Comparative Real-World Effectiveness of Sacubitril/Valsartan and SGLT2 Inhibitors in Patients with HFrEF: A Retrospective Cohort Study

Comparative Real-World Effectiveness of Sacubitril/Valsartan and SGLT2 Inhibitors in Patients with HFrEF: A Retrospective Cohort Study | 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 Research Article Comparative Real-World Effectiveness of Sacubitril/Valsartan and SGLT2 Inhibitors in Patients with HFrEF: A Retrospective Cohort Study Seçkin Dereli, Onur Osman Şeker This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7511564/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Sacubitril/valsartan (S/V) and SGLT2 inhibitors (SGLT2i) are guideline-recommended (Class I) for HFrEF, yet direct comparative data are limited. We evaluated their relative effectiveness in routine care. Methods Retrospective cohort of 626 HFrEF patients (LVEF ≤ 40%) followed 2017–2024, all with ≥ 12 months of optimized β-blocker and RAAS inhibition. Three strategies: Group 1 (n = 200) ACEI/ARB→S/V; Group 2 (n = 190) ACEI/ARB→+SGLT2i (often because of S/V affordability); Group 3 (n = 220) on S/V then + SGLT2i. Outcomes were compared in the 12 months before (T0) and after (T1) treatment change. Results Switching to S/V was associated with greater improvement than adding SGLT2i to ACEI/ARB. HF hospitalizations fell 61% (1.8→0.7 per patient-year; p < 0.001) with S/V vs 25% (1.6→1.2; p = 0.048) with SGLT2i. NT-proBNP decreased 48% (1820→940 pg/mL; p < 0.001) with S/V vs 15% (2395→2020; p = 0.047) with SGLT2i. LVEF rose by 7.1% (28.7→35.8%; p < 0.001) with S/V vs 2.3% (30.5→32.8%; p = 0.06) with SGLT2i. Outpatient visits and emergency department admissions showed parallel reductions. Adding SGLT2i on background S/V (Group 3) provided modest incremental benefits, particularly for visits and NYHA class. Conclusions In well-treated HFrEF, initiating S/V after ACEI/ARB was linked to larger gains across hospitalizations, biomarkers, and function than adding SGLT2i to ACEI/ARB, while SGLT2i on top of S/V offered smaller complementary improvements. These real-world data support S/V as the backbone therapy, with SGLT2i providing additional—though less pronounced—benefits. Heart failure with reduced ejection fraction (HFrEF) Sacubitril/valsartan (S/V) SGLT2 inhibitors Guideline-directed medical therapy (GDMT) Hospitalization outcomes Figures Figure 1 Figure 2 Figure 3 HIGHLIGHTS · Real-world HFrEF cohort (n=626) on optimized beta-blocker and RAAS therapy. · ACEI/ARB→S/V associated with 61% fewer HF hospitalizations (1.8→0.7 pp-yr). · Greater biomarker gains with S/V: NT-proBNP −48%; LVEF +7.1% (p<0.001). · ACEI/ARB→+SGLT2i showed smaller changes: NT-proBNP −15%; LVEF +2.3%. · Adding SGLT2i on S/V gave modest, mostly non-significant, incremental benefit. INTRODUCTION Heart failure with reduced ejection fraction (HFrEF) remains a significant global challenge, characterized by alarmingly high rates of hospitalization and mortality, although improvements in guideline-directed medical therapy (GDMT) [ 1 ]. Current evidence-based guidelines underscore the necessity of employing four fundamental pharmacological classes: angiotensin receptor–neprilysin inhibitors (ARNI), beta-blockers, mineralocorticoid receptor antagonists (MRAs), and sodium–glucose cotransporter-2 inhibitors (SGLT2i) [ 2 ]. Sacubitril/valsartan (S/V) was the inaugural treatment to exhibit a significant advantage, as evidenced by the PARADIGM-HF study, which revealed considerable and enduring decreases in cardiovascular mortality and heart failure hospitalizations in comparison to enalapril. Subsequent research verified that the therapeutic effects of ARNI manifest swiftly after initiation, resulting in early enhancements in symptoms, natriuretic peptide levels, and hemodynamic status, alongside sustained long-term prognosis benefits [ 3 , 4 ]. SGLT2 inhibitors, first designed as glucose-lowering medications, have now transformed heart failure management by exhibiting significant efficacy regardless of diabetes status. Extensive randomized controlled trials, including DAPA-HF and EMPEROR-Reduced, along with meta-analyses, consistently demonstrated substantial reductions in heart failure hospitalizations, cardiovascular mortality, and enhancements in quality of life [ 5 – 7 ]. These findings established SGLT2 inhibitors as a Class I recommendation in the latest guidelines [ 2 ]. Their mechanism of improvement, however, seems to be distinct and more gradual compared to the acute hemodynamic changes noted with S/V. Notwithstanding these advancements, direct randomized comparisons between S/V and SGLT2i are absent, and conducting such trials would pose ethical dilemmas due to the established Class I prescription for both treatments. Real-world practice patterns, however, present a distinctive chance to assess their comparative clinical efficacy. Heterogeneity specifically occurs in health systems where reimbursement limitations restrict universal access—some patients receive S/V following optimal titration of ACEi/ARB, MRA, and beta-blockers, while others commence SGLT2i either in conjunction with S/V or as an adjunct to optimized background therapy without S/V [ 8 , 9 ]. This study aims to retrospectively compare three independent patient groups with HFrEF who received optimum background treatment before the commencement of S/V or SGLT2i. The main aim was to assess alterations in hospitalization, emergency department admissions, outpatient clinic visits, and functional capacity prior to and following the commencement of treatment. We posited that S/V, in addition to the advantages of SGLT2i, provides more substantial, timely, and enduring enhancements in morbidity and functional outcomes, hence affirming its supremacy as the cornerstone of HFrEF therapy. METHODS Study design and population This retrospective observational analysis encompassed individuals with HFrEF monitored from January 2017 to December 2024 at a tertiary cardiology institution. Eligible patients were aged 18 years or older, exhibited a left ventricular ejection fraction (LVEF) of 40% or less, and presented with New York Heart Association (NYHA) class II to IV symptoms. All patients were mandated to have completed systematic and quick dose titration of guideline-directed medical therapy (GDMT), encompassing beta-blockers and mineralocorticoid receptor antagonists (MRAs), to the maximum tolerated or target levels. Prior to therapy adjustment, dosage optimization was confirmed, with over 90% of patients attaining at least 50% of the target doses for beta-blockers and MRAs, and all patients receiving at least 50% of ACEIs/ARBs or S/V. During follow-up, modifications to the doses of S/V or other neurohormonal antagonists were permitted in instances of adverse effects such as hypotension, hyperkalemia, or renal impairment; however, no patient necessitated permanent discontinuation, and all medications were sustained throughout the research duration. Exclusion criteria were the presence of malignancy, acute coronary syndrome, major surgery or trauma during the observation period, or cardiac resynchronization therapy (CRT) within 6 months prior to index treatment modification. Group definitions Patients were categorized into three groups according to treatment strategy: Group 1 Patients optimized on ACE inhibitors/angiotensin receptor blockers, mineralocorticoid receptor antagonists, and beta-blockers who were then transitioned to S/V. Group 2 Patients who were optimized on ACEI/ARB, MRA, and beta-blocker medication, to whom an SGLT2 inhibitor was subsequently administered. This cohort primarily comprised diabetic and non-diabetic HFrEF patients who consented to SGLT2i therapy but could not afford S/V due to out-of-pocket expenses. Group 3 Patients receiving optimal ARNI, MRA, and beta-blocker therapy, to whom an SGLT2 inhibitor was later introduced. The justification for these group classifications is rooted on both clinical practice and healthcare policy in Türkiye: S/V received a Class I recommendation in heart failure recommendations prior to SGLT2i, and both treatments continue to be non-reimbursed for non-diabetic HFrEF patients. Data collection Baseline demographics, comorbidities, functional class, laboratory parameters, echocardiographic measurements, and medical therapy were collected retrospectively at T0. Outcomes were evaluated at both T0 and T1 as follows: Outpatient cardiology clinic visits : the percentage of patients attending the cardiology outpatient clinic was recorded, and the average annual number of visits per patient was calculated over the total number of visits. Emergency department (ED) admissions : the percentage of patients admitted to the ED was documented, and the average annual number of ED admissions per patient was calculated over the total admissions. Hospitalizations : hospital admissions were evaluated in two subgroups as admissions to the cardiac intensive care unit (CICU) and admissions to the medical ward. The percentage of hospitalized patients was determined, the average annual number of hospitalizations per patient was calculated over the total number of admissions, and the average length of stay (LOS) was calculated over the total number of hospitalization days. NYHA class, NT-proBNP levels, and LVEF were evaluated at both T0 and T1. Data were extracted from hospital electronic medical records and the national e-Nabız system, which integrates individual-level medical data across all public and private health institutions in Türkiye. Outcomes The primary endpoints were changes in annualized heart failure hospitalizations, ED admissions, outpatient clinic visits, and hospitalization LOS. Secondary endpoints included changes in NT-proBNP, LVEF, and NYHA class distribution. Ethics The study protocol was approved by the local ethics committee and conducted in accordance with the Declaration of Helsinki. All patients provided informed consent. Statistical Analysis Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile range, IQR) according to their distribution, which was assessed by the Shapiro–Wilk test. Categorical variables were presented as counts and percentages (n, %). Baseline characteristics between the three treatment groups were compared using one-way ANOVA or Kruskal–Wallis tests for continuous