09 0.5 0.94 0.80, 1.12 0.5 0.89 0.76, 1.04 0.15 HbA1c 1.07 1.03, 1.10 < 0.001 1.06 1.02, 1.10 0.006 1.07 1.03, 1.12 < 0.001 eGFR 0.99 0.98, 0.99 < 0.001 0.99 0.98, 0.99 < 0.001 0.99 0.98, 0.99 < 0.001 ACEi/ARB 0.81 0.71, 0.91 < 0.001 0.77 0.66, 0.90 0.002 0.81 0.70, 0.94 0.005 ARNI 0.91 0.75, 1.12 0.4 0.98 0.76, 1.26 0.9 0.79 0.61, 1.02 0.07 MRA 1.08 0.96, 1.21 0.2 1.15 1.00, 1.34 0.059 1.09 0.95, 1.25 0.2 Beta_blockers 0.86 0.76, 0.98 0.022 0.83 0.70, 0.98 0.033 0.92 0.79, 1.07 0.3 SGLT2 inhibitors 0.78 0.68, 0.90 < 0.001 0.7 0.58, 0.85 < 0.001 0.87 0.73, 1.03 0.11 Insulin 1.18 1.04, 1.34 0.01 1.15 0.97, 1.36 0.11 1.31 1.12, 1.52 < 0.001 Metformin 1.01 0.90, 1.13 0.9 1.08 0.93, 1.26 0.3 0.93 0.81, 1.06 0.3 DPP4 inhibitors 0.93 0.82, 1.06 0.3 0.97 0.82, 1.15 0.7 0.89 0.77, 1.04 0.14 Values are presented as n (%) unless stated otherwise. GLP-1 RA: glucagon-like peptide-1 receptor agonists; BMI: body mass index; COPD: chronic obstructive pulmonary disease; PVD: peripheral vascular disease; TIA: transient ischemic attack; CVA: cerebrovascular accident; HbA1C: hemoglobin A1c; eGFR: estimated glomerular filtration rate; ACEI: angiotensin converting enzyme inhibitors; ARB: angiotensin receptor blocker; ARNI: Angiotensin receptor-neprilysin inhibitor; MRA: Mineralocorticoid receptor antagonist; SGLT2: Soluble glucose transporter-2; DPP4: dipeptidyl peptidase-4. * See definition in supplementary file attached. Subgroup analysis The beneficial effect of GLP-1 RA therapy in patients with HFrEF was evident across all sub-populations examined in this study (Fig. 2 ). Patients with a BMI > 30 and a higher hemoglobin A1C level were more likely to benefit from GLP-1 RA compared with those with a lower BMI and a lower hemoglobin A1C, respectively. When examining the effect of concomitant GDMT medications on the effect of GLP-1 RA, patients who were not treated with ARNI, BB, SGLT2 inhibitors and MRA displayed an even lower HR for the primary outcome, compared with those who were treated. Patients who were concomitantly treated with ACEI or ARB displayed a synergistic effect further reducing the HR for the primary outcome. Discussion Summary of results In this large national real-world cohort study of patients with HFrEF, we report the potential beneficial effect of GLP-1 RA in this patient population. Therapy with GLP-1 RA was associated with a lower rate of death or HF hospitalization compared with those who were not treated with GLP-1 RA (HR of 0.60 [0.53–0.68], p < 0.001). The fact that patients in the GLP-1 RA group were older and more likely to have a larger burden of comorbidities compared with those who were not treated with GLP-1 RA further emphasizes the benefit of this therapy in patients with HFrEF. Furthermore, treatment with GLP-1 RA was shown to reduce the likelihood of death and HF hospitalization in all subgroups examined in this study. To our knowledge, this is the first study to report a significant survival benefit and a reduced rate of HF hospitalization in patients with HFrEF who received treatment with GLP-1 RA. Comparison to literature Given the fact that heart failure (HF) and diabetes mellitus (DM) often coexist, anti-diabetic medications have been historically prescribed to patients with cardiac disease with the purpose of lowering their glucose level and prevent long-term diabetes-related complications. Recent studies have provided evidence regarding the beneficial effect of several anti-diabetic medications that improved cardiovascular outcomes in patients with DM, independent of their glucose-lowering effect. However, while medications such as sodium-glucose cotransporter-2 (SGLT2) inhibitors have been proven to be associated with favorable clinical outcomes in patients with heart failure (both HFrEF and HFpEF) [ 17 – 20 ], the evidence regarding the beneficial effect of GLP-1 RA in HF in general and in HFrEF in particular, remains limited [ 5 – 8 ]. Furthermore, in addition to not showing any clear benefit, there was uncertainty regarding the safety of some GLP-1 RA in this patient population [ 13 ]. Several studies have examined the potential benefit of GLP-1 RA therapy in patients with HF. The 2 STEP-HFpEF trials reported improved quality of life and weight loss in a population of obese patients with HFpEF with and without DM [ 10 , 11 ]. The recently reported pooled analysis from 4 trials which investigated the effect of GLP-1 RA further reported a reduction in HF hospitalizations in a cohort of patients with HFpEF [ 21 ]. The evidence regarding HFrEF is not as robust. A recent study reported a reduction of death but not HF hospitalization in a large cohort of patients with HF treated with GLP-1 RA [ 22 ]. However, this study included all subtypes of HF, and therefore its results cannot be applied specifically to patients with HFrEF. Villaschi et al also reported a meta-analysis of GLP-1 RA in patients with HF (HFrEF and HFpEF) and could not find a clear benefit of GLP-1 RA in those patients. Compared with the above studies, our study focuses only on patients with HFrEF, includes a larger cohort, and displays a significant benefit of GLP-1 RA in all patients included, regardless of other factors such as age and BMI. Currently there are no randomized controlled studies to report the effect of GLP-1 RA in patients with HFrEF. GLP-1 RA therapy – weight loss vs. direct cardiac effect Although several bio-mechanisms have been suggested to mediate the cardiometabolic effect of GLP-1 RA, the exact mechanism by which GLP-1 RA improves quality of life and outcomes in patients with HF is still largely unknown. The recent results reported in the STEP-HFpEF trials, which included only patients with HFpEF and obesity, suggested an indirect effect through weight loss, a common comorbidity in patient with HFpEF [ 10 ]. Other suggested mechanisms for the effect of GLP-1 RA on patients with HF include anti-inflammatory and hemodynamic effects [ 23 ]. In our study, the prevalence of the primary outcomes was significantly lower in all patients treated with GLP-1 RA, regardless of their BMI. This finding suggests a different mechanism rather than pure weight loss, which will need to be further explored in future studies. The results of this study also suggest the possible synergistic effect of GLP-1 RA and SGLT2 inhibitors, which provided the lowest hazard ratio for the primary outcome. Limitations This study has several limitations. First, since matching was limited to only age, sex and year of