Effect of SGLT2 Inhibitors on Cardiac Structure and Function Assessed by Cardiac Magnetic Resonance: A Systematic Review and Meta-Analysis

Effect of SGLT2 Inhibitors on Cardiac Structure and Function Assessed by Cardiac Magnetic Resonance: A Systematic Review and Meta-Analysis | 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 Effect of SGLT2 Inhibitors on Cardiac Structure and Function Assessed by Cardiac Magnetic Resonance: A Systematic Review and Meta-Analysis Isabella Leo, Nadia Salerno, Stefano Figliozzi, Angelica Cersosimo, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6790667/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Aug, 2025 Read the published version in Cardiovascular Diabetology → Version 1 posted 13 You are reading this latest preprint version Abstract Background and aim: Sodium-glucose cotransporter-2 inhibitors (SGLT2i) improve outcomes in patients with heart failure (HF) but underlying mechanisms remain incompletely understood. Cardiac magnetic resonance (CMR) is key in evaluating cardiac structure and function, enabling accurate assessment of reverse remodeling. Aim of this systematic review and meta-analysis was to assess the effects of SGLT2i on cardiac remodeling evaluated by CMR changes. Methods: We conducted a systematic review and meta-analysis of studies assessing changes in CMR parameters in patients treated with SGLT2i (PROSPERO registration: CRD42024574302). Databases were searched through April 30, 2025. Random-effects models were used to pool mean changes in left and right ventricular volumes, mass, function, stroke volume, global longitudinal strain, left atrial volume, and tissue characterization indices. Meta-regression and sensitivity analyses were performed to evaluate potential sources of heterogeneity. Results Twenty-one studies and 1008 patients were included. Treatment with SGLT2i was associated with significant reductions in left ventricular (LV) end-diastolic volume (−7.10 mL; 95% CI: −13.01 to −1.19, p=0.023) and left ventricular mass (−4.24 g; 95% CI: −7.88 to −0.60, p=0.027). No significant change was noted in other CMR parameters. A subgroup analysis in patients with reduced LV ejection fraction showed improvement in LV stroke volume. Meta-regression revealed no significant effect of age, male sex or diabetes prevalence on pooled estimates. Conclusions SGLT2i are associated with favorable reverse remodeling effects as assessed by CMR, including reductions in LV volumes and mass. heart failure sodium-glucose transport protein 2 cardiovascular magnetic resonance reverse cardiac remodeling Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Initially proposed as glucose-lowering drugs, sodium-glucose cotransporter-2 inhibitors (SGLT2i) have shown robust beneficial effects on cardiovascular outcomes in patients with heart failure (HF) across different HF phenotypes and irrespective of glycemic control and diabetic status ( 1 , 2 ). For these reasons European guidelines recommend their use in both patients with HF with reduced ejection fraction and preserved ejection fraction to reduce the risk of cardiovascular death and HF hospitalization ( 1 , 2 ). Despite the compelling evidence supporting their use, the precise mechanisms behind SGLT2i cardioprotective effects remain incompletely understood ( 3 ). The occurrence and progression of HF is paralleled by changes in ventricular geometry, function and structure (i.e., cardiac remodeling) ( 4 ). In this setting, cardiac magnetic resonance (CMR) is essential in being the gold standard modality for volumes, mass and function assessment but provides also unique insights on tissue characterization of cardiac chambers ( 5 – 7 ). Aim of this systematic review and meta-analysis was to assess the effects of SGLT2i on cardiac remodeling evaluated by CMR changes. Methods This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines( 8 ) ( Supplementary Table 1 ). The protocol has been published in the PROSPERO International prospective register of systematic reviews (CRD42024574302). Search strategy Two independent investigators (A.C. and J.I.) performed a comprehensive literature search in PubMed, ClinicalTrials.gov, Embase, and the Cochrane Library using the following search terms: “SGLT2i” OR “Sodium-Glucose Transport Protein 2 Inhibitors” OR “SGLT2 Inhibitors” AND “Cardiac MRI” OR “Cardiac Magnetic Resonance” OR “Cardiovascular Magnetic Resonance” OR “CMR” in various combination. Full-text manuscripts published between January 1, 2000, through April 30, 2025 were screened for eligibility. Study eligibility Full-text manuscripts published in peer-reviewed journals assessing changes in CMR parameters in patients treated with SGLT2i were included. Non–English-language studies, editorials, letters, expert opinions, case reports or series, duplicated data and meta-analyses were excluded. No sample size restrictions were applied. Two authors (A.C. and J.I.) independently evaluated studies for eligibility, and discrepancies were resolved by a third reviewer (I.L.). Only studies that met all inclusion criteria were included in the final analysis (Table 1 ). Table 1 Patients’ baseline characteristics Study Study Design Total cohort Control group Age (y) Male n (%) Hypertension n (%) Diabetes n (%) NT-pro-BNP (pg/ml) HbA1c (%) HCT (%) eGFR at baseline (mL/min/1.73m2) SGLT2i Follow-up (days) Bouchi et al 2017 Single-centre, prospective, single arm pilot study 19 No 55 ± 12 14 (74) N/A 19 (100) N/A 7.5 ± 0.7 43.4 ± 3.1 69.7 ± 13.8 Luseogliflozin 84 Brown et al 2020 Single-centre, double-blind, placebo-controlled trial 66 Yes 67 ± 7 38 (56.6) 51 (77.3) 66 (100) 274.42 (116.1, 568.5)* 7.7 ± 3.1 41.7 ± 3.3 101.9 ± 27.1 Dapagliflozin 365 Carberry et al 2025 Multi-centre, prospective, randomized, double-blind, placebo-controlled, trial 105 Yes 63 ± 11 86 (82.7) 35 (33.7) 9 (8.7) 2163.6 N/A N/A 78.8 ± 20.2 Empagliflozin 168 Cohen et al 2019 Single-centre, prospective, matched cohort study 25 Yes 63.3 ± 7.6 16 (64) N/A 25 (100) 6.6 ± 7.1** 8.1 ± 0.8 N/A N/A Empagliflozin 180 Connelly et al 2023 Multi-centre, double- blind, placebo-controlled, randomized trial 169 Yes 59.3 ± 10.5 141 (83) 140 (82.8) 0 (0) 53 ± 57.9 5.7 ± 0.5 42.5 ± 4 80.5 ± 16 Empagliflozin 180 Dihoum et al 2024 Post-hoc analysis of a prospective, double-blind, randomized, placebo-controlled study 60 Yes 65.2 ± 6.9 36 (60) 47 (78.3) 60 (100) 247.4 (100, 560.6)* 7.8 ± 3.1 N/A N/A Dapagliflozin 365 Fukuda et al 2017 Single-centre, single-arm pilot study 9 No 66 ± 8 6 (67) N/A 9 (100) N/A 7.2 ± 0.6 N/A 79.5 ± 17.1 Ipragliflozin 84 Gaborit et al 2021 Single-centre, randomized, double-blind, placebo-controlled, phase 3 trial 51 Yes 56.9 ± 9.6 20 (39.2) 32 (62.7) 51 (100) N/A 8.1 ± 1.1 39 ± 4.5 N/A Empagliflozin 84 Hassan et al 2024 Single-centre, single-arm, prospective study 23 No 42.1 ± 3.8 19 (82.6) 6 (26.1) 5 (21.7) 2830 (775–3875)* N/A 41.2 ± 3.8 118.01 ± 39.3 Dapagliflozin 365 (270–600)* Hsu et al 2019 Single-centre, single-arm, prospective study 35 No 63.5 ± 9.7 17 (48.6) 29 (82.9) 35 (100) 64.3 ± 66.6 7 ± 1.1 41.8 ± 4.5 82.3 ± 19.4 Empagliflozin 180 Hundertmark et al (HFrEF) 2023 Single-centre, prospective, randomized, double-blind, placebo-controlled trial 36 Yes 66 ± 13.5 23 (63.9) 8 (22.2) 5 (13.9) 709.1 ± 3.1 N/A N/A 71.2 ± 24.6 Empagliflozin 84 Hundertmark et al (HFpEF) 2023 Single-centre, prospective, randomized, double-blind, placebo-controlled trial 36 Yes 68.3 ± 11.5 19 (52.8) 12 (33.3) 4 (11.1) 722.3 ± 2.5 N/A N/A 68.1 ± 18.9 Empagliflozin 84 Lee et al 2021 Multi-centre, prospective, randomized, double-blind, placebo-controlled trial 105 Yes 68.7 ± 11.1 77 (73.3) 74 (70.5) 82 (78.1) 466 (177–1120)* 72 ± 1.5 N/A 67.3 ± 22 Empagliflozin 252 Oldgren et al 2021 Multi-centre, double-blind, randomized, parallel-group, exploratory, phase IV trial 49 Yes 64.4 26 (53) 37.2 (76) 49 (100) 90.7 ± 96.7 6.7 ± 0.6 40.1 ± 2.7 N/A Dapagliflozin 42 Pourafkari et al 2024 Post-hoc analysis of a double-blind, randomized controlled trial 90 Yes 64.5 83 (92.2) 91 (90) 90 (100) 108,2 7.9 N/A N/A Empagliflozin 180 Santos-Gallego et al 2021 Single-centre, double-blind, randomized, placebo-controlled trial 84 Yes 62 ± 12.1 54 (64) 62 (74) 0 (0) N/A 5.8 ± 0.4 40.5 ± 4.8 81.5 ± 22 Empagliflozin 180 Sarak et al 2021 Post-hoc analysis of a single-centre, double-blind, randomized, placebo-controlled, phase IV trial 90 Yes 64 81 (90) 82 (91.1) 90 (100) N/A 7.9 42 N/A Empagliflozin 180 Satoh et al 2024 Single-center prospective cohort study 10 No 67.8 ± 10 4 ( 40 ) N/A N/A N/A N/A N/A 52.0 (44.2–55.7) Empagliflozin 180 Singh et al 2020 Single-centre, double-blind, placebo-controlled, randomized trial 56 Yes 67.1 37 (66.1) N/A 56 (100) N/A 7.7 N/A 72 Dapagliflozin 365 Thirunavukarasu et al 2021 Single centre, open-label, cross-over trial 28 Yes 67 ± 9 21 (75) 21 (75) 18 (64.3 ) 179.4 7 ± 1 43.7 ± 4.4 75.5 ± 30.4 Empagliflozin 84 Verma et al 2019 Single centre, double-blind, placebo-controlled, randomized trial 97 Yes 62.9 ± 9 90 (93) 88 (90.1) 97 (100) 106.4 N/A 42 87.5 Empagliflozin 180 Wang et al 2024 Single-centre, double-blind, placebo-controlled, randomized trial 62 Yes 62 ± 10 51 (83) 38 (61.3) 62 (100) N/A 7.9 ± 0.9 42 ± 3.1 N/A Dapagliflozin 365 Categorial variables are given as absolute numbers and percentage, n (%). Continuous variables are given as mean ± standard deviation or * median (IQR, interquartile range). **The value is expressed as pmol/l. Legend. eGFR : estimated glomerular filtration rate; NT-pro-BNP : N-terminal pro b-type natriuretic peptide; Hb1Ac : glycated hemoglobin; HCT : hematocrit; SGLT2i : Sodium-Glucose Transport Protein 2 Inhibitors. Data extraction The following variables were collected: i) first author, ii) year of publication, iii) study design, iv) sample size, v) main demographic, clinical and CMR baseline patient characteristics. In detail, CMR parameters included left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV), left ventricular end-diastolic volume indexed (LVEDVi), left ventricular end-systolic volume (LVESV), left ventricular end-systolic volume indexed (LVESVi), left ventricular mass (LVM) and indexed mass (LVMi), left atrial volume indexed (LAVi), left ventricular stroke volume (LVSV), right ventricular end-diastolic volume indexed (RVEDVi), right ventricular end-systolic volume indexed (RVESVi), pericardial fat, native T1 mapping and extracellular volume (ECV). At least three studies reporting CMR outcome variables were required to be eligible for the analysis. The individual quality of each study was assessed using the Newcastle-Ottawa Scale (NOS), with studies categorized as poor, fair, or good quality based on criteria related to selection, comparability, and outcome ( 9 ) ( Supplementary Table 2 ). Statistical Analysis The primary endpoint was the mean difference (baseline vs. follow-up evaluation) of CMR parameters. A random-effects model (DerSimonian and Laird method)( 10 ) was used to estimate pooled mean differences and corresponding 95% confidence intervals (CIs) of reported average measures of CMR parameters before and after treatment with SGLT2i, accounting for anticipated heterogeneity across studies. For each study, the effect size was defined as the mean difference (MD) in the outcome of interest. The standard error (SE) of the mean difference was calculated from the reported change in standard deviation (SD) and sample size. When SDs were not directly reported, they were imputed based on available information according to Cochrane Handbook recommendations ( 11 ), using available confidence intervals, p-values from parametric tests of change, or from correlation coefficients. When correlation coefficients were not provided in the study, they were either extracted or imputed based on data from similar studies. For studies that included a control group (patients not treated with SGLT2i), we extracted the MD in CMR parameters from baseline to follow-up separately for treated (a) and untreated (b) patients. The difference between these two changes (a minus b) was calculated to assess the treatment effect attributable to SGLT2i treatment. Measures of variability for these differences were derived accordingly. Studies without available control group data were included in the pre-versus-post treatment meta-analysis but excluded from between-group comparisons. Heterogeneity was assessed using the Cochran Q test and quantified with the I² statistic, with I² values above 50% indicating substantial heterogeneity( 12 ). Publication bias was evaluated using visual inspection of funnel plots and Egger’s regression test, with a p value < 0.10 considered indicative of significant asymmetry. Sensitivity analyses were performed by excluding one study at a time (leave-one-out analysis) to identify potential sources of heterogeneity and assess the robustness of the pooled effect estimates. A subgroup analysis was conducted stratifying studies by reduced LVEF (< 50%) at baseline. Effect of potential confounders on the pooled estimates for main CMR outcomes were assessed by meta-regression analysis. All statistical analyses were performed using JASP (University of Amsterdam, v. 0.19.3), and a two-tailed p-value < 0.05 was considered statistically significant. Results Literature Search The study flow-chart is reported in Fig. 1 . Initially, 1,640 articles were identified, with 114 duplicates removed. After screening the titles and abstracts of 464 articles, 45 were selected for full-text evaluation. Ultimately, 21 articles were deemed eligible for quantitative analysis of SGLT2i effects on CMR parameters ( 13 – 33 ).Three studies ( 14 , 16 , 22 ) were conducted to analyze different parameters (i.e. left ventricular, right ventricular and left atrial) on the same cohort of patients. Similarly, Dihoum et al.( 17 ) performed a sub-analysis of the DAPA-LVH study including a previously unpublished assessment of Left Ventricular Global Longitudinal Strain (GLS); these studies have been included in the analysis and the population overlap was taken into account when summarizing main results (Table 1 ). Study Characteristics A total of 1008 patients (74% males; mean age ± SD equal to 62 ± 11 years) undergoing baseline and follow-up CMR [median follow-up of 180 days [IQR: 96 days]) were included for quantitative analysis. Among them, 553 (55%) patients were treated with SGLT2i and 455 (45%) patients were not. Main CMR characteristics are summarized in Tables 2 and 3 . Table 2 Main CMR parameters in patients treated with SGLT2i at baseline. Study LVEDV (ml) LVEDVi (ml/m 2 ) LVESV (ml) LVESVi (ml/m 2 ) LVEF (%) LVM (g) LVMi (g/m 2 ) LAVi (ml/m 2 ) LVSV (ml) LVGLS (%) ECV (%) T1 (ms) Brown et al 2020 127.6 ± 22.5 N/A 37.2 ± 9.9 N/A 71.3 ± 5.4 126.5 ± 20.5 60.9 ± 7.8 N/A 90.5 ± 16.4 N/A N/A N/A Carberry et al 2025 N/A 97.8 ± 19.8 N/A 65.6 ± 17 33.4 ± 6 N/A 62.2 ± 13.7 34.3 ± 12.7 N/A N/A N/A N/A Cohen et al 2019 155.2 ± 8.7 N/A N/A N/A 63.4 ± 1.7 93.1 ± 4.9 N/A N/A N/A N/A N/A 989.8 ± 25.3 Connelly et al 2023 145.8 ± 39 74.2 ± 20.2 60.2 ± 28 30.7 ± 15 59.9 ± 10.7 124.4 ± 35.6 63.2 ± 17.9 N/A N/A N/A N/A N/A Dihoum et al 2024 124.1 ± 20.2 N/A 35.6 ± 9.4 N/A 71.7 ± 5.4 124.7 ± 21.5 73.9 ± 9.9 N/A N/A -17.8 ± 2.1 N/A N/A Gaborit et al 2021 N/A N/A N/A N/A 63.1 ± 8.2 117 (93,150) 58 (51,66) N/A N/A N/A N/A N/A Hassan et al 2024 N/A 178.3 ± 11 N/A 140 ± 44.3 23.8± 9.2 N/A N/A N/A 41.2 ± 3.9* N/A 33.7 ± 1.3 N/A Hsu et al 2019 94.4 ± 28.2 53.5 ± 16.2 24.5 ± 19.6 13.8 ± 11.9 77.2 ± 12.1 N/A 95.1 ± 28.3 N/A N/A N/A 27.4 ± 4.1 N/A Hundertmark et al (HFrEF) 2023 242 ± 78.5 N/A N/A N/A 36.8 ± 9.2 146.6 ± 8.3 75.4 ± 4.7 N/A 85.3 ± 6.3 -6.8 ± 1.4 30.3 ± 2.1 1190.1 ± 11.2 Hundertmark et al ( HFpEF) 2023 174.2 ± 18.6 N/A N/A N/A 52.6 ± 2.2 127.7 ± 14.5 62.2 ± 5.9 N/A 88.8 ± 7.4 -14.2 ± 1 29.7 ± 1 1177.9 ± 11.3 Lee et al 2021 224.8 ± 72.2 114.7 ± 37 157.5 ± 68.1 80.8 ± 37.2 31.7 ± 9.9 121.2 ± 36.5 61.2 ± 16.1 40.5 ± 13.3 N/A -7± 2.1 31.8± 4.5 N/A Oldgren et al 2021 N/A 83.1 ± 16.7 N/A 32.8 ± 8.2 60.7 ± 3.8 N/A 44.8 ± 8.6 33.1 ± 13.6 50.3 ± 9.7* N/A N/A N/A Pourafkari et al 2024 N/A 62.9 ± 15.4 N/A 26.7 ± 9.9 58.4 ± 7 N/A 59.2 ± 10.7 26.4 ± 8.4 N/A N/A N/A N/A Santos-Gallego et al 2021 219.8 ± 75.8 N/A 143.6 ± 66.3 N/A 36.2± 8.2 135.2± 45.2 N/A N/A N/A N/A N/A N/A Satoh et al 2024 N/A 70.1 ± 15.3 N/A 29.5 ± 7.5 N/A N/A N/A N/A N/A −13.8 ± 2.0 N/A N/A Singh et al 2020 172.4± 47.7 85.9 ± 24.1 99.2 ± 40.7 49.4 ± 21.3 44.5 ± 12.4 N/A 69.5 ± 16.3 49± 18.8 36.6 ± 10.4 N/A N/A N/A Thirunavukarasu et al 2021 163 ± 50 86 ± 27 83 ± 45 44 ± 25 52 ± 13 119 ± 33 61 ± 15 30 ± 16 81 ± 20 -10 ± 3 25 ± 3 1.285 ± 104 Verma et al 2019 124.1 ± 33 63.3 ± 15.5 53 ± 20.8 27.1 ± 10.5 58 ± 7.5 116.5 ± 26.3 59.3± 10.9 N/A N/A N/A N/A N/A Wang et al 2024 N/A N/A N/A N/A N/A N/A N/A N/A N/A -12.9± 3.4 27.7 ± 2.9 N/A Categorial variables are given as absolute numbers and percentage, n (%). Continuous variables are given as mean ± standard deviation or * median (IQR, interquartile range). Legend. LVEDV : left ventricular end-diastolic volume; LVEDVi : left ventricular end-diastolic volume indexed; LVESV : left ventricular end-systolic volume; LVESVi : left ventricular end-systolic volume indexed; LVEF : left ventricular ejection fraction; LVM : left ventricular mass; LVMi : left ventricular mass indexed; ECV : extracellular volume; LAVi : left atrial volume indexed; LVSV : left ventricular stroke volume; LVGLS : left ventricular longitudinal strain. Table 3 Other CMR parameters in patients treated with SGLT2i at baseline. Study RVEDVi (ml/m 2 ) RVESVi (ml/m 2 ) RVEF (%) Pericardial fat (cm 3 ) Bouchi et al 2017 N/A N/A N/A 117 (96–136) Fukuda et al 2017 N/A N/A N/A 102 (79–126) Hassan et al 2024 100 (78,111) 60 (31,79) 38.1 ± 4.1 N/A Hsu et al 2019 N/A N/A N/A 32.3 (5.7–82.8) Sarak et al 2021 62 ± 13.2 28.9 ± 6.5 53.2± 4.9 N/A Satoh et al 2024 79 ± 16.9 36.4 ± 16.1 N/A N/A Thirunavukarasu et al 2021 79 ± 19 38 ± 15 53 ± 9 N/A Categorial variables are given as absolute numbers and percentage, n (%). Continuous variables are given as mean ± standard deviation or * median (IQR, interquartile range). Legend. RVEDVi : right ventricular end-diastolic volume indexed; RVESVi : right ventricular end-systolic volume indexed; RVEF : right ventricular ejection fraction. The smallest study had a population of 9 patients ( 23 ) and the largest 169 ( 26 ). Thirteen studies( 13 – 16 , 18 , 21 , 22 , 25 – 27 , 29 , 31 , 33 ) included patients treated with empaglifozin, six studies with dapaglifozin ( 17 , 19 , 20 , 28 , 30 , 32 ), one with ipraglifozin ( 23 ) and one with luseoglifozin ( 24 ). Six studies ( 13 , 15 , 18 , 20 , 21 , 28 ) included patients with reduced LVEF at baseline. Six studies ( 23 , 24 , 28 , 29 , 31 , 33 ) did not report data for a control group and were therefore analyzed as single-arm cohorts. Meta-Analyses Effects on left heart volumes, mass, and function. Treatment with SGLT2i was associated with a significant reduction in LVEDV (− 7.10 mL [95% CI: −13.01, − 1.19]; 10 studies, I² = 69%, p = 0.023), whereas no significant changes were observed in LVESV (− 5.97 mL [95% CI: −13.80, 1.87]; 8 studies, I² = 80%, p = 0.115), LVEDVi (− 0.53 mL/m² [95% CI: −3.24, 2.18]; 10 studies, I² = 46%, p = 0.668), LVESVi (− 1.09 mL/m² [95% CI: −2.94, 0.75], 9 studies, I² = 40%, p = 0.213), LVEF (1.14% [95% CI: −0.39, 2.68]; 14 studies, I² = 80%, p = 0.133) (Figs. 2 and 3 ), and GLS (-0.16% [95% CI: −2.67, 2.35]; 5 studies, I² = 83%, p = 0.878). A non-significant trend towards increase in LVSV was observed (1.41 ml [95% CI: −0.12, 2.94]; 4 studies, I 2 = 0, p = 0.063, Supplementary Fig. 1 ). A significant decrease in LVM was observed (− 4.24 g [95% CI: −7.88, − 0.60]; 9 studies, I² = 53%, p = 0.027), while LVMi showed no significant change (− 0.86 g/m² [95% CI: −2.02, 0.31]; 11 studies, I² = 41%, p = 0.135). There was no significant change in LAVi values (− 0.60 mL/m² [95% CI: −2.70, 1.49]; 6 studies, I² = 54%, p = 0.494) ( Fig. 3 ). Effects on right heart volumes and function Both RVEDVi and RVESVi remained unchanged (− 0.03 mL/m² [95% CI: −2.54, 2.49]; 4 studies, I² = 0%, p = 0.975; −0.31 mL/m² [95% CI: −1.61, 0.99]; 4 studies, I² = 0%, p = 0.502, respectively). No effect was also noted on RVEF (1.29% [95% CI: −1.33,3.92]; 3 studies, I 2 = 40%, p = 0.502) (Supplementary Fig. 2) . Effects on tissue characterization There were no differences in ECV (0.13% [95% CI: −1.08, 1.33]; 6 studies, I² = 83%, p = 0.807), or T1 mapping (7.38 ms [95% CI: −30.60, 45.37]; 3 studies, I² = 76%, p = 0.580) ( Supplementary Fig. 1 ). Effect on