variables and chi-square or Fisher’s exact test for categorical variables. Within-group comparisons of T0 (pre-treatment) and T1 (post-treatment) were performed using paired-samples t-test or Wilcoxon signed-rank test for continuous variables and McNemar’s test for categorical variables. Between-group comparisons of treatment effect (Δ = T1–T0) were assessed using repeated measures ANOVA with Bonferroni correction or generalized estimating equations (GEE) to account for within-subject correlations, given that the groups were heterogeneous and not perfectly balanced. Given baseline differences in LVEF and NYHA class, additional models were run including these variables as covariates (ANCOVA approach), which did not materially change the results. Effect sizes were calculated to better illustrate clinical relevance in addition to p values. A two-tailed p value < 0.05 was considered statistically significant. All analyses were performed using SPSS version XX (IBM Corp., Armonk, NY, USA). RESULTS A total of 626 patients were analyzed, comprising 216 in Group 1 (ACEI/ARB→S/V), 190 in Group 2 (ACEI/ARB→SGLT2i), and 220 in Group 3 (ARNI→+SGLT2i). Table 1 presents baseline demographics, comorbidities, and background therapy. The three cohorts exhibited general comparability; however, Group 3 patients demonstrated a greater proportion of NYHA class I–II (70%) and a marginally elevated mean LVEF (31.2 ± 4.7%) relative to Groups 1 and 2. Guideline-directed dose optimization was consistently achieved, with over 90% of patients reaching at least 50% of the target doses for beta-blockers and MRAs. Additionally, all patients received at least 50% of ACEI/ARB or S/V before any treatment modifications (Table 1 ). No patient permanently discontinued sacubitril/valsartan, SGLT2i, or background neurohormonal blockade. Temporary dose reductions occurred in a minority of cases due to hypotension or renal fluctuations; however, all patients remained on full multidrug therapy at the conclusion of follow-up. A direct comparison indicated that the transition from ACEI/ARB to ARNI (Group 1) resulted in significantly greater improvements compared to the transition from ACEI/ARB to SGLT2i (Group 2). Furthermore, the addition of SGLT2i on top of ARNI (Group 3) provided only incremental benefits (Table 2 A–C). Hospitalizations decreased from 56.5–31.5% (p < 0.001), accompanied by similar reductions in emergency department visits and outpatient consultations, each exceeding 40% (p < 0.001). The length of stay was significantly reduced from 8.4 ± 3.2 days to 5.6 ± 2.1 days (p < 0.001). Functional status demonstrated significant improvement: NYHA I–II increased from 33.3–59.3% (p < 0.001), NT-proBNP decreased by approximately 620 pg/mL (p < 0.001), and LVEF improved by 6.3% (p < 0.001). In Group 2, the addition of SGLT2i to ACEI/ARB therapy yielded more modest benefits (Table 2 B). Hospitalization rates decreased from 55.8–42.1% (p = 0.049), with a marginal reduction in length of stay observed (8.0 ± 3.0 to 6.2 ± 2.4 days, p = 0.050). There was a significant decrease in outpatient visits, from 3.6 ± 1.1 to 2.5 ± 0.9 per year (p = 0.046). NT-proBNP decreased by approximately 375 pg/mL (p = 0.047), while the enhancement in LVEF (+ 2.3%) did not achieve statistical significance (p = 0.06). The proportion of NYHA IV patients decreased significantly from 10.5–8.4% (p = 0.041). In Group 3 (ARNI→+SGLT2i), the incremental benefit was reduced (Table 2 C). Outpatient visits exhibited a modest reduction (p = 0.046), whereas hospitalizations, emergency department visits, and length of stay remained statistically unchanged. NT-proBNP and LVEF exhibited numerical improvements that were not statistically significant (–200 pg/mL, p = 0.072; +0.8%, p = 0.08). Between-group analyses established a distinct hierarchy: ARNI switch (Group 1) > ACEI/ARB→SGLT2i addition (Group 2) > ARNI→+SGLT2i addition (Group 3), thereby confirming that ARNI initiation represents the most effective therapeutic transition (Table 3 ). Group 1 demonstrated the most significant decreases in hospitalizations (–0.8 compared to − 0.4 and − 0.1 per patient-year, p = 0.018), outpatient visits (–1.7 versus − 1.1 and − 0.4, p = 0.021), and emergency department visits (–1.1 relative to − 0.6 and − 0.1, p = 0.030). Group 1 exhibited the most significant functional and biomarker enhancements: NYHA I–II increased by + 26% compared to + 7.4% and + 3.6% (p = 0.015), LVEF improved by + 6.3% versus + 2.3% and + 0.8% (p = 0.008), and NT-proBNP decreased by − 620 pg/mL in contrast to − 375 pg/mL and − 200 pg/mL (p = 0.033). Graphical analyses corroborate these findings. Figure 1 demonstrates that hospitalization, length of stay, and outpatient visits decreased significantly with ARNI, moderately with ACEI/ARB→SGLT2i, and minimally with ARNI→+SGLT2i. Figure 2 illustrates the most significant shift in NYHA class associated with S/V. Figure 3 illustrates the most significant decreases in NT-proBNP and improvements in LVEF observed in Group 1. Figure 4, a composite difference-in-differences analysis, highlights that ARNI initiation yields the most significant overall reduction in clinical burden. DISCUSSION This real-world analysis of HFrEF patients assessed three treatment options representing GDMT evolution and reimbursement variability. After full titration of baseline beta-blockers and MRA treatment, switching from ACEI/ARB to sacubitril/valsartan had the greatest clinical advantages. This technique consistently reduced hospitalizations, emergency visits, and outpatient consultations and improved NYHA class, NT-proBNP, and LVEF. Adding an SGLT2 inhibitor to optimal ARNI therapy had very minor, non-significant effects, whereas adding it to ACEI/ARB regimens had intermediate benefits. These findings imply that S/V initiation is the most effective treatment transition in real-world HFrEF therapy, surpassing SGLT2i initiation. The PARADIGM-HF trial showed that sacubitril/valsartan reduced cardiovascular mortality and HF hospitalization better than enalapril, while PROVE-HF showed that ARNI rapidly reduced NT-proBNP and reversed remodeling [ 10 , 11 ]. ]. ARNI's early and long-term effects in various HFrEF populations have been proven by real-world registries [ 12 , 13 ]. However, big SGLT2i randomized controlled trials like DAPA-HF and EMPEROR-Reduced consistently reduced HF hospitalization and cardiovascular death [ 5 , 14 ]. A recent meta-analysis confirmed these findings regardless of diabetes status, recommending ARNI and SGLT2i as Class I cornerstone treatments in the 2023 ESC Focused Update [ 2 , 7 ]. Despite this strong trial evidence, our data imply that adding SGLT2i to well optimized S/V, MRA, and BB has modest benefit. The thorough titration of background treatments in our group, with high target doses for MRA (50 mg in most patients), may have diminished the limited benefit of subsequent SGLT2i start. Most of our patients reached the target sacubitril/valsartan dose of 97/103 mg twice daily, unlike in real-world cohorts like PROVE-HF and CHAMP-HF, where only ~ 35–40% reached this dose [ 11 , 15 ]. This aggressive uptitration technique may have increased S/V's clinical advantages in our trial, reducing SGLT2i's incremental advantage. Finally, access-related drug coverage limits caused treatment heterogeneity, as SGLT2i patients differed in socioeconomic and clinical features from S/V patients. In our analysis, S/V was superior because it blocked the renin–angiotensin–aldosterone system and enhanced the natriuretic peptide pathway, resulting in rapid hemodynamic improvement, NT-proBNP decline, and structural reverse remodeling [ 16 ]. In contrast, SGLT2i improve metabolic regulation, osmotic diuresis, and natriuresis [ 17 ]. These mechanisms reduce HF hospitalization over time but may not improve symptoms as much as S/V. Our study's strengths include a large cohort, 2017–2024 follow-up, and stringent adherence to guideline-directed titration regimens before new therapy. These characteristics improve internal validity and demonstrate best-practice GDMT in everyday care. Several limitations must be noted. With retrospective design, biases and residual confounding are inevitable. Access-driven allocation created varied treatment groups. The lack of mortality data precluded comparisons with landmark RCTs. The findings may not apply to all healthcare systems due to the single-center cohort. In conclusion, this study represents one of the most complete real-world assessments of two HFrEF cornerstone therapy. After full background titration, S/V has the greatest and most consistent effects on functional status, NT-proBNP, LVEF, and hospitalizations. SGLT2i are essential in quadruple therapy, but their additive impact is less evident, especially when coupled to optimal S/V therapy. These findings reaffirm sacubitril/valsartan as the key therapeutic transition in HFrEF therapy, with SGLT2i acting as a complement. Declarations Acknowledgements The authors would like to sincerely thank Prof. Dr. Mehmet Birhan Yılmaz for his invaluable mentorship and guidance throughout this project. His expertise in heart failure research and thoughtful input during study design and manuscript preparation substantially enhanced the scientific quality of this work. Funding: This research received no external funding. Conflicts of interest/Competing interests: The authors declare no conflicts of interest. Availability of data and material: Data are available from the corresponding author upon reasonable request. Code availability: Not applicable. Authors’ contributions: SD and OOŞ contributed to study conception, data collection, analysis, and drafting. MBY served as Senior Mentor, providing input in study design and critical revision of the manuscript. Ethics approval: The study protocol was approved by the Local Ethics Committee of Ordu University Faculty of Medicine and conducted in accordance with the Declaration of Helsinki. Consent to participate: Written informed consent was obtained from all participants. 