diagnosis, the study and the control groups differed in terms of medical therapy and comorbidities. However, since the GLP-1 RA group tended to be on the “sicker” side, our findings further emphasize the benefit of GLP-1 RA. Moreover, we further applied a multivariable model which included numerous demographic and clinical parameters, thus strengthening the robustness of our results. Second, our database did not include natriuretic peptide level, and therefore we could not assess the association between natriuretic peptide level and the effect of GLP-1 RA. Third, given the retrospective nature of this study, residual confounders which were not included in our databases might have influenced the results, and therefore the study conclusions are merely hypothesis-generating. Policy implications Although current guidelines call for caution when using GLP-1 RA in patients with HFrEF, the results of our study suggest the beneficial effect of GLP-1 RA as an additive therapy to the contemporary GDMT given to all patients with HFrEF. The possible addition of GLP-1 RA may further improve the clinical outcomes of this patient population by reducing the rate of death and HF hospitalization. While therapy with GLP-1 RA is associated with possible gastrointestinal side effects, they are mostly mild and tend to resolve within a short period of time, thus making the risk-benefit profile tilt towards the benefit side. Considering the already established effect of GLP-1 RA in terms of weight loss, which is a common comorbidity in HFrEF [ 24 ], GLP-1 RA may be an especially appealing treatment option for patients with HFrEF, especially in those with coexistent obesity. Conclusions In this cohort study of patients with DM and HFrEF, medical therapy with GLP-1 RA was associated with a reduced likelihood of death or HF hospitalization. GLP-1 RA was found to be potentially beneficial and safe in all analyzed patient subgroups. Further studies are required to validate these findings. Declarations This study was approved by the Community Medical Services Division institutional review board and by data utilization committees of Clalit health services. Due to the retrospective design, the study was exempt from obtaining informed consent from the patients due to its retrospective design and because identifying information about patients was concealed. 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Eur Heart J Cardiovasc Pharmacother 10(4):296–306 Zheng Z, Zong Y, Ma Y et al (2024) Glucagon-like peptide-1 receptor: mechanisms and advances in therapy. Signal Transduct Target Ther 9(1):234 Vest AR, Schauer PR, Rodgers JE et al (2024) Obesity and Weight Loss Strategies for Patients With Heart Failure. JACC Heart Fail 12(9):1509–1527 Additional Declarations There is NO Competing Interest. Supplementary Files Supplementaryfile.docx Supplementary file Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6768681","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":467584225,"identity":"da9fc96c-85b8-46a5-9394-23a651790a6d","order_by":0,"name":"Yoav Hammer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYJACZjDJ3gAkDCxI0cJzAKRFghQtEglgkrByg+PNz6QLarbJmc98fnXDjwIJBv727gT8Ws4cM5Oecey2scztnLKbPUCHSZw5uwG/lhsJxsY8bLcTZ0jnpN3gAWoxkMglpCX9szHPv9v1MyTPpN38Q5yWHMPHvG23EyQk2I/dJsoWyTNnCh/z9t02nMGTw3ZbxkCCh6Bf+I63bzjM8+22vAT78Wc33/yxkeNv78WvReEAnMljACbxKgcB+QY4k/0BQdWjYBSMglEwMgEAyllIk+YDMvEAAAAASUVORK5CYII=","orcid":"","institution":"Rabin Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Yoav","middleName":"","lastName":"Hammer","suffix":""},{"id":467584226,"identity":"9d7fc623-4a84-4b89-a1a0-3e1b1a83a91a","order_by":1,"name":"Ronen Arbel","email":"","orcid":"https://orcid.org/0000-0002-6058-8665","institution":"Clalit Health Services","correspondingAuthor":false,"prefix":"","firstName":"Ronen","middleName":"","lastName":"Arbel","suffix":""},{"id":467584227,"identity":"590f1cbf-c375-4dd6-95a2-9fe2cca8ad8c","order_by":2,"name":"Talish Razi","email":"","orcid":"","institution":"Clalit Health Services","correspondingAuthor":false,"prefix":"","firstName":"Talish","middleName":"","lastName":"Razi","suffix":""},{"id":467584228,"identity":"b257d7e4-45b9-43ae-8e5c-7ba2e1b6b30f","order_by":3,"name":"Doron Netzer","email":"","orcid":"","institution":"Clalit Health Service","correspondingAuthor":false,"prefix":"","firstName":"Doron","middleName":"","lastName":"Netzer","suffix":""},{"id":467584229,"identity":"c04c44cf-a50d-44a7-a314-cd0c3152e065","order_by":4,"name":"Jean Marc Weinstein","email":"","orcid":"","institution":"Cardiology Department, Soroka University Medical Center, Beer Sheva, Israel","correspondingAuthor":false,"prefix":"","firstName":"Jean","middleName":"Marc","lastName":"Weinstein","suffix":""},{"id":467584230,"identity":"cc981d42-33b6-4122-a6d5-ad4d6dde904a","order_by":5,"name":"Zaza Iakobishvili","email":"","orcid":"","institution":"Department of Community Cardiology, Tel Aviv Jaffa District, Clalit Health Services, Tel Aviv","correspondingAuthor":false,"prefix":"","firstName":"Zaza","middleName":"","lastName":"Iakobishvili","suffix":""}],"badges":[],"createdAt":"2025-05-28 13:45:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6768681/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6768681/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85367893,"identity":"f47c3e49-6055-4a22-839a-c891b3f93238","added_by":"auto","created_at":"2025-06-25 07:06:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34094,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier estimates for event free survival in patients with heart failure with reduced ejection fraction who were treated with a GLP-1 RA vs. those who were not. Shaded areas indicate 95% confidence intervals.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6768681/v1/125982c3584c613bf4cbc4d1.png"},{"id":85367894,"identity":"5eb4116e-c547-411d-866e-a163c7406e19","added_by":"auto","created_at":"2025-06-25 07:06:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53791,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis for the primary outcome of death or heart failure hospitalizations, stratified according to GLP-1 RA use. Abbreviations as in Table 1.