pericardial fat A trend toward reduction in pericardial fat was observed, although not reaching statistical significance (− 5.14 mL [95% CI: −11.87, 1.60]; 3 studies, I² = 0%, p = 0.082) ( Supplementary Fig. 2 ). Effects in patients with heart failure In patients with LVEF at baseline < 50%, LVSV increased significantly (1.83 [95% CI: 0.86, 2.80]; 2 studies, I² = 0%, p = 0.027). A non-significant trend towards increase in LVEF was also noted (2.61 [95% CI: -0.50, 5.70]; 5 studies, I² =80%, p = 0.08). No significant differences were observed for the other parameters. Effects in patients with diabetes In patients with diabetes, there was a significant reduction in LVM was observed (–4.61 [95% CI: − 8.59, − 0.63]; 3 studies, I² = 0%, p = 0.024). Native T1 mapping also decreased significantly (–20.34 ms [95% CI: − 35.47, − 5.22]; 2 studies, I² = 0%, p = 0.008). No significant differences were found for LVEDV, LVESV, LVMi, LVEF, or ECV. Sensitivity analysis A sensitivity analysis including only studies with a control group (n = 15) was conducted, confirming both the decrease in LVEDV (− 7.73 mL [95% CI: −14.68, − 0.78]; I² = 70.4%, p = 0.033) and LVM (− 3.96 g [95% CI: −7.84, − 0.08]; I² = 55.4%, p = 0.047). Leave one-out analyses were performed to assess the robustness of the meta-analytic estimates across all imaging-derived parameters; for LVEDV, pooled effect estimates ranged from − 5.38 to − 8.23 mL, with all but one iteration (Cohen et al( 25 ), p = 0.064) maintaining statistical significance; heterogeneity varied between 59.5% and 75.5%, indicating moderate-to-high between-study variability. No single study exerted a disproportionate influence on the overall estimate. In contrast, LVESV analysis revealed greater sensitivity to individual studies, with a significant drop in heterogeneity when removing Santos-Gallego et al( 13 ) (I² = 46.5%). For indexed LV volumes (LVEDVi and LVESVi), all iterations produced non-significant results. While effect sizes remained consistently small, heterogeneity decreased substantially when Lee et al( 21 ) (LVEDVi I² = 10.0%) or Hsu et al( 29 ) (LVESVi I² = 17.7%) were excluded. The analysis of LVM demonstrated consistent effect estimates across all exclusions (range: − 2.73 to − 5.02 g), with all the iterations but Hundermarkt et al ( 15 ) (p = 0.065) retaining statistical significance. Heterogeneity varied modestly, with Santos-Gallego et al ( 13 ) being a key contributor (I² = 0% upon exclusion). For LVEF, removal of Cohen et al ( 25 ) yielded a statistically significant result (p = 0.029), with heterogeneity remanining steadily high across all iterations. For LVSV, statistical significance was observed upon exclusion of Brown et al ( 19 ) (p = 0.014, MD 1.88) and heterogeneity remained null across all exclusions. Both LVMi and LAVi analyses revealed non-significant effects with moderate, stable, heterogeneity for LVMi (I² range: 30.3–46.3%) and notable reduction in heterogeneity after the exclusion of Oldgren et al( 30 ) (I² = 7.9%) or Carberry et al ( 18 ) (I² = 12.9%) for LAVi (Supplementary Table 3). Meta-regression analyses At meta-regression analyses, none of the predictors included in the model (i.e., age, male sex and diabetes) revealed a significant effect modification on LVEDV, LVESV, LVEDVi, LVESVi, LVEF, LAVi, LVM, LVMi (all p-values > 0.05). Meta-regression analyses were not performed on other CMR parameters due to the limited number of studies available. Publication bias and grading of evidence Funnel plots were visually inspected for asymmetry and assessed using Egger’s regression test across all cardiac structural, functional, and tissue parameters. No substantial visual asymmetry was observed for most outcomes, except for ECV and LAVi. Egger’s test results statistically confirmed possible publication bias for both parameters (p = 0.01 and 0.031, respectively) ( Fig. 4 and Supplementary Fig. 3). According to the GRADE Working Group system( 34 ), the level of certainty for the association between SGLT2i treatment and CMR outcomes was moderate for most outcomes but in 7, in which were adjudicated to be low ( Supplementary Table 4 ). Discussion The present updated systematic review and meta-analysis demonstrated an association between SGLT2i treatment and decrease of LVEDV and LVM, providing evidence for favorable effects on cardiac remodeling. These results were confirmed in a sensitivity analysis including only studies with control group and were not affected by baseline patient characteristics including age, sex and diabetes. Patients with reduced LVEF also showed a significant, although modest, increase in LVSV after SGLT2i treatment. Our data on favorable LV remodeling are in line with a previous meta-analysis including 9 randomized controlled trials (3 of which were CMR-based) demonstrating a significant reduction in LV volumes and indexed LV mass with significant increase in LVEF in the whole population ( 35 ). However, the use of different imaging modalities to assess cardiac remodeling in that study may have introduced variability and potentially obscured subtle treatment effects. CMR is in fact considered the gold standard for quantifying ventricular volumes, mass, and tissue characterization, offering superior spatial resolution and interobserver consistency( 36 ). In contrast, echocardiography is more widely available and used in clinical practice but is subject to greater operator dependence and geometric assumptions, that may be unneglectable particularly in patients with abnormal ventricular shapes( 37 ). A recent meta-analysis ( 38 ) focusing only on CMR studies (n = 5, 408 patients) was able to confirm only LVM regression after SGLT2i administration, likely due to the limited number of studies available at the time of publication. Cardiac remodeling reflects complex molecular and structural changes, involving inflammation, fibrosis, and metabolic dysregulation( 3 ). Maladaptive remodeling is associated with worse clinical outcomes, and represents one of the main targets of HF therapy( 39 ). In this regard, SGLT2i have proven in several trials to reduce key cardiovascular endpoints as hospitalizations and HF-related mortality, irrespective of the glycemic status( 40 – 44 ). The exact mechanisms subtended to these beneficial effects are not yet fully understood, with different hypothesis generated so far( 3 ). By blocking glucose reabsorption in the proximal renal tubule, these agents promote glycosuria, reduce insulin levels, and increase glucagon secretion—facilitating lipolysis and fat oxidation, with consequent reduction in visceral adiposity( 45 ). Moreover, their natriuretic effect determines unloading and suppresses the renin-angiotensin-aldosterone system, with favorable effect on blood pressure( 46 ). However, these metabolic and hemodynamic changes alone do not fully account for the observed CV benefits. Improvements in endothelial function and arterial stiffness, reduced oxidative stress( 47 ), inflammation( 48 ), vascular resistance ( 42 ), and a shift toward more efficient metabolic pathways( 3 ) have been demonstrated in clinical and pre-clinical models and may all contribute to the positive observed effect( 49 , 50 ). In this regard, we found no impact of SGLT2i treatment on tissue characterization indices such as T1 mapping and ECV in the whole population; this result should be interpret carefully given the limited number of studies included in the analysis for these parameters, with possible publication bias for ECV( 15 , 21 , 28 , 29 , 31 , 32 ). A significant decrease in T1 mapping values was noted in patients with diabetes, although only 2 studies were available for this analysis. Therefore, the reduction in LVM observed following SGLT2 inhibitor treatment appears to result primarily from left ventricular unloading rather than from a decrease in extracellular volume. However, pre-clinical studies in animal models demonstrated reduced intramyocardial fibrosis after empaglifozin with lower collagen deposition and decreased extracellular volume ( 3 , 49 ). Moreover, in some studies a significant reduction in LVM was observed even in the absence of LV unloading ( 22 ). Remarkably, the demonstrated effect on LV volumes may have a significant impact on clinical outcomes; in a pooled analysis, a 10 mL decrease in end-diastolic volume was associated with a 5% relative reduction in the odds of mortality( 36 ). Our study also found no evidence of significant changes in RV volumes and function. This is in line with the results of the post-hoc analysis of the EMPA-HEART CardioLink-6 that failed to demonstrate any impact of empaglifozin treatment on RV parameters (including RV mass) on 90 patients with diabetes and coronary artery disease( 14 ). Limitations This study has several limitations. First, the number of included studies for some parameters—particularly right ventricular volumes, strain, and tissue characterization markers—was limited, reducing the statistical power of the analysis. Heterogeneity was also moderate to high for several outcomes, potentially reflecting differences in patient populations, imaging protocols, follow-up durations, and background therapies. However, the sensitivity analysis performed failed to identify studies that would significantly affect our results. The meta-regression of pre-specified and other variables did not identify any significant moderator; however, confounding cannot be ruled out. Finally, some of the included studies had relatively small sample sizes and were not blinded or randomized, increasing the risk of bias. Prospective studies with standardized CMR endpoints and longer follow-up will certainly provide more information, particularly regarding effects on tissue-level changes. Conclusions This meta-analysis demonstrated an association between SGLT2i treatment and decrease of LVEDV and LVM, reinforcing the mechanistic plausibility of reverse LV cardiac remodeling as a contributor to the cardiovascular benefits of SGLT2i therapy. Declarations Conflicts of interest: All authors have reported that they have no relationships relevant to the contents of this paper to disclose. Funding This work was supported by grants from the Italian Ministry of University and Research (PNRR—National Center for Gene Therapy and Drugs based on RNA Technology No. CN00000041) and from the Italian Ministry of Health (POS4 ‘Cal-Hub-Ria’ No. T4-AN-09; PNRRMAD-2022-12376814). Author Contribution I.L.: conceptualization, statistical analysis, drafting of the main manuscript. N.S.: conceptualization, drafting main manuscript. A.C. and J.I.: systematic review, data extraction, figure preparation. 