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Tables Table 1 Baseline characteristics of study groups Characteristics Group 1 (ACEI/ARB → S/V) (n = 216) Group 2 (ACEI/ARB → SGLT2i) (n = 190) Group 3 (S/V → + SGLT2i) (n = 220) p-value Age (years) 66.2 ± 9.8 66.8 ± 8.7 67.5 ± 9.1 0.41 Male sex, n (%) 144 (66.7%) 120 (63.2%) 132 (60.0%) 0.38 HF duration (years) 4.5 ± 2.1 4.9 ± 2.2 5.2 ± 2.4 0.12 Ischemic etiology, n (%) 132 (61.1%) 112 (58.9%) 128 (58.2%) 0.77 NYHA class I–II 72 (33.3%) 102 (53.7%) 154 (70.0%) < 0.001 NYHA class III 122 (56.5%) 68 (35.8%) 54 (24.5%) NYHA class IV 22 (10.2%) 20 (10.5%) 12 (5.5%) SBP (mmHg) 119 ± 14 117 ± 13 118 ± 12 0.52 Heart rate (bpm) 77 ± 10 74 ± 11 73 ± 9 0.08 Creatinine (mg/dL) 1.25 ± 0.31 1.21 ± 0.29 1.18 ± 0.28 0.22 NT-proBNP (pg/mL) 2460 ± 880 2395 ± 835 2280 ± 810 0.37 LVEF (%) 28.5 ± 4.2 30.5 ± 4.4 31.2 ± 4.7 0.001 ACEI/ARB, n (%) 216 (100%) 190 (100%) 0 (0%) – S/V, n (%) 0 (0%) 0 (0%) 220 (100%) – Beta-blocker, n (%) 198 (91.7%) 174 (91.6%) 210 (95.5%) 0.19 MRA, n (%) 186 (86.1%) 162 (85.3%) 188 (85.5%) 0.96 Loop diuretic, n (%) 98 (45.4%) 86 (45.3%) 92 (41.8%) 0.62 SGLT2i, n (%) 0 (0%) 0 (0%) 0 (0%) – Target BB dose, n (%) 138 (63.9%) 120 (63.2%) 152 (69.1%) 0.37 Target MRA dose, n (%) 172 (79.6%) 152 (80.0%) 190 (86.4%) 0.21 Target S/V/ACEI/ARB dose, n (%) 174 (80.6%) 154 (81.1%) 178 (80.9%) 0.98 Continuous variables are expressed as mean ± SD; categorical variables are presented as n (%). ACEI = Angiotensin-converting enzyme inhibitor; ARB = Angiotensin receptor blocker; ARNI = Angiotensin receptor–neprilysin inhibitor; BB = Beta-blocker; bpm = Beats per minute; HF = Heart failure; LVEF = Left ventricular ejection fraction; MRA = Mineralocorticoid receptor antagonist; NT-proBNP = N-terminal pro–B-type natriuretic peptide; NYHA = New York Heart Association; SBP = Systolic blood pressure; SD = Standard deviation; SGLT2i = Sodium–glucose cotransporter-2 inhibitor; S/V = Sacubitril/valsartan. Table 2 A. Clinical and laboratory changes in Group 1 (n = 216) Parameters T0 (Pre-S/V) T1 (Post-S/V, 12 months) p-value Outpatient clinic visits, n (%) 186 (86.1%) 124 (57.4%) < 0.001 Annual visits per patient, mean ± SD 3.8 ± 1.2 2.1 ± 0.8 < 0.001 Emergency department visits, n (%) 132 (61.1%) 72 (33.3%) < 0.001 Annual ED visits per patient, mean ± SD 1.9 ± 0.7 0.8 ± 0.4 < 0.001 Hospitalization, n (%) 122 (56.5%) 68 (31.5%) < 0.001 Annual HF hospitalizations per patient 1.4 ± 0.5 0.6 ± 0.3 < 0.001 Average length of stay (days) 8.4 ± 3.2 5.6 ± 2.1 < 0.001 NYHA class I–II, n (%) 72 (33.3%) 128 (59.3%) < 0.001 NYHA class III, n (%) 122 (56.5%) 74 (34.3%) < 0.001 NYHA class IV, n (%) 22 (10.2%) 14 (6.5%) 0.04 NT-proBNP (pg/mL) 2460 ± 880 1840 ± 720 < 0.001 LVEF (%) 28.5 ± 4.2 34.8 ± 5.0 < 0.001 Loop diuretic use, n (%) 98 (45.4%) 74 (34.3%) 0.01 MRA use, n (%) 186 (86.1%) 186 (86.1%) NS Beta-blocker use, n (%) 198 (91.7%) 198 (91.7%) NS Continuous variables are expressed as mean ± SD; categorical variables are presented as n (%). BB = Beta-blocker; ED = Emergency department; HF = Heart failure; LVEF = Left ventricular ejection fraction; MRA = Mineralocorticoid receptor antagonist; NT-proBNP = N-terminal pro–B-type natriuretic peptide; NS = Not significant; NYHA = New York Heart Association; SD = Standard deviation, S/V = Sacubitril/Valsartan Table 2 B. Clinical and laboratory changes in Group 2 (ACEI/ARB → SGLT2i, n = 190) Parameters T0 (Pre-SGLT2i) T1 (Post-SGLT2i, 12 months) p-value Outpatient clinic visits, n (%) 142 (74.7%) 110 (57.9%) 0.048 Annual visits per patient, mean ± SD 3.6 ± 1.1 2.5 ± 0.9 0.046 Emergency department visits, n (%) 116 (61.1%) 86 (45.3%) 0.051 Annual ED visits per patient, mean ± SD 1.7 ± 0.6 1.1 ± 0.5 0.052 Hospitalization, n (%) 106 (55.8%) 80 (42.1%) 0.049 Annual HF hospitalizations per patient 1.3 ± 0.5 0.9 ± 0.4 0.048 Average length of stay (days) 8.0 ± 3.0 6.2 ± 2.4 0.050 NYHA class I–II, n (%) 102 (53.7%) 116 (61.1%) 0.12 NYHA class III, n (%) 68 (35.8%) 58 (30.5%) 0.11 NYHA class IV, n (%) 20 (10.5%) 16 (8.4%) 0.041 NT-proBNP (pg/mL) 2395 ± 835 2020 ± 760 0.047 LVEF (%) 30.5 ± 4.4 32.8 ± 4.9 0.06 Loop diuretic use, n (%) 86 (45.3%) 78 (41.1%) 0.09 MRA use, n (%) 162 (85.3%) 162 (85.3%) NS Beta-blocker use, n (%) 174 (91.6%) 174 (91.6%) NS SGLT-2 inhibitor use, n (%) 0 (0%) 190 (100%) < 0.001 Continuous variables are expressed as mean ± SD; categorical variables are presented as n (%). ED = Emergency department; HF = Heart failure; LVEF = Left ventricular ejection fraction; MRA = Mineralocorticoid receptor antagonist; NT-proBNP = N-terminal pro–B-type natriuretic peptide; NS = Not significant; NYHA = New York Heart Association; SD = Standard deviation; SGLT2i = Sodium–glucose cotransporter-2 inhibitor. Table 2 C. Clinical and laboratory changes in Group 3 (S/V → + SGLT2i, n = 220) Parameters T0 (Pre-SGLT2i) T1 (Post-SGLT2i, 12 months) p-value Outpatient clinic visits, n (%) 148 (67.3%) 132 (60.0%) 0.046 Annual visits per patient, mean ± SD 3.1 ± 1.0 2.7 ± 0.9 0.049 Emergency department visits, n (%) 88 (40.0%) 80 (36.4%) 0.28 Annual ED visits per patient, mean ± SD 1.1 ± 0.4 1.0 ± 0.3 0.30 Hospitalization, n (%) 92 (41.8%) 84 (38.2%) 0.25 Annual HF hospitalizations per patient 0.9 ± 0.4 0.8 ± 0.3 0.20 Average length of stay (days) 7.2 ± 2.8 6.8 ± 2.7 0.18 NYHA class I–II, n (%) 154 (70.0%) 162 (73.6%) 0.22 NYHA class III, n (%) 54 (24.5%) 48 (21.8%) 0.24 NYHA class IV, n (%) 12 (5.5%) 10 (4.5%) 0.30 NT-proBNP (pg/mL) 2280 ± 810 2080 ± 790 0.072 LVEF (%) 31.2 ± 4.7 32.0 ± 4.9 0.08 Loop diuretic use, n (%) 92 (41.8%) 84 (38.2%) 0.082 MRA use, n (%) 188 (85.5%) 188 (85.5%) NS Beta-blocker use, n (%) 210 (95.5%) 210 (95.5%) NS SGLT-2 inhibitor use, n (%) 0 (0%) 220 (100%) < 0.001 Continuous variables are expressed as mean ± SD; categorical variables are presented as n (%) ED = Emergency department; HF = Heart failure; LVEF = Left ventricular ejection fraction; MRA = Mineralocorticoid receptor antagonist; NT-proBNP = N-terminal pro–B-type natriuretic peptide; NS = Not significant; NYHA = New York Heart Association; SD = Standard deviation; SGLT2i = Sodium–glucose cotransporter-2 inhibitor. Table 3 Between-group comparison of changes (Δ = T1 – T0) Parameters (Δ change) Group 1 (S/V, n = 216) Group 2 (SGLT2i after ACEI/ARB, n = 190) Group 3 (SGLT2i after S/V, n = 220) p-value (between groups) Δ Outpatient visits (per patient/year) -1.7 -1.1 -0.4 0.021 Δ ED visits (per patient/year) -1.1 -0.6 -0.1 0.030 Δ Hospitalizations (per patient/year) -0.8 -0.4 -0.1 0.018 Δ Average length of each stay (days) -2.8 -1.8 -0.4 0.042 Δ NYHA I–II (%) + 26.0% + 7.4% + 3.6% 0.015 Δ NYHA III (%) -22.2% -5.3% -2.7% 0.022 Δ NYHA IV (%) -3.7% -2.1% -1.0% 0.12 Δ NT-proBNP (pg/mL) -620 -375 -200 0.033 Δ LVEF (%) + 6.3 + 2.3 + 0.8 0.008 Data are presented as mean changes (Δ) or percentage changes from baseline (T0 to T1). ACEI = Angiotensin-converting enzyme inhibitor; ARB = Angiotensin receptor blocker; ED = Emergency department; HF = Heart failure; LVEF = Left ventricular ejection fraction; NT-proBNP = N-terminal pro–B-type natriuretic peptide; NYHA = New York Heart Association; SD = Standard deviation; SGLT2i = Sodium-glucose cotransporter-2 inhibitor; S/V = Sacubitril/Valsartan Cite Share Download PDF Status: Posted 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-7511564","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":511875205,"identity":"2f1ecafb-d329-41ac-8fce-6db21bba6364","order_by":0,"name":"Seçkin Dereli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYDCCA2BCAsJ4YGADJBkbDxCvJcEgDaSlgRgtUJzAcBghiAvw3T7+8MGPMxZ5fMd7Hz5IKDhvt7b9MNCWGptoXFokz+UYG/bckCiWPHPc2CDB4HbytjOJQC3H0nIbcGgxOMPDJs3wQSJxw400NgmQFrMDQC2MDYfxaGF//hus5f4z9h8JBueSzc4/JKSFwYyZ4QbIFjY2YIgdsDO7QcAWyTM8xpI9ZyQSZ55JYwY6LDnB7AbQlgQ8fuE7w/7ww49jdYl9x48xfvjwx87e7Hz6wwcfamxwasEAiWCVCcQqBwF7UhSPglEwCkbByAAAzm9sCAqoUzQAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0090-3835","institution":"Ordu University Faculty of Medicine: Ordu Universitesi Tip Fakultesi","correspondingAuthor":true,"prefix":"","firstName":"Seçkin","middleName":"","lastName":"Dereli","suffix":""},{"id":511875206,"identity":"4e0b34af-2dd5-4526-9702-b65110facb5b","order_by":1,"name":"Onur Osman Şeker","email":"","orcid":"","institution":"Samsun Education and Research Hospital: TC Saglik Bakanligi Samsun Egitim ve Arastirma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Onur","middleName":"Osman","lastName":"Şeker","suffix":""}],"badges":[],"createdAt":"2025-09-01 21:19:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7511564/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7511564/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91816876,"identity":"82d964df-9eac-42a2-a520-eb1140615355","added_by":"auto","created_at":"2025-09-22 06:52:51","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10543352,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2NYHA.tif","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/8145686683fa1a01226c38f5.tif"},{"id":91816811,"identity":"6c6210fa-7e0d-4d25-9379-a24f7dbbd1d0","added_by":"auto","created_at":"2025-09-22 06:52:46","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":906,"visible":true,"origin":"","legend":"","description":"","filename":"CDTYD2500968Import.xml","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/281910ffb87e82ed3f2f8726.xml"},{"id":91816798,"identity":"08901bee-dde5-4cdf-82bc-c4bf6bee1493","added_by":"auto","created_at":"2025-09-22 06:52:45","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":115639,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2NYHA.png","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/b58f3700478bc89fd0e408fd.png"},{"id":91816806,"identity":"3bd95ff3-b551-4530-8cb1-aba8e82ccdc9","added_by":"auto","created_at":"2025-09-22 06:52:45","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":98672,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/3b7c935e95c11688792af384.html"},{"id":91817109,"identity":"65adf762-ac5b-4223-8457-5e187472e4ff","added_by":"auto","created_at":"2025-09-22 06:53:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":173316,"visible":true,"origin":"","legend":"\u003cp\u003eMulticomponent outcomes before and after \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;treatment modification (T0 vs T1). (A) Hospitalization rate, (B) average length of stay, (C) annual HF hospitalizations per patient, and (D) annual outpatient visits per patient. Bars represent mean values ± SD, with p-values for within-group comparisons shown above.