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6768681/v1/72f616cbf7fc8456d359c473.png"},{"id":85368977,"identity":"3bc79209-b978-46c4-9b66-f476be7a70fc","added_by":"auto","created_at":"2025-06-25 07:14:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":921691,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6768681/v1/8a44d1e8-ac82-4db3-8424-019bfd5a0fad.pdf"},{"id":85367895,"identity":"ab8df708-572d-43af-bdfd-293188151bb0","added_by":"auto","created_at":"2025-06-25 07:06:12","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":80973,"visible":true,"origin":"","legend":"Supplementary file","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6768681/v1/a0d26ccb7b24cd020020d17e.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Glucagon-like peptide-1 receptor agonists in patients with heart failure with reduced ejection fraction – real world outcomes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough the pharmacological field in patients with heart failure with reduced ejection fraction (HFrEF) had greatly evolved over the past 2 decades, this patient population is still subjected to a relatively high incidence of death, heart failure (HF) hospitalization and reduced quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGlucagon-like peptide-1 receptor agonists (GLP-1 RA) include several medications which bind to a GLP-1 receptor and thereby promote insulin secretion, inhibit glucagon release and gastric emptying, and induce satiety [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Various GLP-1 RA differ in their structure and therefore differ in their dose, duration of action, mode of administration, and efficacy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. GLP-1 RA therapy has been investigated in several cohorts and was shown to decrease the likelihood of death and major adverse cardiac events as well renal outcomes [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, as the prevalence of HF ranged from 9–24% in those studies, evidence regarding the effect of GLP-1 RA in patients with HF in general and HFrEF in particular, is scarce. While the recent publication of the STEP-HFpEF trials have provided evidence regarding the possible beneficial effect of GLP-1 RA in patients with heart failure with preserved ejection fraction (HFpEF) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], there is still no robust evidence regarding the efficacy in those with HFrEF, as only 3 small clinical trials have examined the use of GLP-1 RA in patients with HFrEF [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and none currently in progress. Furthermore, while GLP-1 RA do not feature as recommended therapy in patients with HFrEF per latest published HF guidelines [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], a substantial number of patients with HFrEF are treated with GLP-1 RA for indications other than HF. Therefore, the aim of this study was to examine the effectiveness of GLP-1 RA therapy in patients with HFrEF.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy population –\u003c/p\u003e\u003cp\u003e This retrospective cohort study was based on the Clalit Health Services database – the largest health care organization in Israel, which delivers universal healthcare coverage to two thirds of patients older than 65. To be included in the study, patients were required to have diabetes mellitus, a validated ICD-9 HF diagnosis (codes 428.x) and a documented left ventricular ejection fraction (LVEF) ≤ 40%. Next, patients were stratified into 2 groups – the treatment group and the control group. To be included in the treatment group, patients had to be treated with a GLP-1 RA; namely, liraglutide, exenatide, dulaglutide or semaglutide. To note, only patients who had 2 consecutive dispensed prescriptions for one of the GLP-1 RA were included in the treatment group. In order to examine the direct effect of GLP-1 RA on patients already diagnosed with HFrEF, only patients who started GLP-1 RA therapy after the date of systolic HF diagnosis were included in the treatment group. The control group included patients with HFrEF who were not treated with GLP-1 RA. Excluded from the study were patients who were treated with GLP-1 RA before a diagnosis of HFrEF was established, patients with heart failure with preserved EF (HFpEF), patients on hemodialysis, patients who underwent renal transplant, heart transplant or left-ventricular assist device implantation.\u003c/p\u003e\u003cp\u003eData extraction\u003c/p\u003e\u003cp\u003eFor this study, demographic, social, medical and laboratory data were extracted from the patient’s electronic medical record (EMR). For the purpose of including only patients with HFrEF, ejection fraction was extracted from the patient’s echocardiographic reports.\u003c/p\u003e\u003cp\u003eOutcomes\u003c/p\u003e\u003cp\u003eThe primary outcome of the study was a composite outcome of death and HF hospitalization, which was defined as any hospitalization with a primary diagnosis of heart failure. Secondary outcomes evaluated in this study were all-cause death and HF hospitalization, separately.\u003c/p\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe analysis was done in two stages:\u003c/p\u003e\u003cp\u003eFirst, patients treated with GLP1A were matched 1:1 with untreated subjects. Individual matching of patients was conducted based on sex, age at HF diagnosis, and the year of HF diagnosis. Descriptive statistics were used to characterize the study participants. The index date was the initiation of GLP-1 RA therapy.\u003c/p\u003e\u003cp\u003eIn the second stage, time-dependent Cox regression analysis was used to assess the association between GLP-1 RA therapy and outcomes adjusting for additional variables: social sector, socio-economic status, BMI, chronic obstructive pulmonary disease (COPD) hypertension (HTN), history of cerebrovascular disease, peripheral arterial disease (PAD), ischemic heart disease (IHD), Hemoglobin A1C, estimated glomerual filtration rate (eGFR), and concurrent medications at baseline - angiotensin converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), mineralocorticoid receptor antagonists (MRA), angiotensin receptor-neprilysin inhibitor (ARNI), beta-adrenergic receptor blockers (BB), dipeptidyl peptidase IV inhibitors (DPP4i), insulin, metformin and sodium-glucose co-transporter-2 inhibitors (SGLT2i).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePatient population\u003c/p\u003e \u003cp\u003eA graphical depiction of the formation of the study cohort is presented in \u003cb\u003eSupplementary Fig.\u0026nbsp;1.