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Early hemodynamic impact of SGLT2 inhibitors in overweight cardiometabolic heart failure: beyond fluid offloading to vascular adaptation– a preliminary report. Cardiovasc Diabetol. 2025;24(1):141. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable3LOOanalysis2105.docx SupplementaryTable2NOSscale.docx SupplementaryTable1PRISMA2020checklist.docx SupplementaryTable4GradingofEvidence.docx SupplementaryFigure1.tif SupplementaryFigure3.tif SupplementaryFigure4.tif SupplementaryFigure2.tif Cite Share Download PDF Status: Published Journal Publication published 21 Aug, 2025 Read the published version in Cardiovascular Diabetology → Version 1 posted Editorial decision: Revision requested 30 Jun, 2025 Reviews received at journal 29 Jun, 2025 Reviews received at journal 26 Jun, 2025 Reviewers agreed at journal 21 Jun, 2025 Reviewers agreed at journal 20 Jun, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviews received at journal 14 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviewers invited by journal 03 Jun, 2025 Editor assigned by journal 31 May, 2025 Submission checks completed at journal 31 May, 2025 First submitted to journal 31 May, 2025 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. 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2","display":"","copyAsset":false,"role":"figure","size":6930181,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of SGLT2i on cardiac imaging parameters measured by CMR. Forest plots: meta-analyses on LVEDV (A), LVESV (B), LVEDVi (C) and LVESVi (D). Effect sizes: differences in means between baseline and follow-up measurements. LVEDV: left ventricular end-diastolic volume; LVESV: left ventricular end-systolic volume; LVEDVi: left ventricular end-diastolic volume indexed; LVESVi: left ventricular end-systolic volume indexed.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/29b4e9ea840ec0e8b4d59d54.png"},{"id":84219809,"identity":"0e402e5f-3739-457e-86b7-95aff84c4cb5","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2692787,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of SGLT2i on cardiac imaging parameters measured by CMR. Forest plots: meta-analyses on LAVi (A), LVEF (B), LVM (C) and LVMi (D). Effect sizes: differences in means between baseline and follow-up measurements. LAVi: left atrial volume indexed; LVEF: left ventricular ejection fraction; LVM: left ventricular mass; LVMi: left ventricular mass indexed.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/1b90132d29185d7113bf878c.png"},{"id":84219803,"identity":"d0b02483-b1be-427b-9848-27a5bfd0eca2","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1296860,"visible":true,"origin":"","legend":"\u003cp\u003eEvaluation for publication bias. Funnel plots with 95% confidence intervals for LVEDV, LVESV, LVEF on the top, LVEDVi, LVESVi, LAVi on the bottom. LVEDV: left ventricular end-diastolic volume; LVESV: left ventricular end-systolic volume; LVEDVi: left ventricular end-diastolic volume indexed; LVESVi: left ventricular end-systolic volume indexed; LVEF: left ventricular ejection fraction; LAVi: left atrial volume indexed.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/2dbed04580bdf5cb8a1569fc.png"},{"id":89847286,"identity":"c1097e05-bc8c-4e50-97be-0d36b3ab0d97","added_by":"auto","created_at":"2025-08-25 16:42:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":19358006,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/c3b84d5c-188e-46fc-81a0-d37206e98aca.pdf"},{"id":84219798,"identity":"cdef1325-09dd-4944-a2b3-76a7e469fe7e","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":38272,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3LOOanalysis2105.docx","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/3ba56683fa02cee3369a9642.docx"},{"id":84220449,"identity":"20b037d7-ef86-4e51-bfc6-0fd03e670621","added_by":"auto","created_at":"2025-06-09 11:32:14","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":21532,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2NOSscale.docx","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/e10a4a65cb80c7bcd9bf8a26.docx"},{"id":84219818,"identity":"03ff7c8a-c030-46f4-9536-f2cc1ec62e3f","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":31247,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1PRISMA2020checklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/0d34e80a24c385b8ba5ee0af.docx"},{"id":84220453,"identity":"b17a2ee6-3cc6-4ec0-8faf-2bb60ab33ed4","added_by":"auto","created_at":"2025-06-09 11:32:14","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":39625,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable4GradingofEvidence.docx","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/42dc70ec137416bba621d043.docx"},{"id":84219806,"identity":"4190cb67-c090-4b7c-ba1d-343c194c119b","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":1475373,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/344647b5347d22185eaa9756.tif"},{"id":84219822,"identity":"98e2efcb-d6f4-41a2-9e07-f76db5f789a2","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":963909,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/b232d05846962fda9b55c272.tif"},{"id":84219812,"identity":"8c14b143-efea-432d-8f76-e6368b6776fc","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"tif","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":780345,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/1f5e4a58ceb711ed13357493.tif"},{"id":84219825,"identity":"a60482ae-13d2-4b96-8cea-836ac2571432","added_by":"auto","created_at":"2025-06-09 11:24:14","extension":"tif","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":1305751,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-6790667/v1/7fa956be96bd08f83531977c.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of SGLT2 Inhibitors on Cardiac Structure and Function Assessed by Cardiac Magnetic Resonance: A Systematic Review and Meta-Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInitially proposed as glucose-lowering drugs, sodium-glucose cotransporter-2 inhibitors (SGLT2i) have shown robust beneficial effects on cardiovascular outcomes in patients with heart failure (HF) across different HF phenotypes and irrespective of glycemic control and diabetic status (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). For these reasons European guidelines recommend their use in both patients with HF with reduced ejection fraction and preserved ejection fraction to reduce the risk of cardiovascular death and HF hospitalization (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Despite the compelling evidence supporting their use, the precise mechanisms behind SGLT2i cardioprotective effects remain incompletely understood (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The occurrence and progression of HF is paralleled by changes in ventricular geometry, function and structure (i.e., cardiac remodeling) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In this setting, cardiac magnetic resonance (CMR) is essential in being the gold standard modality for volumes, mass and function assessment but provides also unique insights on tissue characterization of cardiac chambers (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Aim of this systematic review and meta-analysis was to assess the effects of SGLT2i on cardiac remodeling evaluated by CMR changes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis meta-analysis was performed according to the Preferred Reporting Items for Systematic\u003c/p\u003e \u003cp\u003eReviews and Meta-Analyses (PRISMA) guidelines(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). The protocol has been published in the PROSPERO International prospective register of systematic reviews (CRD42024574302).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSearch strategy\u003c/h2\u003e \u003cp\u003eTwo independent investigators (A.C. and J.I.) performed a comprehensive literature search in PubMed, ClinicalTrials.gov, Embase, and the Cochrane Library using the following search terms: \u0026ldquo;SGLT2i\u0026rdquo; OR \u0026ldquo;Sodium-Glucose Transport Protein 2 Inhibitors\u0026rdquo; OR \u0026ldquo;SGLT2 Inhibitors\u0026rdquo; AND \u0026ldquo;Cardiac MRI\u0026rdquo; OR \u0026ldquo;Cardiac Magnetic Resonance\u0026rdquo; OR \u0026ldquo;Cardiovascular Magnetic Resonance\u0026rdquo; OR \u0026ldquo;CMR\u0026rdquo; in various combination. Full-text manuscripts published between January 1, 2000, through April 30, 2025 were screened for eligibility.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy eligibility\u003c/h3\u003e\n\u003cp\u003eFull-text manuscripts published in peer-reviewed journals assessing changes in CMR parameters in patients treated with SGLT2i were included. Non\u0026ndash;English-language studies, editorials, letters, expert opinions, case reports or series, duplicated data and meta-analyses were excluded. No sample size restrictions were applied. Two authors (A.C. and J.I.) independently evaluated studies for eligibility, and discrepancies were resolved by a third reviewer (I.L.). Only studies that met all inclusion criteria were included in the final analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatients\u0026rsquo; baseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal cohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e(y)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNT-pro-BNP (pg/ml)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHbA1c\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHCT\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eeGFR at baseline\u003c/p\u003e \u003cp\u003e(mL/min/1.73m2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSGLT2i\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eFollow-up\u003c/p\u003e \u003cp\u003e(days)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBouchi et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2017\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, prospective, single arm pilot study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e69.