\u003c/p\u003e","description":"","filename":"Figure1HospVisits.png","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/6c121fd724167d8e20de9e93.png"},{"id":91487728,"identity":"18d5a852-99de-444a-95bb-901f3ae75056","added_by":"auto","created_at":"2025-09-17 05:04:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":219751,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of NYHA functional class at baseline (T0) and 12 months (T1) in each study group. Stacked bars indicate relative proportions; p-values represent within-group comparisons.\u003c/p\u003e","description":"","filename":"Figure2NYHA.png","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/08638d3e58585fd7d7abe17b.png"},{"id":91487727,"identity":"d0a22f6a-98f7-4916-905b-bf035df79769","added_by":"auto","created_at":"2025-09-17 05:04:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":255428,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in NT-proBNP levels and LVEF at baseline (T0) and after 12 months (T1) for each group. Data are presented as mean ± SD, with significance levels shown above comparisons.\u003c/p\u003e","description":"","filename":"Figure3BNPLVEF.png","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/64a78303998d9c4fa73804cf.png"},{"id":91817979,"identity":"4acaeac0-12f6-4686-a2dc-17d80f890e1d","added_by":"auto","created_at":"2025-09-22 07:01:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1649973,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7511564/v1/11a4fb06-9fdc-48b2-8db6-9b3a15a9bdf8.pdf"}],"financialInterests":"","formattedTitle":"Comparative Real-World Effectiveness of Sacubitril/Valsartan and SGLT2 Inhibitors in Patients with HFrEF: A Retrospective Cohort Study","fulltext":[{"header":"HIGHLIGHTS","content":"\u003cp\u003e\u0026middot;\u0026nbsp; Real-world HFrEF cohort (n=626) on optimized beta-blocker and RAAS therapy.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; ACEI/ARB\u0026rarr;S/V associated with 61% fewer HF hospitalizations (1.8\u0026rarr;0.7 pp-yr).\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; Greater biomarker gains with S/V: NT-proBNP \u0026minus;48%; LVEF +7.1% (p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; ACEI/ARB\u0026rarr;+SGLT2i showed smaller changes: NT-proBNP \u0026minus;15%; LVEF +2.3%.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp;Adding SGLT2i on S/V gave modest, mostly non-significant, incremental benefit.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eHeart failure with reduced ejection fraction (HFrEF) remains a significant global challenge, characterized by alarmingly high rates of hospitalization and mortality, although improvements in guideline-directed medical therapy (GDMT) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Current evidence-based guidelines underscore the necessity of employing four fundamental pharmacological classes: angiotensin receptor\u0026ndash;neprilysin inhibitors (ARNI), beta-blockers, mineralocorticoid receptor antagonists (MRAs), and sodium\u0026ndash;glucose cotransporter-2 inhibitors (SGLT2i) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSacubitril/valsartan (S/V) was the inaugural treatment to exhibit a significant advantage, as evidenced by the PARADIGM-HF study, which revealed considerable and enduring decreases in cardiovascular mortality and heart failure hospitalizations in comparison to enalapril. Subsequent research verified that the therapeutic effects of ARNI manifest swiftly after initiation, resulting in early enhancements in symptoms, natriuretic peptide levels, and hemodynamic status, alongside sustained long-term prognosis benefits [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSGLT2 inhibitors, first designed as glucose-lowering medications, have now transformed heart failure management by exhibiting significant efficacy regardless of diabetes status. Extensive randomized controlled trials, including DAPA-HF and EMPEROR-Reduced, along with meta-analyses, consistently demonstrated substantial reductions in heart failure hospitalizations, cardiovascular mortality, and enhancements in quality of life [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These findings established SGLT2 inhibitors as a Class I recommendation in the latest guidelines [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Their mechanism of improvement, however, seems to be distinct and more gradual compared to the acute hemodynamic changes noted with S/V.\u003c/p\u003e\u003cp\u003eNotwithstanding these advancements, direct randomized comparisons between S/V and SGLT2i are absent, and conducting such trials would pose ethical dilemmas due to the established Class I prescription for both treatments. Real-world practice patterns, however, present a distinctive chance to assess their comparative clinical efficacy. Heterogeneity specifically occurs in health systems where reimbursement limitations restrict universal access\u0026mdash;some patients receive S/V following optimal titration of ACEi/ARB, MRA, and beta-blockers, while others commence SGLT2i either in conjunction with S/V or as an adjunct to optimized background therapy without S/V [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aims to retrospectively compare three independent patient groups with HFrEF who received optimum background treatment before the commencement of S/V or SGLT2i. The main aim was to assess alterations in hospitalization, emergency department admissions, outpatient clinic visits, and functional capacity prior to and following the commencement of treatment. We posited that S/V, in addition to the advantages of SGLT2i, provides more substantial, timely, and enduring enhancements in morbidity and functional outcomes, hence affirming its supremacy as the cornerstone of HFrEF therapy.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and population\u003c/h2\u003e\u003cp\u003eThis retrospective observational analysis encompassed individuals with HFrEF monitored from January 2017 to December 2024 at a tertiary cardiology institution. Eligible patients were aged 18 years or older, exhibited a left ventricular ejection fraction (LVEF) of 40% or less, and presented with New York Heart Association (NYHA) class II to IV symptoms. All patients were mandated to have completed systematic and quick dose titration of guideline-directed medical therapy (GDMT), encompassing beta-blockers and mineralocorticoid receptor antagonists (MRAs), to the maximum tolerated or target levels. Prior to therapy adjustment, dosage optimization was confirmed, with over 90% of patients attaining at least 50% of the target doses for beta-blockers and MRAs, and all patients receiving at least 50% of ACEIs/ARBs or S/V. During follow-up, modifications to the doses of S/V or other neurohormonal antagonists were permitted in instances of adverse effects such as hypotension, hyperkalemia, or renal impairment; however, no patient necessitated permanent discontinuation, and all medications were sustained throughout the research duration.\u003c/p\u003e\u003cp\u003eExclusion criteria were the presence of malignancy, acute coronary syndrome, major surgery or trauma during the observation period, or cardiac resynchronization therapy (CRT) within 6 months prior to index treatment modification.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGroup definitions\u003c/h3\u003e\n\u003cp\u003ePatients were categorized into three groups according to treatment strategy:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGroup 1\u003c/strong\u003e\u003cp\u003ePatients optimized on ACE inhibitors/angiotensin receptor blockers, mineralocorticoid receptor antagonists, and beta-blockers who were then transitioned to S/V.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGroup 2\u003c/strong\u003e\u003cp\u003ePatients who were optimized on ACEI/ARB, MRA, and beta-blocker medication, to whom an SGLT2 inhibitor was subsequently administered. This cohort primarily comprised diabetic and non-diabetic HFrEF patients who consented to SGLT2i therapy but could not afford S/V due to out-of-pocket expenses.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGroup 3\u003c/strong\u003e\u003cp\u003ePatients receiving optimal ARNI, MRA, and beta-blocker therapy, to whom an SGLT2 inhibitor was later introduced.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eThe justification for these group classifications is rooted on both clinical practice and healthcare policy in T\u0026uuml;rkiye: S/V received a Class I recommendation in heart failure recommendations prior to SGLT2i, and both treatments continue to be non-reimbursed for non-diabetic HFrEF patients.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eBaseline demographics, comorbidities, functional class, laboratory parameters, echocardiographic measurements, and medical therapy were collected retrospectively at T0. Outcomes were evaluated at both T0 and T1 as follows:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eOutpatient cardiology clinic visits\u003c/b\u003e: the percentage of patients attending the cardiology outpatient clinic was recorded, and the average annual number of visits per patient was calculated over the total number of visits.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEmergency department (ED) admissions\u003c/b\u003e: the percentage of patients admitted to the ED was documented, and the average annual number of ED admissions per patient was calculated over the total admissions.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eHospitalizations\u003c/b\u003e: hospital admissions were evaluated in two subgroups as admissions to the cardiac intensive care unit (CICU) and admissions to the medical ward. The percentage of hospitalized patients was determined, the average annual number of hospitalizations per patient was calculated over the total number of admissions, and the average length of stay (LOS) was calculated over the total number of hospitalization days.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eNYHA class, NT-proBNP levels, and LVEF were evaluated at both T0 and T1. Data were extracted from hospital electronic medical records and the national \u003cb\u003ee-Nabız\u003c/b\u003e system, which integrates individual-level medical data across all public and private health institutions in T\u0026uuml;rkiye.