\u003c/b\u003e Between the years 2014\u0026ndash;2024, a total of 22,411 patients met the inclusion and exclusion criteria of the study. Of these, 3023 were treated with GLP-1 RA (treatment group) and 19,388 were not treated with GLP-1 RA (control group). Out of those 22,411 patients, 1939 pairs were matched. No major differences between the 2 groups were noted with respect to baseline demographic characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Median age of the study cohort was 69 (63, 76), 67% were males and median follow-up time of the study was 30.8 months for both groups. In general, patients in the GLP-1 RA group tended to have more comorbidities, a higher hemoglobin A1C level and a higher BMI compared with the control group. In terms of medical therapy, patients in the GLP-1 RA group were more likely to be treated with guideline directed medical therapy (GDMT) and anti-diabetic medications.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Baseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;3,858\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLP-1 RA\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,939\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,919\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDemographic\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (63, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (63, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (63, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,584 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,297 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,287 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,274 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e642 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e632 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic sector, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJews- General\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,900 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,459 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,441 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArabs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e958 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e480 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e478 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocioeconomic score*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.00 (4.0, 7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00 (4.0, 7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.00 (4.0, 7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eClinical characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear started on GLP-1 RA therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e722 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e362 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e360 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,136 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,577 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,559 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI group (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e598 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e479 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,352 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e594 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e758 (39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,595 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,006 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e589 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e313 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.9 (26.6, 34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.6 (28.3, 35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.1 (25.0, 31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e731 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e371 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e360 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,249 (84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,701 (88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,548 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of CVA/TIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e388 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e228 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e341 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e302 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,890 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,502 (77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,388 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.60 (6.50, 9.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.50 (7.50, 9.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.80 (6.20, 7.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR (ml/min/1.73 m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e244 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e177 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e688 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e425 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e263 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e667 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e336 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e331 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,923 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e908 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,015 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR (ml/min/1.73 m2), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (41, 84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (38, 82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (45, 86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMedical therapy\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEi/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,633 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,389 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,244 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e517 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e274 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e243 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,389 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e793 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e596 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,993 (78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,604 (83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,389 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGLT2 inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,282 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e841 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e441 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDPP4 inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e818 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e530 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e288 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,069 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e762 (39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e307 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,379 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,346 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,033 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are presented as n (%) unless stated otherwise. GLP-1 RA: glucagon-like peptide-1 receptor agonists; BMI: body mass index; COPD: chronic obstructive pulmonary disease; PVD: peripheral vascular disease; TIA: transient ischemic attack; CVA: cerebrovascular accident; HbA1C: hemoglobin A1c; eGFR: estimated glomerular filtration rate; ACEI: angiotensin converting enzyme inhibitors; ARB: angiotensin receptor blocker; ARNI: Angiotensin receptor-neprilysin inhibitor; MRA: mineralocorticoid receptor antagonist; SGLT2: soluble glucose transporter-2; DPP4: dipeptidyl peptidase-4.\u003c/p\u003e \u003cp\u003e* See definition in supplementary file attached.\u003c/p\u003e \u003cp\u003eClinical outcomes\u003c/p\u003e \u003cp\u003eTreatment with GLP-1 RA was associated with a lower rate of the composite outcome of death or HF hospitalization (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGLP1-A therapy was associated with a reduction in the primary outcome of death or HF hospitalization HR of 0.60 [0.53\u0026ndash;0.68], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared to the control group. A detailed description of the multivariable model results is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Older age, higher BMI, concurrent therapy with insulin, a higher glycated hemoglobin, a lower glomerular filtration rate and history of other comorbidities (COPD, history of peripheral vascular disease, hypertension) were all associated with a higher hazard for experiencing the combined outcome. With regards to GDMT, concomitant treatment (in addition to GLP-1 RA therapy) with ACE inhibitors, angiotensin receptor blockers, beta blockers and SGLT2 inhibitors were all shown to reduce the likelihood of the primary outcome. Of all GDMT examined in the multivariable model, treatment with SGLT2 inhibitors in addition to GLP-1 RA provided the lowest hazard for experiencing the primary outcome (HR 0.78 [0.68\u0026ndash;0.90], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eSecondary outcomes of the study also favored GLP-1 RA therapy, with a lower rate of death (HR 0.54 [0.46\u0026ndash;0.63], p\u0026thinsp;\u0026gt;\u0026thinsp;0.001) and HF hospitalization (HR 0.66 [0.56\u0026ndash;0.79], compared with the control group. A detailed results of the secondary study outcomes (death or HF hospitalization, separately) are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003e\u0026ndash; Multivariable model for the primary combined outcome of death or heart failure hospitalization, and for the secondary separate outcomes of death and heart failure hospitalization.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCombined outcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eHF hospitalization\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGLP-1 RA therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53, 0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.56, 0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.46, 0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01, 1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00, 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.03, 1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.87, 1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJews- General\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArabs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88, 1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97, 1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.72, 1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocioeconomic score *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91, 0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89, 0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.92, 1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00, 1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01, 1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.98, 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear started on GLP-1 RA therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99, 1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95, 1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.02, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26, 1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.11, 1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.28, 1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00, 1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98, 1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.93, 1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVA/TIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12, 1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.90, 1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.27, 1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30, 1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25, 1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.29, 1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84, 1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80, 1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.76, 1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.03, 1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98, 0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98, 0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.98, 0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEi/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71, 0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66, 0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.70, 0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75, 1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76, 