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eLuseogliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrown et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2020\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38 (56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51 (77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e274.42 (116.1, 568.5)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e41.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e101.9\u0026thinsp;\u0026plusmn;\u0026thinsp;27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDapagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarberry et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2025\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-centre, prospective, randomized, double-blind, placebo-controlled, trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86 (82.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2163.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e78.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, prospective, matched cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnelly et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-centre, double- blind, placebo-controlled, randomized trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e141 (83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e140 (82.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;57.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e80.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDihoum et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-hoc analysis of a prospective, double-blind, randomized, placebo-controlled study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e(78.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e247.4\u003c/p\u003e \u003cp\u003e(100, 560.6)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDapagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFukuda et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2017\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, single-arm pilot study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e79.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eIpragliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGaborit et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, randomized, double-blind,\u003c/p\u003e \u003cp\u003eplacebo-controlled, phase 3 trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 (39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32 (62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHassan et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, single-arm, prospective study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2830 (775\u0026ndash;3875)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e41.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e118.01\u0026thinsp;\u0026plusmn;\u0026thinsp;39.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDapagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e365 (270\u0026ndash;600)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHsu et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, single-arm, prospective study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29 (82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64.3\u0026thinsp;\u0026plusmn;\u0026thinsp;66.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e41.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e82.3\u0026thinsp;\u0026plusmn;\u0026thinsp;19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHundertmark et al \u003cem\u003e(HFrEF)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, prospective, randomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e709.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e71.2\u0026thinsp;\u0026plusmn;\u0026thinsp;24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHundertmark et al \u003cem\u003e(HFpEF)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, prospective, randomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e722.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e68.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLee et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-centre, prospective, randomized, double-blind,\u003c/p\u003e \u003cp\u003eplacebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74 (70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82 (78.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e466 (177\u0026ndash;1120)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e67.3\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOldgren et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-centre, double-blind, randomized, parallel-group, exploratory, phase IV trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.2 (76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e49 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e90.7\u0026thinsp;\u0026plusmn;\u0026thinsp;96.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDapagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePourafkari et al \u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-hoc analysis of a double-blind, randomized controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83 (92.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91 (90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e108,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSantos-Gallego et al \u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, double-blind, randomized, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54 (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e81.5\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSarak et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-hoc analysis of a single-centre, double-blind, randomized, placebo-controlled, phase IV trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81 (90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82 (91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatoh et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-center prospective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e52.0 (44.2\u0026ndash;55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingh et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2020\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre, double-blind, placebo-controlled, randomized trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDapagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThirunavukarasu et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle centre, open-label, cross-over trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18 (64.3\u003c/p\u003e \u003cp\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e179.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e75.5\u0026thinsp;\u0026plusmn;\u0026thinsp;30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerma et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle centre, double-blind, placebo-controlled, randomized trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90 (93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88 (90.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e106.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEmpagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWang et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-centre,\u003c/p\u003e \u003cp\u003edouble-blind,\u003c/p\u003e \u003cp\u003eplacebo-controlled, randomized trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e(83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDapagliflozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003eCategorial variables are given as absolute numbers and percentage, n (%). Continuous variables are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or * median (IQR, interquartile range). **The value is expressed as pmol/l.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003e\u003cb\u003eLegend.\u003c/b\u003e \u003cem\u003eeGFR\u003c/em\u003e: estimated glomerular filtration rate; \u003cem\u003eNT-pro-BNP\u003c/em\u003e: N-terminal pro b-type natriuretic peptide; \u003cem\u003eHb1Ac\u003c/em\u003e: glycated hemoglobin; \u003cem\u003eHCT\u003c/em\u003e: hematocrit; \u003cem\u003eSGLT2i\u003c/em\u003e: Sodium-Glucose Transport Protein 2 Inhibitors.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData extraction\u003c/h3\u003e\n\u003cp\u003eThe following variables were collected: i) first author, ii) year of publication, iii) study design, iv) sample size, v) main demographic, clinical and CMR baseline patient characteristics. In detail,\u003c/p\u003e \u003cp\u003eCMR parameters included left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV), left ventricular end-diastolic volume indexed (LVEDVi), left ventricular end-systolic volume (LVESV), left ventricular end-systolic volume indexed (LVESVi), left ventricular mass (LVM) and indexed mass (LVMi), left atrial volume indexed (LAVi), left ventricular stroke volume (LVSV), right ventricular end-diastolic volume indexed (RVEDVi), right ventricular end-systolic volume indexed (RVESVi), pericardial fat, native T1 mapping and extracellular volume (ECV). At least three studies reporting CMR outcome variables were required to be eligible for the analysis. The individual quality of each study was assessed using the Newcastle-Ottawa Scale (NOS), with studies categorized as poor, fair, or good quality based on criteria related to selection, comparability, and outcome (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe primary endpoint was the mean difference (baseline vs. follow-up evaluation) of CMR parameters. A random-effects model (DerSimonian and Laird method)(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) was used to estimate pooled mean differences and corresponding 95% confidence intervals (CIs) of reported average measures of CMR parameters before and after treatment with SGLT2i, accounting for anticipated heterogeneity across studies.