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary endpoints were changes in annualized heart failure hospitalizations, ED admissions, outpatient clinic visits, and hospitalization LOS. Secondary endpoints included changes in NT-proBNP, LVEF, and NYHA class distribution.\u003c/p\u003e\n\u003ch3\u003eEthics\u003c/h3\u003e\n\u003cp\u003e The study protocol was approved by the local ethics committee and conducted in accordance with the Declaration of Helsinki. All patients provided informed consent.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (interquartile range, IQR) according to their distribution, which was assessed by the Shapiro\u0026ndash;Wilk test. Categorical variables were presented as counts and percentages (n, %). Baseline characteristics between the three treatment groups were compared using one-way ANOVA or Kruskal\u0026ndash;Wallis tests for continuous variables and chi-square or Fisher\u0026rsquo;s exact test for categorical variables. Within-group comparisons of T0 (pre-treatment) and T1 (post-treatment) were performed using paired-samples t-test or Wilcoxon signed-rank test for continuous variables and McNemar\u0026rsquo;s test for categorical variables. Between-group comparisons of treatment effect (Δ\u0026thinsp;=\u0026thinsp;T1\u0026ndash;T0) were assessed using repeated measures ANOVA with Bonferroni correction or generalized estimating equations (GEE) to account for within-subject correlations, given that the groups were heterogeneous and not perfectly balanced. Given baseline differences in LVEF and NYHA class, additional models were run including these variables as covariates (ANCOVA approach), which did not materially change the results. Effect sizes were calculated to better illustrate clinical relevance in addition to p values. A two-tailed p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were performed using SPSS version XX (IBM Corp., Armonk, NY, USA).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 626 patients were analyzed, comprising 216 in Group 1 (ACEI/ARB\u0026rarr;S/V), 190 in Group 2 (ACEI/ARB\u0026rarr;SGLT2i), and 220 in Group 3 (ARNI\u0026rarr;+SGLT2i). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents baseline demographics, comorbidities, and background therapy. The three cohorts exhibited general comparability; however, Group 3 patients demonstrated a greater proportion of NYHA class I\u0026ndash;II (70%) and a marginally elevated mean LVEF (31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7%) relative to Groups 1 and 2. Guideline-directed dose optimization was consistently achieved, with over 90% of patients reaching at least 50% of the target doses for beta-blockers and MRAs. Additionally, all patients received at least 50% of ACEI/ARB or S/V before any treatment modifications (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No patient permanently discontinued sacubitril/valsartan, SGLT2i, or background neurohormonal blockade. Temporary dose reductions occurred in a minority of cases due to hypotension or renal fluctuations; however, all patients remained on full multidrug therapy at the conclusion of follow-up.\u003c/p\u003e\u003cp\u003eA direct comparison indicated that the transition from ACEI/ARB to ARNI (Group 1) resulted in significantly greater improvements compared to the transition from ACEI/ARB to SGLT2i (Group 2). Furthermore, the addition of SGLT2i on top of ARNI (Group 3) provided only incremental benefits (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;C). Hospitalizations decreased from 56.5\u0026ndash;31.5% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), accompanied by similar reductions in emergency department visits and outpatient consultations, each exceeding 40% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The length of stay was significantly reduced from 8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 days to 5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 days (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Functional status demonstrated significant improvement: NYHA I\u0026ndash;II increased from 33.3\u0026ndash;59.3% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), NT-proBNP decreased by approximately 620 pg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and LVEF improved by 6.3% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eIn Group 2, the addition of SGLT2i to ACEI/ARB therapy yielded more modest benefits (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Hospitalization rates decreased from 55.8\u0026ndash;42.1% (p\u0026thinsp;=\u0026thinsp;0.049), with a marginal reduction in length of stay observed (8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0 to 6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 days, p\u0026thinsp;=\u0026thinsp;0.050). There was a significant decrease in outpatient visits, from 3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 to 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 per year (p\u0026thinsp;=\u0026thinsp;0.046). NT-proBNP decreased by approximately 375 pg/mL (p\u0026thinsp;=\u0026thinsp;0.047), while the enhancement in LVEF (+\u0026thinsp;2.3%) did not achieve statistical significance (p\u0026thinsp;=\u0026thinsp;0.06). The proportion of NYHA IV patients decreased significantly from 10.5\u0026ndash;8.4% (p\u0026thinsp;=\u0026thinsp;0.041).\u003c/p\u003e\u003cp\u003eIn Group 3 (ARNI\u0026rarr;+SGLT2i), the incremental benefit was reduced (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Outpatient visits exhibited a modest reduction (p\u0026thinsp;=\u0026thinsp;0.046), whereas hospitalizations, emergency department visits, and length of stay remained statistically unchanged. NT-proBNP and LVEF exhibited numerical improvements that were not statistically significant (\u0026ndash;200 pg/mL, p\u0026thinsp;=\u0026thinsp;0.072; +0.8%, p\u0026thinsp;=\u0026thinsp;0.08).\u003c/p\u003e\u003cp\u003eBetween-group analyses established a distinct hierarchy: ARNI switch (Group 1)\u0026thinsp;\u0026gt;\u0026thinsp;ACEI/ARB\u0026rarr;SGLT2i addition (Group 2)\u0026thinsp;\u0026gt;\u0026thinsp;ARNI\u0026rarr;+SGLT2i addition (Group 3), thereby confirming that ARNI initiation represents the most effective therapeutic transition (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Group 1 demonstrated the most significant decreases in hospitalizations (\u0026ndash;0.8 compared to \u0026minus;\u0026thinsp;0.4 and \u0026minus;\u0026thinsp;0.1 per patient-year, p\u0026thinsp;=\u0026thinsp;0.018), outpatient visits (\u0026ndash;1.7 versus \u0026minus;\u0026thinsp;1.1 and \u0026minus;\u0026thinsp;0.4, p\u0026thinsp;=\u0026thinsp;0.021), and emergency department visits (\u0026ndash;1.1 relative to \u0026minus;\u0026thinsp;0.6 and \u0026minus;\u0026thinsp;0.1, p\u0026thinsp;=\u0026thinsp;0.030). Group 1 exhibited the most significant functional and biomarker enhancements: NYHA I\u0026ndash;II increased by +\u0026thinsp;26% compared to +\u0026thinsp;7.4% and +\u0026thinsp;3.6% (p\u0026thinsp;=\u0026thinsp;0.015), LVEF improved by +\u0026thinsp;6.3% versus +\u0026thinsp;2.3% and +\u0026thinsp;0.8% (p\u0026thinsp;=\u0026thinsp;0.008), and NT-proBNP decreased by \u0026minus;\u0026thinsp;620 pg/mL in contrast to \u0026minus;\u0026thinsp;375 pg/mL and \u0026minus;\u0026thinsp;200 pg/mL (p\u0026thinsp;=\u0026thinsp;0.033).\u003c/p\u003e\u003cp\u003eGraphical analyses corroborate these findings. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e demonstrates that hospitalization, length of stay, and outpatient visits decreased significantly with ARNI, moderately with ACEI/ARB\u0026rarr;SGLT2i, and minimally with ARNI\u0026rarr;+SGLT2i. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the most significant shift in NYHA class associated with S/V. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the most significant decreases in NT-proBNP and improvements in LVEF observed in Group 1. Figure\u0026nbsp;4, a composite difference-in-differences analysis, highlights that ARNI initiation yields the most significant overall reduction in clinical burden.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis real-world analysis of HFrEF patients assessed three treatment options representing GDMT evolution and reimbursement variability. After full titration of baseline beta-blockers and MRA treatment, switching from ACEI/ARB to sacubitril/valsartan had the greatest clinical advantages. This technique consistently reduced hospitalizations, emergency visits, and outpatient consultations and improved NYHA class, NT-proBNP, and LVEF. Adding an SGLT2 inhibitor to optimal ARNI therapy had very minor, non-significant effects, whereas adding it to ACEI/ARB regimens had intermediate benefits. These findings imply that S/V initiation is the most effective treatment transition in real-world HFrEF therapy, surpassing SGLT2i initiation.\u003c/p\u003e\u003cp\u003eThe PARADIGM-HF trial showed that sacubitril/valsartan reduced cardiovascular mortality and HF hospitalization better than enalapril, while PROVE-HF showed that ARNI rapidly reduced NT-proBNP and reversed remodeling [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. ]. ARNI's early and long-term effects in various HFrEF populations have been proven by real-world registries [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, big SGLT2i randomized controlled trials like DAPA-HF and EMPEROR-Reduced consistently reduced HF hospitalization and cardiovascular death [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A recent meta-analysis confirmed these findings regardless of diabetes status, recommending ARNI and SGLT2i as Class I cornerstone treatments in the 2023 ESC Focused Update [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite this strong trial evidence, our data imply that adding SGLT2i to well optimized S/V, MRA, and BB has modest benefit. The thorough titration of background treatments in our group, with high target doses for MRA (50 mg in most patients), may have diminished the limited benefit of subsequent SGLT2i start. Most of our patients reached the target sacubitril/valsartan dose of 97/103 mg twice daily, unlike in real-world cohorts like PROVE-HF and CHAMP-HF, where only\u0026thinsp;~\u0026thinsp;35\u0026ndash;40% reached this dose [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This aggressive uptitration technique may have increased S/V's clinical advantages in our trial, reducing SGLT2i's incremental advantage. Finally, access-related drug coverage limits caused treatment heterogeneity, as SGLT2i patients differed in socioeconomic and clinical features from S/V patients.