1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.61, 1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96, 1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00, 1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.95, 1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta_blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76, 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70, 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.79, 1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGLT2 inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68, 0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.58, 0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.73, 1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04, 1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97, 1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.12, 1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90, 1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93, 1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.81, 1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDPP4 inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82, 1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82, 1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.77, 1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are presented as n (%) unless stated otherwise. GLP-1 RA: glucagon-like peptide-1 receptor agonists; BMI: body mass index; COPD: chronic obstructive pulmonary disease; PVD: peripheral vascular disease; TIA: transient ischemic attack; CVA: cerebrovascular accident; HbA1C: hemoglobin A1c; eGFR: estimated glomerular filtration rate; ACEI: angiotensin converting enzyme inhibitors; ARB: angiotensin receptor blocker; ARNI: Angiotensin receptor-neprilysin inhibitor; MRA: Mineralocorticoid receptor antagonist; SGLT2: Soluble glucose transporter-2; DPP4: dipeptidyl peptidase-4.\u003c/p\u003e \u003cp\u003e* See definition in supplementary file attached.\u003c/p\u003e \u003cp\u003eSubgroup analysis\u003c/p\u003e \u003cp\u003eThe beneficial effect of GLP-1 RA therapy in patients with HFrEF was evident across all sub-populations examined in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Patients with a BMI\u0026thinsp;\u0026gt;\u0026thinsp;30 and a higher hemoglobin A1C level were more likely to benefit from GLP-1 RA compared with those with a lower BMI and a lower hemoglobin A1C, respectively. When examining the effect of concomitant GDMT medications on the effect of GLP-1 RA, patients who were not treated with ARNI, BB, SGLT2 inhibitors and MRA displayed an even lower HR for the primary outcome, compared with those who were treated. Patients who were concomitantly treated with ACEI or ARB displayed a synergistic effect further reducing the HR for the primary outcome.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSummary of results\u003c/p\u003e \u003cp\u003eIn this large national real-world cohort study of patients with HFrEF, we report the potential beneficial effect of GLP-1 RA in this patient population. Therapy with GLP-1 RA was associated with a lower rate of death or HF hospitalization compared with those who were not treated with GLP-1 RA (HR of 0.60 [0.53\u0026ndash;0.68], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The fact that patients in the GLP-1 RA group were older and more likely to have a larger burden of comorbidities compared with those who were not treated with GLP-1 RA further emphasizes the benefit of this therapy in patients with HFrEF. Furthermore, treatment with GLP-1 RA was shown to reduce the likelihood of death and HF hospitalization in all subgroups examined in this study. To our knowledge, this is the first study to report a significant survival benefit and a reduced rate of HF hospitalization in patients with HFrEF who received treatment with GLP-1 RA.\u003c/p\u003e \u003cp\u003eComparison to literature\u003c/p\u003e \u003cp\u003eGiven the fact that heart failure (HF) and diabetes mellitus (DM) often coexist, anti-diabetic medications have been historically prescribed to patients with cardiac disease with the purpose of lowering their glucose level and prevent long-term diabetes-related complications. Recent studies have provided evidence regarding the beneficial effect of several anti-diabetic medications that improved cardiovascular outcomes in patients with DM, independent of their glucose-lowering effect. However, while medications such as sodium-glucose cotransporter-2 (SGLT2) inhibitors have been proven to be associated with favorable clinical outcomes in patients with heart failure (both HFrEF and HFpEF) [\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], the evidence regarding the beneficial effect of GLP-1 RA in HF in general and in HFrEF in particular, remains limited [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, in addition to not showing any clear benefit, there was uncertainty regarding the safety of some GLP-1 RA in this patient population [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have examined the potential benefit of GLP-1 RA therapy in patients with HF. The 2 STEP-HFpEF trials reported improved quality of life and weight loss in a population of obese patients with HFpEF with and without DM [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The recently reported pooled analysis from 4 trials which investigated the effect of GLP-1 RA further reported a reduction in HF hospitalizations in a cohort of patients with HFpEF [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The evidence regarding HFrEF is not as robust. A recent study reported a reduction of death but not HF hospitalization in a large cohort of patients with HF treated with GLP-1 RA [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, this study included all subtypes of HF, and therefore its results cannot be applied specifically to patients with HFrEF. Villaschi et al also reported a meta-analysis of GLP-1 RA in patients with HF (HFrEF and HFpEF) and could not find a clear benefit of GLP-1 RA in those patients. Compared with the above studies, our study focuses only on patients with HFrEF, includes a larger cohort, and displays a significant benefit of GLP-1 RA in all patients included, regardless of other factors such as age and BMI. Currently there are no randomized controlled studies to report the effect of GLP-1 RA in patients with HFrEF.