\u003c/p\u003e \u003cp\u003eFor each study, the effect size was defined as the mean difference (MD) in the outcome of interest. The standard error (SE) of the mean difference was calculated from the reported change in standard deviation (SD) and sample size. When SDs were not directly reported, they were imputed based on available information according to Cochrane Handbook recommendations (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), using available confidence intervals, p-values from parametric tests of change, or from correlation coefficients. When correlation coefficients were not provided in the study, they were either extracted or imputed based on data from similar studies.\u003c/p\u003e \u003cp\u003eFor studies that included a control group (patients not treated with SGLT2i), we extracted the MD in CMR parameters from baseline to follow-up separately for treated (a) and untreated (b) patients. The difference between these two changes (a minus b) was calculated to assess the treatment effect attributable to SGLT2i treatment. Measures of variability for these differences were derived accordingly.\u003c/p\u003e \u003cp\u003eStudies without available control group data were included in the pre-versus-post treatment meta-analysis but excluded from between-group comparisons.\u003c/p\u003e \u003cp\u003eHeterogeneity was assessed using the Cochran Q test and quantified with the I\u0026sup2; statistic, with I\u0026sup2; values above 50% indicating substantial heterogeneity(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Publication bias was evaluated using visual inspection of funnel plots and Egger\u0026rsquo;s regression test, with a p value\u0026thinsp;\u0026lt;\u0026thinsp;0.10 considered indicative of significant asymmetry.\u003c/p\u003e \u003cp\u003eSensitivity analyses were performed by excluding one study at a time (leave-one-out analysis) to identify potential sources of heterogeneity and assess the robustness of the pooled effect estimates. A subgroup analysis was conducted stratifying studies by reduced LVEF (\u0026lt;\u0026thinsp;50%) at baseline. Effect of potential confounders on the pooled estimates for main CMR outcomes were assessed by meta-regression analysis. All statistical analyses were performed using JASP (University of Amsterdam, v. 0.19.3), and a two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLiterature Search\u003c/h2\u003e \u003cp\u003eThe study flow-chart is reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Initially, 1,640 articles were identified, with 114 duplicates removed. After screening the titles and abstracts of 464 articles, 45 were selected for full-text evaluation. Ultimately, 21 articles were deemed eligible for quantitative analysis of SGLT2i effects on CMR parameters (\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).Three studies (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) were conducted to analyze different parameters (i.e. left ventricular, right ventricular and left atrial) on the same cohort of patients. Similarly, Dihoum et al.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) performed a sub-analysis of the DAPA-LVH study including a previously unpublished assessment of Left Ventricular Global Longitudinal Strain (GLS); these studies have been included in the analysis and the population overlap was taken into account when summarizing main results (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Characteristics\u003c/h3\u003e\n\u003cp\u003eA total of 1008 patients (74% males; mean age\u0026thinsp;\u0026plusmn;\u0026thinsp;SD equal to 62\u0026thinsp;\u0026plusmn;\u0026thinsp;11 years) undergoing baseline and follow-up CMR [median follow-up of 180 days [IQR: 96 days]) were included for quantitative analysis. Among them, 553 (55%) patients were treated with SGLT2i and 455 (45%) patients were not. Main CMR characteristics are summarized in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain CMR parameters in patients treated with SGLT2i at baseline.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLVEDV \u003cem\u003e(ml)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLVEDVi \u003cem\u003e(ml/m\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLVESV \u003cem\u003e(ml)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLVESVi \u003cem\u003e(ml/m\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLVEF\u003c/p\u003e \u003cp\u003e\u003cem\u003e(%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLVM\u003c/p\u003e \u003cp\u003e\u003cem\u003e(g)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLVMi \u003cem\u003e(g/m\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLAVi \u003cem\u003e(ml/m\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLVSV\u003c/p\u003e \u003cp\u003e\u003cem\u003e(ml)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eLVGLS \u003cem\u003e(%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eECV \u003cem\u003e(%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003cp\u003e\u003cem\u003e(ms)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrown et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2020\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127.6\u0026thinsp;\u0026plusmn;\u0026thinsp;22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e126.5\u0026thinsp;\u0026plusmn;\u0026thinsp;20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e90.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarberry et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2025\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.6\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e989.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnelly et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145.8\u0026thinsp;\u0026plusmn;\u0026thinsp;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.2\u0026thinsp;\u0026plusmn;\u0026thinsp;20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.2\u0026thinsp;\u0026plusmn;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e124.4\u0026thinsp;\u0026plusmn;\u0026thinsp;35.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e63.2\u0026thinsp;\u0026plusmn;\u0026thinsp;17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDihoum et al \u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.1\u0026thinsp;\u0026plusmn;\u0026thinsp;20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e124.7\u0026thinsp;\u0026plusmn;\u0026thinsp;21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-17.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGaborit et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e117\u003c/p\u003e \u003cp\u003e(93,150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58 (51,66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHassan et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140\u0026thinsp;\u0026plusmn;\u0026thinsp;44.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.8\u0026plusmn; 9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e41.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e33.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHsu et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.4\u0026thinsp;\u0026plusmn;\u0026thinsp;28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.5\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95.1\u0026thinsp;\u0026plusmn;\u0026thinsp;28.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHundertmark et al \u003cem\u003e(HFrEF)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242\u0026thinsp;\u0026plusmn;\u0026thinsp;78.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e146.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e85.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1190.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHundertmark et al (\u003cem\u003eHFpEF)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174.2\u0026thinsp;\u0026plusmn;\u0026thinsp;18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e127.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e88.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e29.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1177.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLee et al\u003c/p\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224.8\u0026thinsp;\u0026plusmn;\u0026thinsp;72.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114.7\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157.5\u0026thinsp;\u0026plusmn;\u0026thinsp;68.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.8\u0026thinsp;\u0026plusmn;\u0026thinsp;37.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121.2\u0026thinsp;\u0026plusmn;\u0026thinsp;36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-7\u0026plusmn;\u003c/p\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e31.8\u0026plusmn;\u003c/p\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOldgren et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePourafkari et al \u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSantos-Gallego et al \u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e219.8\u0026thinsp;\u0026plusmn;\u0026thinsp;75.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143.6\u0026thinsp;\u0026plusmn;\u0026thinsp;66.