\u003c/p\u003e\u003cp\u003eIn our analysis, S/V was superior because it blocked the renin\u0026ndash;angiotensin\u0026ndash;aldosterone system and enhanced the natriuretic peptide pathway, resulting in rapid hemodynamic improvement, NT-proBNP decline, and structural reverse remodeling [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In contrast, SGLT2i improve metabolic regulation, osmotic diuresis, and natriuresis [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These mechanisms reduce HF hospitalization over time but may not improve symptoms as much as S/V.\u003c/p\u003e\u003cp\u003e Our study's strengths include a large cohort, 2017\u0026ndash;2024 follow-up, and stringent adherence to guideline-directed titration regimens before new therapy. These characteristics improve internal validity and demonstrate best-practice GDMT in everyday care. Several limitations must be noted. With retrospective design, biases and residual confounding are inevitable. Access-driven allocation created varied treatment groups. The lack of mortality data precluded comparisons with landmark RCTs. The findings may not apply to all healthcare systems due to the single-center cohort.\u003c/p\u003e\u003cp\u003eIn conclusion, this study represents one of the most complete real-world assessments of two HFrEF cornerstone therapy. After full background titration, S/V has the greatest and most consistent effects on functional status, NT-proBNP, LVEF, and hospitalizations. SGLT2i are essential in quadruple therapy, but their additive impact is less evident, especially when coupled to optimal S/V therapy. These findings reaffirm sacubitril/valsartan as the key therapeutic transition in HFrEF therapy, with SGLT2i acting as a complement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to sincerely thank \u003cem\u003eProf. Dr. Mehmet Birhan Yılmaz\u0026nbsp;\u003c/em\u003efor his invaluable mentorship and guidance throughout this project. His expertise in heart failure research and thoughtful input during study design and manuscript preparation substantially enhanced the scientific quality of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eData are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003eSD and OOŞ contributed to study conception, data collection, analysis, and drafting. MBY served as Senior Mentor, providing input in study design and critical revision of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eThe study protocol was approved by the Local Ethics Committee of Ordu University Faculty of Medicine and conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eWritten informed consent was obtained from all participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcDonagh TA et al. 2021 \u003cem\u003eESC 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.\u003c/em\u003e European heart journal, 2021. 42(36): pp. 3599\u0026ndash;3726.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcDonagh TA et al. \u003cem\u003e2023 focused update of the 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.\u003c/em\u003e European heart journal, 2023. 44(37): pp. 3627\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLewis EF et al. \u003cem\u003eHealth-related quality of life outcomes in PARADIGM-HF.\u003c/em\u003e Circulation: Heart Failure, 2017. 10(8): p. e003430.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeferovic JP, et al. Effect of sacubitril/valsartan versus enalapril on glycaemic control in patients with heart failure and diabetes: a post-hoc analysis from the PARADIGM-HF trial. lancet Diabetes Endocrinol. 2017;5(5):333\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcMurray JJ, et al. Dapagliflozin in patients with heart failure and reduced ejection fraction. N Engl J Med. 2019;381(21):1995\u0026ndash;2008.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnker SD, et al. Empagliflozin in heart failure with a preserved ejection fraction. N Engl J Med. 2021;385(16):1451\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLu Y, et al. Effect of SGLT-2 inhibitors on cardiovascular outcomes in heart failure patients: a meta-analysis of randomized controlled trials. Eur J Intern Med. 2021;87:20\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBurgos LM, et al. In-hospital initiation of sodium-glucose cotransporter-2 inhibitors in patients with heart failure and reduced ejection fraction: 90-day prescription patterns and clinical implications. Curr Probl Cardiol. 2024;49(10):102779.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElserafy AS, et al. Egyptian atherosclerosis and vascular biology association consensus on the use of sodium glucose cotransporter-2 inhibitors in heart failure with reduced ejection fraction. Clin Drug Investig. 2021;41(12):1027\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcMurray JJ, et al. Angiotensin\u0026ndash;neprilysin inhibition versus enalapril in heart failure. N Engl J Med. 2014;371(11):993\u0026ndash;1004.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJanuzzi JL, et al. Association of change in N-terminal pro\u0026ndash;B-type natriuretic peptide following initiation of sacubitril-valsartan treatment with cardiac structure and function in patients with heart failure with reduced ejection fraction. JAMA. 2019;322(11):1085\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartens P, et al. Impact of sacubitril/valsartan on heart failure admissions: insights from real-world patient prescriptions. Acta Cardiol. 2019;74(2):115\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDereli S, et al. Impact of sacubitril/valsartan treatment on depression and anxiety in heart failure with reduced ejection fraction. Acta Cardiol. 2020;75(8):774\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePacker M, et al. Cardiovascular and renal outcomes with empagliflozin in heart failure. N Engl J Med. 2020;383(15):1413\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeVore AD, et al. Characteristics and treatments of patients enrolled in the CHAMP-HF registry compared with patients enrolled in the PARADIGM‐HF trial. J Am Heart Association. 2018;7(12):e009237.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSolomon SD, et al. Sacubitril/valsartan across the spectrum of ejection fraction in heart failure. Circulation. 2020;141(5):352\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScheen AJ. Sodium\u0026ndash;glucose cotransporter type 2 inhibitors for the treatment of type 2 diabetes mellitus. Nat reviews Endocrinol. 2020;16(10):556\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\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\u003eBaseline characteristics of study groups\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1 (ACEI/ARB \u0026rarr; S/V)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;216)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2 (ACEI/ARB \u0026rarr; SGLT2i)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3 (S/V \u0026rarr; + SGLT2i)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;220)\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\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale sex, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e144 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 (63.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132 (60.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHF duration (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIschemic etiology, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e132 (61.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e112 (58.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e128 (58.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNYHA class I\u0026ndash;II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102 (53.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e154 (70.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" 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\u003eNYHA class III\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e122 (56.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68 (35.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (24.5%)\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\u003eNYHA class IV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (10.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (10.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (5.5%)\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\u003eSBP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e119\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e117\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e118\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart rate (bpm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNT-proBNP (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2460\u0026thinsp;\u0026plusmn;\u0026thinsp;880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2395\u0026thinsp;\u0026plusmn;\u0026thinsp;835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2280\u0026thinsp;\u0026plusmn;\u0026thinsp;810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVEF (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEI/ARB, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e216 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e190 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS/V, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e220 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeta-blocker, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e198 (91.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e174 (91.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e210 (95.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMRA, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e186 (86.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e162 (85.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e188 (85.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoop diuretic, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98 (45.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (45.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92 (41.