\u003c/p\u003e \u003cp\u003eGLP-1 RA therapy \u0026ndash; weight loss vs. direct cardiac effect\u003c/p\u003e \u003cp\u003eAlthough several bio-mechanisms have been suggested to mediate the cardiometabolic effect of GLP-1 RA, the exact mechanism by which GLP-1 RA improves quality of life and outcomes in patients with HF is still largely unknown. The recent results reported in the STEP-HFpEF trials, which included only patients with HFpEF and obesity, suggested an indirect effect through weight loss, a common comorbidity in patient with HFpEF [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Other suggested mechanisms for the effect of GLP-1 RA on patients with HF include anti-inflammatory and hemodynamic effects [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In our study, the prevalence of the primary outcomes was significantly lower in all patients treated with GLP-1 RA, regardless of their BMI. This finding suggests a different mechanism rather than pure weight loss, which will need to be further explored in future studies. The results of this study also suggest the possible synergistic effect of GLP-1 RA and SGLT2 inhibitors, which provided the lowest hazard ratio for the primary outcome.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, since matching was limited to only age, sex and year of diagnosis, the study and the control groups differed in terms of medical therapy and comorbidities. However, since the GLP-1 RA group tended to be on the \u0026ldquo;sicker\u0026rdquo; side, our findings further emphasize the benefit of GLP-1 RA. Moreover, we further applied a multivariable model which included numerous demographic and clinical parameters, thus strengthening the robustness of our results. Second, our database did not include natriuretic peptide level, and therefore we could not assess the association between natriuretic peptide level and the effect of GLP-1 RA. Third, given the retrospective nature of this study, residual confounders which were not included in our databases might have influenced the results, and therefore the study conclusions are merely hypothesis-generating.\u003c/p\u003e \u003cp\u003ePolicy implications\u003c/p\u003e \u003cp\u003e Although current guidelines call for caution when using GLP-1 RA in patients with HFrEF, the results of our study suggest the beneficial effect of GLP-1 RA as an additive therapy to the contemporary GDMT given to all patients with HFrEF. The possible addition of GLP-1 RA may further improve the clinical outcomes of this patient population by reducing the rate of death and HF hospitalization. While therapy with GLP-1 RA is associated with possible gastrointestinal side effects, they are mostly mild and tend to resolve within a short period of time, thus making the risk-benefit profile tilt towards the benefit side. Considering the already established effect of GLP-1 RA in terms of weight loss, which is a common comorbidity in HFrEF [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], GLP-1 RA may be an especially appealing treatment option for patients with HFrEF, especially in those with coexistent obesity.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this cohort study of patients with DM and HFrEF, medical therapy with GLP-1 RA was associated with a reduced likelihood of death or HF hospitalization. GLP-1 RA was found to be potentially beneficial and safe in all analyzed patient subgroups. Further studies are required to validate these findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThis study was approved by the Community Medical Services Division institutional review board and by data utilization committees of Clalit health services. Due to the retrospective design, the study was exempt from obtaining informed consent from the patients due to its retrospective design and because identifying information about patients was concealed.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was supported by the ISRAEL SCIENCE FOUNDATION (grant No. 3543/21), within the Israel Precision Medicine Partnership program.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcDonagh TA, Metra M, Adamo M et al (2023) 2023 Focused Update of the 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J 44(37):3627\u0026ndash;3639\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarx N, Husain M, Lehrke M et al (2022) GLP-1 Receptor Agonists for the Reduction of Atherosclerotic Cardiovascular Risk in Patients With Type 2 Diabetes. Circulation 146(24):1882\u0026ndash;1894\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan MS, Fonarow GC, McGuire DK et al (2020) Glucagon-Like Peptide 1 Receptor Agonists and Heart Failure: The Need for Further Evidence Generation and Practice Guidelines Optimization. Circulation 142(12):1205\u0026ndash;1218\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerkovic V, Tuttle KR, Rossing P et al (2024) Effects of Semaglutide on Chronic Kidney Disease in Patients with Type 2 Diabetes. N Engl J Med 391(2):109\u0026ndash;121\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGerstein HC, Colhoun HM, Dagenais GR et al (2019) Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial. Lancet 394(10193):121\u0026ndash;130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHusain M, Birkenfeld AL, Donsmark M et al (2019) Oral Semaglutide and Cardiovascular Outcomes in Patients with Type 2 Diabetes. N Engl J Med 381(9):841\u0026ndash;851\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarso SP, Bain SC, Consoli A et al (2016) Semaglutide and Cardiovascular Outcomes in Patients with Type 2 Diabetes. N Engl J Med 375(19):1834\u0026ndash;1844\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarso SP, Daniels GH, Brown-Frandsen K et al (2016) Liraglutide and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med 375(4):311\u0026ndash;322\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLincoff AM, Brown-Frandsen K, Colhoun HM et al (2023) Semaglutide and Cardiovascular Outcomes in Obesity without Diabetes. N Engl J Med 389(24):2221\u0026ndash;2232\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKosiborod MN, Abildstrom SZ, Borlaug BA et al (2023) Semaglutide in Patients with Heart Failure with Preserved Ejection Fraction and Obesity. N Engl J Med 389(12):1069\u0026ndash;1084\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKosiborod MN, Petrie MC, Borlaug BA et al (2024) Semaglutide in Patients with Obesity-Related Heart Failure and Type 2 Diabetes. N Engl J Med 390(15):1394\u0026ndash;1407\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLepore JJ, Olson E, Demopoulos L et al (2016) Effects of the Novel Long-Acting GLP-1 Agonist, Albiglutide, on Cardiac Function, Cardiac Metabolism, and Exercise Capacity in Patients With Chronic Heart Failure and Reduced Ejection Fraction. JACC Heart Fail 4(7):559\u0026ndash;566\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMargulies KB, Hernandez AF, Redfield MM et al (2016) Effects of Liraglutide on Clinical Stability Among Patients With Advanced Heart Failure and Reduced Ejection Fraction: A Randomized Clinical Trial. JAMA 316(5):500\u0026ndash;508\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJorsal A, Kistorp C, Holmager P et al (2017) Effect of liraglutide, a glucagon-like peptide-1 analogue, on left ventricular function in stable chronic heart failure patients with and without diabetes (LIVE)-a multicentre, double-blind, randomised, placebo-controlled trial. Eur J Heart Fail 19(1):69\u0026ndash;77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAuthors/Task Force M, McDonagh TA, Metra M et al (2022) 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 24(1):4\u0026ndash;131\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeidenreich PA, Bozkurt B, Aguilar D et al (2022) 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 145(18):e895\u0026ndash;e1032\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZinman B, Wanner C, Lachin JM et al (2015) Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J Med 373(22):2117\u0026ndash;2128\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWiviott SD, Raz I, Sabatine MS (2019) Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. Reply N Engl J Med 380(19):1881\u0026ndash;1882\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcMurray JJV, Solomon SD, Inzucchi SE et al (2019) Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction. N Engl J Med 381(21):1995\u0026ndash;2008\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePacker M, Anker SD, Butler J et al (2020) Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med 383(15):1413\u0026ndash;1424\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKosiborod MN, Deanfield J, Pratley R et al (2024) Semaglutide versus placebo in patients with heart failure and mildly reduced or preserved ejection fraction: a pooled analysis of the SELECT, FLOW, STEP-HFpEF, and STEP-HFpEF DM randomised trials. Lancet 404(10456):949\u0026ndash;961\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWallner M, Biber ME, Stolfo D et al (2024) Glucagon-like peptide-1 receptor agonists use and associations with outcomes in heart failure and type 2 diabetes: data from the Swedish Heart Failure and Swedish National Diabetes Registries. Eur Heart J Cardiovasc Pharmacother 10(4):296\u0026ndash;306\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Z, Zong Y, Ma Y et al (2024) Glucagon-like peptide-1 receptor: mechanisms and advances in therapy. Signal Transduct Target Ther 9(1):234\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVest AR, Schauer PR, Rodgers JE et al (2024) Obesity and Weight Loss Strategies for Patients With Heart Failure. JACC Heart Fail 12(9):1509\u0026ndash;1527\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6768681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6768681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The evidence regarding the effect of glucagon-like peptide-1 receptor agonists (GLP-1 RA) in patients with heart failure with reduced ejection fraction (HFrEF) is limited and conflicting, with some studies suggesting a favorable effect and some not. The aim of the study was to examine the safety and efficacy of GLP-1 RA therapy in a large national database of patients with HFrEF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In this observational retrospective cohort, data was obtained from the electronic medical records of Clalit Health Services, the largest health care organization in Israel. Between the years 2014 -2024, using a 1:1 matching, patients with HFrEF who were treated with GLP-1 RA were compared with those who were not. Outcomes included heart failure (HF) hospitalization and death. A subgroup analysis by body mass index (BMI), age, sex, HbA1C level and concomitant medications was conducted as well.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Out of 22,411 patients with HFrEF, 3023 initiated GLP-1 RA therapy after the diagnosis of HF was made. After a 1:1 nearest-neighbor matching, 3858 patients were matched and included in the study, with 1939 and 1919 patients in the GLP-1 RA group and the control group, respectively. Mean age of the cohort was 69, 33% female, and mean BMI was 29.9 kg/m\u003csup\u003e2\u003c/sup\u003e. While therapy with beta blockers and ACEI/ARB/ARNI was common within the cohort, only a third of the cohort was treated with SGLT2 inhibitors or mineralocorticoid receptor antagonists. Median follow-up time of the study was 30 months (17.06, 43.0). In a multivariable model which included multiple demographic and clinical variables, patients who were treated with GLP-1 RA were less likely to experience the primary outcome of death or HF hospitalization (HR 0.6, 0.53 – 0.68, p\u0026lt;0.001) compared with the control group. The subgroup analysis revealed a robust favorable effect of GLP-1 RA across the entire spectrum of patients with HFrEF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: In this large cohort study of patients with HFrEF, GLP-1 RA therapy in addition to standard guideline directed medical therapy was associated with a lower rate of death and HF hospitalization. Future randomized trials are needed to confirm these results.\u0026nbsp;\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Glucagon-like peptide-1 receptor agonists in patients with heart failure with reduced ejection fraction – real world outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 07:06:07","doi":"10.21203/rs.3.rs-6768681/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d8e515e8-0648-417a-b36f-65126b5a8de2","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":49648970,"name":"Health sciences/Medical research/Outcomes research"},{"id":49648971,"name":"Health sciences/Health care/Prognosis/Disease-free survival"}],"tags":[],"updatedAt":"2025-06-25T07:06:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 07:06:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6768681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6768681","identity":"rs-6768681","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}