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.2\u0026plusmn;\u003c/p\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e135.2\u0026plusmn;\u003c/p\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatoh et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026minus;13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingh et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2020\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e172.4\u0026plusmn;\u003c/p\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.9\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003c/p\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.2\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003c/p\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.4\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003c/p\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.5\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003c/p\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69.5\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003c/p\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49\u0026plusmn;\u003c/p\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThirunavukarasu et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163\u0026thinsp;\u0026plusmn;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 \u0026plusmn;\u003c/p\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 \u0026plusmn;\u003c/p\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 \u0026plusmn;\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52 \u0026plusmn;\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e119\u0026thinsp;\u0026plusmn;\u0026thinsp;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61 \u0026plusmn;\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e81\u003c/p\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-10\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e25 \u0026plusmn;\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.285\u0026thinsp;\u0026plusmn;\u0026thinsp;104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerma et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.1\u0026thinsp;\u0026plusmn;\u0026thinsp;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e116.5\u0026thinsp;\u0026plusmn;\u0026thinsp;26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59.3\u0026plusmn;\u003c/p\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWang et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-12.9\u0026plusmn;\u003c/p\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003eCategorial variables are given as absolute numbers and percentage, n (%). Continuous variables are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or * median (IQR, interquartile range).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003cb\u003eLegend.\u003c/b\u003e \u003cem\u003eLVEDV\u003c/em\u003e: left ventricular end-diastolic volume; \u003cem\u003eLVEDVi\u003c/em\u003e: left ventricular end-diastolic volume indexed; \u003cem\u003eLVESV\u003c/em\u003e: left ventricular end-systolic volume; \u003cem\u003eLVESVi\u003c/em\u003e: left ventricular end-systolic volume indexed; \u003cem\u003eLVEF\u003c/em\u003e: left ventricular ejection fraction; \u003cem\u003eLVM\u003c/em\u003e: left ventricular mass; \u003cem\u003eLVMi\u003c/em\u003e: left ventricular mass indexed; \u003cem\u003eECV\u003c/em\u003e: extracellular volume; \u003cem\u003eLAVi\u003c/em\u003e: left atrial volume indexed; \u003cem\u003eLVSV\u003c/em\u003e: left ventricular stroke volume; \u003cem\u003eLVGLS\u003c/em\u003e: left ventricular longitudinal strain.\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=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOther CMR parameters in patients treated with SGLT2i at baseline.\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\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRVEDVi (ml/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRVESVi (ml/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRVEF\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePericardial fat (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBouchi et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2017\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117 (96\u0026ndash;136)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFukuda et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2017\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102 (79\u0026ndash;126)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHassan et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003cp\u003e(78,111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (31,79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHsu et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2019\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003cp\u003e(5.7\u0026ndash;82.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSarak et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 \u0026plusmn;\u003c/p\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.2\u0026plusmn;\u003c/p\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatoh et al\u003c/p\u003e \u003cp\u003e\u003cem\u003e2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79\u0026thinsp;\u0026plusmn;\u0026thinsp;16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThirunavukarasu et al \u003cem\u003e2021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 \u0026plusmn;\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 \u0026plusmn;\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 \u0026plusmn;\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCategorial variables are given as absolute numbers and percentage, n (%). Continuous variables are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or * median (IQR, interquartile range). \u003cb\u003eLegend.\u003c/b\u003e \u003cem\u003eRVEDVi\u003c/em\u003e: right ventricular end-diastolic volume indexed; \u003cem\u003eRVESVi\u003c/em\u003e: right ventricular end-systolic volume indexed; \u003cem\u003eRVEF\u003c/em\u003e: right ventricular ejection fraction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe smallest study had a population of 9 patients (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and the largest 169 (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Thirteen studies(\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) included patients treated with empaglifozin, six studies with dapaglifozin (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), one with ipraglifozin (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and one with luseoglifozin (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Six studies (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) included patients with reduced LVEF at baseline. Six studies (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) did not report data for a control group and were therefore analyzed as single-arm cohorts.\u003c/p\u003e\n\u003ch3\u003eMeta-Analyses\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eEffects on left heart volumes, mass, and function.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTreatment with SGLT2i was associated with a significant reduction in LVEDV (\u0026minus;\u0026thinsp;7.10 mL [95% CI: \u0026minus;13.01, \u0026minus;\u0026thinsp;1.19]; 10 studies, I\u0026sup2; = 69%, p\u0026thinsp;=\u0026thinsp;0.023), whereas no significant changes were observed in LVESV (\u0026minus;\u0026thinsp;5.97 mL [95% CI: \u0026minus;13.80, 1.87]; 8 studies, I\u0026sup2; = 80%, p\u0026thinsp;=\u0026thinsp;0.115), LVEDVi (\u0026minus;\u0026thinsp;0.53 mL/m\u0026sup2; [95% CI: \u0026minus;3.24, 2.18]; 10 studies, I\u0026sup2; = 46%, p\u0026thinsp;=\u0026thinsp;0.668), LVESVi (\u0026minus;\u0026thinsp;1.09 mL/m\u0026sup2; [95% CI: \u0026minus;2.94, 0.75], 9 studies, I\u0026sup2; = 40%, p\u0026thinsp;=\u0026thinsp;0.213), LVEF (1.14% [95% CI: \u0026minus;0.39, 2.68]; 14 studies, I\u0026sup2; = 80%, p\u0026thinsp;=\u0026thinsp;0.133) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and GLS (-0.16% [95% CI: \u0026minus;2.67, 2.35]; 5 studies, I\u0026sup2; = 83%, p\u0026thinsp;=\u0026thinsp;0.878). A non-significant trend towards increase in LVSV was observed (1.41 ml [95% CI: \u0026minus;0.12, 2.94]; 4 studies, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0, p\u0026thinsp;=\u0026thinsp;0.063, \u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). A significant decrease in LVM was observed (\u0026minus;\u0026thinsp;4.24 g [95% CI: \u0026minus;7.88, \u0026minus;\u0026thinsp;0.60]; 9 studies, I\u0026sup2; = 53%, p\u0026thinsp;=\u0026thinsp;0.027), while LVMi showed no significant change (\u0026minus;\u0026thinsp;0.86 g/m\u0026sup2; [95% CI: \u0026minus;2.02, 0.31]; 11 studies, I\u0026sup2; = 41%, p\u0026thinsp;=\u0026thinsp;0.135). There was no significant change in LAVi values (\u0026minus;\u0026thinsp;0.60 mL/m\u0026sup2; [95% CI: \u0026minus;2.70, 1.49]; 6 studies, I\u0026sup2; = 54%, p\u0026thinsp;=\u0026thinsp;0.494) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEffects on right heart volumes and function\u003c/h2\u003e \u003cp\u003eBoth RVEDVi and RVESVi remained unchanged (\u0026minus;\u0026thinsp;0.03 mL/m\u0026sup2; [95% CI: \u0026minus;2.54, 2.49]; 4 studies, I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.975; \u0026minus;0.31 mL/m\u0026sup2; [95% CI: \u0026minus;1.61, 0.99]; 4 studies, I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.502, respectively). No effect was also noted on RVEF (1.29% [95% CI: \u0026minus;1.33,3.92]; 3 studies, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;40%, p\u0026thinsp;=\u0026thinsp;0.502) \u003cb\u003e(Supplementary Fig.\u0026nbsp;2)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffects on tissue characterization\u003c/h2\u003e \u003cp\u003eThere were no differences in ECV (0.13% [95% CI: \u0026minus;1.08, 1.33]; 6 studies, I\u0026sup2; = 83%, p\u0026thinsp;=\u0026thinsp;0.807), or T1 mapping (7.38 ms [95% CI: \u0026minus;30.60, 45.37]; 3 studies, I\u0026sup2; = 76%, p\u0026thinsp;=\u0026thinsp;0.580) (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEffect on pericardial fat\u003c/h2\u003e \u003cp\u003eA trend toward reduction in pericardial fat was observed, although not reaching statistical significance (\u0026minus;\u0026thinsp;5.14 mL [95% CI: \u0026minus;11.87, 1.60]; 3 studies, I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.082) (\u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffects in patients with heart failure\u003c/h2\u003e \u003cp\u003eIn patients with LVEF at baseline\u0026thinsp;\u0026lt;\u0026thinsp;50%, LVSV increased significantly (1.83 [95% CI: 0.86, 2.80]; 2 studies, I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.027). A non-significant trend towards increase in LVEF was also noted (2.61 [95% CI: -0.50, 5.70]; 5 studies, I\u0026sup2; =80%, p\u0026thinsp;=\u0026thinsp;0.08). No significant differences were observed for the other parameters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eEffects in patients with diabetes\u003c/h2\u003e \u003cp\u003eIn patients with diabetes, there was a significant reduction in LVM was observed (\u0026ndash;4.61 [95% CI: \u0026minus;\u0026thinsp;8.59, \u0026minus;\u0026thinsp;0.63]; 3 studies, I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.024). Native T1 mapping also decreased significantly (\u0026ndash;20.34 ms [95% CI: \u0026minus;\u0026thinsp;35.47, \u0026minus;\u0026thinsp;5.22]; 2 studies, I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.008). No significant differences were found for LVEDV, LVESV, LVMi, LVEF, or ECV.