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSGLT2i, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTarget BB dose, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e138 (63.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 (63.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e152 (69.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTarget MRA dose, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e172 (79.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e152 (80.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e190 (86.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTarget S/V/ACEI/ARB dose, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e174 (80.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e154 (81.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e178 (80.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eContinuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; categorical variables are presented as n (%).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eACEI\u0026thinsp;=\u0026thinsp;Angiotensin-converting enzyme inhibitor; ARB\u0026thinsp;=\u0026thinsp;Angiotensin receptor blocker; ARNI\u0026thinsp;=\u0026thinsp;Angiotensin receptor\u0026ndash;neprilysin inhibitor; BB\u0026thinsp;=\u0026thinsp;Beta-blocker; bpm\u0026thinsp;=\u0026thinsp;Beats per minute; HF\u0026thinsp;=\u0026thinsp;Heart failure; LVEF\u0026thinsp;=\u0026thinsp;Left ventricular ejection fraction; MRA\u0026thinsp;=\u0026thinsp;Mineralocorticoid receptor antagonist; NT-proBNP\u0026thinsp;=\u0026thinsp;N-terminal pro\u0026ndash;B-type natriuretic peptide; NYHA\u0026thinsp;=\u0026thinsp;New York Heart Association; SBP\u0026thinsp;=\u0026thinsp;Systolic blood pressure; SD\u0026thinsp;=\u0026thinsp;Standard deviation; SGLT2i\u0026thinsp;=\u0026thinsp;Sodium\u0026ndash;glucose cotransporter-2 inhibitor; S/V\u0026thinsp;=\u0026thinsp;Sacubitril/valsartan.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\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\u003eA.\u003c/b\u003e Clinical and laboratory changes in Group 1 (n\u0026thinsp;=\u0026thinsp;216)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0 (Pre-S/V)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eT1 (Post-S/V, 12 months)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\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\u003eOutpatient clinic visits, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e186 (86.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124 (57.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eAnnual visits per patient, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eEmergency department visits, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e132 (61.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eAnnual ED visits per patient, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eHospitalization, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e122 (56.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68 (31.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eAnnual HF hospitalizations per patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eAverage length of stay (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eNYHA class I\u0026ndash;II, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128 (59.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eNYHA class III, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e122 (56.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (34.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eNYHA class IV, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (10.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (6.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNT-proBNP (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2460\u0026thinsp;\u0026plusmn;\u0026thinsp;880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1840\u0026thinsp;\u0026plusmn;\u0026thinsp;720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eLVEF (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003eLoop diuretic use, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98 (45.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (34.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMRA use, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e186 (86.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e186 (86.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeta-blocker use, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e198 (91.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e198 (91.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eContinuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; categorical variables are presented as n (%).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eBB\u0026thinsp;=\u0026thinsp;Beta-blocker; ED\u0026thinsp;=\u0026thinsp;Emergency department; HF\u0026thinsp;=\u0026thinsp;Heart failure; LVEF\u0026thinsp;=\u0026thinsp;Left ventricular ejection fraction; MRA\u0026thinsp;=\u0026thinsp;Mineralocorticoid receptor antagonist; NT-proBNP\u0026thinsp;=\u0026thinsp;N-terminal pro\u0026ndash;B-type natriuretic peptide; NS\u0026thinsp;=\u0026thinsp;Not significant; NYHA\u0026thinsp;=\u0026thinsp;New York Heart Association; SD\u0026thinsp;=\u0026thinsp;Standard deviation, S/V\u0026thinsp;=\u0026thinsp;Sacubitril/Valsartan\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eB.\u003c/span\u003e Clinical and laboratory changes in Group 2 (ACEI/ARB \u0026rarr; SGLT2i, n\u0026thinsp;=\u0026thinsp;190)\u003c/div\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eParameters\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eT0 (Pre-SGLT2i)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eT1 (Post-SGLT2i, 12 months)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003ep-value\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eOutpatient clinic visits, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e142 (74.7%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e110 (57.9%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.048\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAnnual visits per patient, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.046\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eEmergency department visits, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e116 (61.1%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e86 (45.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.051\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAnnual ED visits per patient, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.052\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eHospitalization, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e106 (55.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e80 (42.1%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.049\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAnnual HF hospitalizations per patient\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.048\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAverage length of stay (days)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.050\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNYHA class I\u0026ndash;II, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e102 (53.7%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e116 (61.1%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.12\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNYHA class III, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e68 (35.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e58 (30.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.11\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNYHA class IV, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e20 (10.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e16 (8.4%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.041\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNT-proBNP (pg/mL)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e2395\u0026thinsp;\u0026plusmn;\u0026thinsp;835\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e2020\u0026thinsp;\u0026plusmn;\u0026thinsp;760\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.047\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eLVEF (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e32.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.06\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eLoop diuretic use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e86 (45.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e78 (41.1%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.09\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMRA use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e162 (85.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e162 (85.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eNS\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBeta-blocker use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e174 (91.6%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e174 (91.6%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eNS\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eSGLT-2 inhibitor use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e0 (0%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e190 (100%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eContinuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; categorical variables are presented as n (%).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eED\u0026thinsp;=\u0026thinsp;Emergency department; HF\u0026thinsp;=\u0026thinsp;Heart failure; LVEF\u0026thinsp;=\u0026thinsp;Left ventricular ejection fraction; MRA\u0026thinsp;=\u0026thinsp;Mineralocorticoid receptor antagonist; NT-proBNP\u0026thinsp;=\u0026thinsp;N-terminal pro\u0026ndash;B-type natriuretic peptide; NS\u0026thinsp;=\u0026thinsp;Not significant; NYHA\u0026thinsp;=\u0026thinsp;New York Heart Association; SD\u0026thinsp;=\u0026thinsp;Standard deviation; SGLT2i\u0026thinsp;=\u0026thinsp;Sodium\u0026ndash;glucose cotransporter-2 inhibitor.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cbr/\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eC.\u003c/span\u003e Clinical and laboratory changes in Group 3 (S/V \u0026rarr; + SGLT2i, n\u0026thinsp;=\u0026thinsp;220)\u003c/div\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eParameters\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eT0 (Pre-SGLT2i)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eT1 (Post-SGLT2i, 12 months)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003ep-value\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eOutpatient clinic visits, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e148 (67.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e132 (60.0%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.046\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAnnual visits per patient, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.049\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eEmergency department visits, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e88 (40.0%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e80 (36.4%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.28\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAnnual ED visits per patient, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.30\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eHospitalization, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e92 (41.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e84 (38.2%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.25\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAnnual HF hospitalizations per patient\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.20\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAverage length of stay (days)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.18\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNYHA class I\u0026ndash;II, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e154 (70.0%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e162 (73.6%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.22\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNYHA class III, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e54 (24.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e48 (21.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.24\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNYHA class IV, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e12 (5.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e10 (4.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.30\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNT-proBNP (pg/mL)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e2280\u0026thinsp;\u0026plusmn;\u0026thinsp;810\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e2080\u0026thinsp;\u0026plusmn;\u0026thinsp;790\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.072\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eLVEF (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e32.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.08\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eLoop diuretic use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e92 (41.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e84 (38.2%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.082\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMRA use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e188 (85.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e188 (85.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eNS\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBeta-blocker use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e210 (95.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e210 (95.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eNS\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eSGLT-2 inhibitor use, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e0 (0%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e220 (100%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eContinuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; categorical variables are presented as n (%)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eED\u0026thinsp;=\u0026thinsp;Emergency department; HF\u0026thinsp;=\u0026thinsp;Heart failure; LVEF\u0026thinsp;=\u0026thinsp;Left ventricular ejection fraction; MRA\u0026thinsp;=\u0026thinsp;Mineralocorticoid receptor antagonist; NT-proBNP\u0026thinsp;=\u0026thinsp;N-terminal pro\u0026ndash;B-type natriuretic peptide; NS\u0026thinsp;=\u0026thinsp;Not significant; NYHA\u0026thinsp;=\u0026thinsp;New York Heart Association; SD\u0026thinsp;=\u0026thinsp;Standard deviation; SGLT2i\u0026thinsp;=\u0026thinsp;Sodium\u0026ndash;glucose cotransporter-2 inhibitor.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cbr/\u003e\n\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBetween-group comparison of changes (Δ\u0026thinsp;=\u0026thinsp;T1 \u0026ndash; T0)\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\u003eParameters (Δ change)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1 (S/V, n\u0026thinsp;=\u0026thinsp;216)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2 (SGLT2i after ACEI/ARB, n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3 (SGLT2i after S/V, n\u0026thinsp;=\u0026thinsp;220)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003cp\u003e(between groups)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ Outpatient visits (per patient/year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ ED visits (per patient/year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ Hospitalizations (per patient/year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ Average length of each stay (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ NYHA I\u0026ndash;II (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;26.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;7.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u0026thinsp;3.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ NYHA III (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-22.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-5.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ NYHA IV (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.0%\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\u003eΔ NT-proBNP (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ LVEF (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are presented as mean changes (Δ) or percentage changes from baseline (T0 to T1).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eACEI\u0026thinsp;=\u0026thinsp;Angiotensin-converting enzyme inhibitor; ARB\u0026thinsp;=\u0026thinsp;Angiotensin receptor blocker; ED\u0026thinsp;=\u0026thinsp;Emergency department; HF\u0026thinsp;=\u0026thinsp;Heart failure; LVEF\u0026thinsp;=\u0026thinsp;Left ventricular ejection fraction; NT-proBNP\u0026thinsp;=\u0026thinsp;N-terminal pro\u0026ndash;B-type natriuretic peptide; NYHA\u0026thinsp;=\u0026thinsp;New York Heart Association; SD\u0026thinsp;=\u0026thinsp;Standard deviation; SGLT2i\u0026thinsp;=\u0026thinsp;Sodium-glucose cotransporter-2 inhibitor; S/V\u0026thinsp;=\u0026thinsp;Sacubitril/Valsartan\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Heart failure with reduced ejection fraction (HFrEF), Sacubitril/valsartan (S/V), SGLT2 inhibitors, Guideline-directed medical therapy (GDMT), Hospitalization outcomes","lastPublishedDoi":"10.21203/rs.3.rs-7511564/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7511564/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003e Sacubitril/valsartan (S/V) and SGLT2 inhibitors (SGLT2i) are guideline-recommended (Class I) for HFrEF, yet direct comparative data are limited. We evaluated their relative effectiveness in routine care.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eRetrospective cohort of 626 HFrEF patients (LVEF\u0026thinsp;\u0026le;\u0026thinsp;40%) followed 2017\u0026ndash;2024, all with \u0026ge;\u0026thinsp;12 months of optimized β-blocker and RAAS inhibition. Three strategies: Group 1 (n\u0026thinsp;=\u0026thinsp;200) ACEI/ARB\u0026rarr;S/V; Group 2 (n\u0026thinsp;=\u0026thinsp;190) ACEI/ARB\u0026rarr;+SGLT2i (often because of S/V affordability); Group 3 (n\u0026thinsp;=\u0026thinsp;220) on S/V then +\u0026thinsp;SGLT2i. Outcomes were compared in the 12 months before (T0) and after (T1) treatment change.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eSwitching to S/V was associated with greater improvement than adding SGLT2i to ACEI/ARB. HF hospitalizations fell 61% (1.8\u0026rarr;0.7 per patient-year; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with S/V vs 25% (1.6\u0026rarr;1.2; p\u0026thinsp;=\u0026thinsp;0.048) with SGLT2i. NT-proBNP decreased 48% (1820\u0026rarr;940 pg/mL; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with S/V vs 15% (2395\u0026rarr;2020; p\u0026thinsp;=\u0026thinsp;0.047) with SGLT2i. LVEF rose by 7.1% (28.7\u0026rarr;35.8%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with S/V vs 2.3% (30.5\u0026rarr;32.8%; p\u0026thinsp;=\u0026thinsp;0.06) with SGLT2i. Outpatient visits and emergency department admissions showed parallel reductions. Adding SGLT2i on background S/V (Group 3) provided modest incremental benefits, particularly for visits and NYHA class.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIn well-treated HFrEF, initiating S/V after ACEI/ARB was linked to larger gains across hospitalizations, biomarkers, and function than adding SGLT2i to ACEI/ARB, while SGLT2i on top of S/V offered smaller complementary improvements. These real-world data support S/V as the backbone therapy, with SGLT2i providing additional\u0026mdash;though less pronounced\u0026mdash;benefits.\u003c/p\u003e","manuscriptTitle":"Comparative Real-World Effectiveness of Sacubitril/Valsartan and SGLT2 Inhibitors in Patients with HFrEF: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 05:04:31","doi":"10.21203/rs.3.rs-7511564/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"70f51d23-41e9-4424-9d7a-c19ed5ee005f","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-21T07:20:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-17 05:04:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7511564","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7511564","identity":"rs-7511564","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}