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eA sensitivity analysis including only studies with a control group (n\u0026thinsp;=\u0026thinsp;15) was conducted, confirming both the decrease in LVEDV (\u0026minus;\u0026thinsp;7.73 mL [95% CI: \u0026minus;14.68, \u0026minus;\u0026thinsp;0.78]; I\u0026sup2; = 70.4%, p\u0026thinsp;=\u0026thinsp;0.033) and LVM (\u0026minus;\u0026thinsp;3.96 g [95% CI: \u0026minus;7.84, \u0026minus;\u0026thinsp;0.08]; I\u0026sup2; = 55.4%, p\u0026thinsp;=\u0026thinsp;0.047). Leave one-out analyses were performed to assess the robustness of the meta-analytic estimates across all imaging-derived parameters; for LVEDV, pooled effect estimates ranged from \u0026minus;\u0026thinsp;5.38 to \u0026minus;\u0026thinsp;8.23 mL, with all but one iteration (Cohen et al(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), p\u0026thinsp;=\u0026thinsp;0.064) maintaining statistical significance; heterogeneity varied between 59.5% and 75.5%, indicating moderate-to-high between-study variability. No single study exerted a disproportionate influence on the overall estimate. In contrast, LVESV analysis revealed greater sensitivity to individual studies, with a significant drop in heterogeneity when removing Santos-Gallego et al(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) (I\u0026sup2; = 46.5%). For indexed LV volumes (LVEDVi and LVESVi), all iterations produced non-significant results. While effect sizes remained consistently small, heterogeneity decreased substantially when Lee et al(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) (LVEDVi I\u0026sup2; = 10.0%) or Hsu et al(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) (LVESVi I\u0026sup2; = 17.7%) were excluded. The analysis of LVM demonstrated consistent effect estimates across all exclusions (range: \u0026minus;\u0026thinsp;2.73 to \u0026minus;\u0026thinsp;5.02 g), with all the iterations but Hundermarkt et al (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) (p\u0026thinsp;=\u0026thinsp;0.065) retaining statistical significance. Heterogeneity varied modestly, with Santos-Gallego et al (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) being a key contributor (I\u0026sup2; = 0% upon exclusion). For LVEF, removal of Cohen et al (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) yielded a statistically significant result (p\u0026thinsp;=\u0026thinsp;0.029), with heterogeneity remanining steadily high across all iterations. For LVSV, statistical significance was observed upon exclusion of Brown et al (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) (p\u0026thinsp;=\u0026thinsp;0.014, MD 1.88) and heterogeneity remained null across all exclusions. Both LVMi and LAVi analyses revealed non-significant effects with moderate, stable, heterogeneity for LVMi (I\u0026sup2; range: 30.3\u0026ndash;46.3%) and notable reduction in heterogeneity after the exclusion of Oldgren et al(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) (I\u0026sup2; = 7.9%) or Carberry et al (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) (I\u0026sup2; = 12.9%) for LAVi \u003cb\u003e(Supplementary Table\u0026nbsp;3).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMeta-regression analyses\u003c/h2\u003e \u003cp\u003eAt meta-regression analyses, none of the predictors included in the model (i.e., age, male sex and diabetes) revealed a significant effect modification on LVEDV, LVESV, LVEDVi, LVESVi, LVEF, LAVi, LVM, LVMi (all p-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Meta-regression analyses were not performed on other CMR parameters due to the limited number of studies available.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePublication bias and grading of evidence\u003c/h2\u003e \u003cp\u003eFunnel plots were visually inspected for asymmetry and assessed using Egger\u0026rsquo;s regression test across all cardiac structural, functional, and tissue parameters. No substantial visual asymmetry was observed for most outcomes, except for ECV and LAVi. Egger\u0026rsquo;s test results statistically confirmed possible publication bias for both parameters (p\u0026thinsp;=\u0026thinsp;0.01 and 0.031, respectively) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003eand Supplementary Fig.\u0026nbsp;3).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccording to the GRADE Working Group system(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), the level of certainty for the association between SGLT2i treatment and CMR outcomes was moderate for most outcomes but in 7, in which were adjudicated to be low (\u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e The present updated systematic review and meta-analysis demonstrated an association between SGLT2i treatment and decrease of LVEDV and LVM, providing evidence for favorable effects on cardiac remodeling. These results were confirmed in a sensitivity analysis including only studies with control group and were not affected by baseline patient characteristics including age, sex and diabetes. Patients with reduced LVEF also showed a significant, although modest, increase in LVSV after SGLT2i treatment.\u003c/p\u003e \u003cp\u003eOur data on favorable LV remodeling are in line with a previous meta-analysis including 9 randomized controlled trials (3 of which were CMR-based) demonstrating a significant reduction in LV volumes and indexed LV mass with significant increase in LVEF in the whole population (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). However, the use of different imaging modalities to assess cardiac remodeling in that study may have introduced variability and potentially obscured subtle treatment effects. CMR is in fact considered the gold standard for quantifying ventricular volumes, mass, and tissue characterization, offering superior spatial resolution and interobserver consistency(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). In contrast, echocardiography is more widely available and used in clinical practice but is subject to greater operator dependence and geometric assumptions, that may be unneglectable particularly in patients with abnormal ventricular shapes(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA recent meta-analysis (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) focusing only on CMR studies (n\u0026thinsp;=\u0026thinsp;5, 408 patients) was able to confirm only LVM regression after SGLT2i administration, likely due to the limited number of studies available at the time of publication. Cardiac remodeling reflects complex molecular and structural changes, involving inflammation, fibrosis, and metabolic dysregulation(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Maladaptive remodeling is associated with worse clinical outcomes, and represents one of the main targets of HF therapy(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). In this regard, SGLT2i have proven in several trials to reduce key cardiovascular endpoints as hospitalizations and HF-related mortality, irrespective of the glycemic status(\u003cspan additionalcitationids=\"CR41 CR42 CR43\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). The exact mechanisms subtended to these beneficial effects are not yet fully understood, with different hypothesis generated so far(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy blocking glucose reabsorption in the proximal renal tubule, these agents promote glycosuria, reduce insulin levels, and increase glucagon secretion\u0026mdash;facilitating lipolysis and fat oxidation, with consequent reduction in visceral adiposity(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Moreover, their natriuretic effect determines unloading and suppresses the renin-angiotensin-aldosterone system, with favorable effect on blood pressure(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). However, these metabolic and hemodynamic changes alone do not fully account for the observed CV benefits. Improvements in endothelial function and arterial stiffness, reduced oxidative stress(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), inflammation(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e), vascular resistance (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), and a shift toward more efficient metabolic pathways(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) have been demonstrated in clinical and pre-clinical models and may all contribute to the positive observed effect(\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this regard, we found no impact of SGLT2i treatment on tissue characterization indices such as T1 mapping and ECV in the whole population; this result should be interpret carefully given the limited number of studies included in the analysis for these parameters, with possible publication bias for ECV(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). A significant decrease in T1 mapping values was noted in patients with diabetes, although only 2 studies were available for this analysis. Therefore, the reduction in LVM observed following SGLT2 inhibitor treatment appears to result primarily from left ventricular unloading rather than from a decrease in extracellular volume. However, pre-clinical studies in animal models demonstrated reduced intramyocardial fibrosis after empaglifozin with lower collagen deposition and decreased extracellular volume (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Moreover, in some studies a significant reduction in LVM was observed even in the absence of LV unloading (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRemarkably, the demonstrated effect on LV volumes may have a significant impact on clinical outcomes; in a pooled analysis, a 10 mL decrease in end-diastolic volume was associated with a 5% relative reduction in the odds of mortality(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study also found no evidence of significant changes in RV volumes and function. This is in line with the results of the post-hoc analysis of the EMPA-HEART CardioLink-6 that failed to demonstrate any impact of empaglifozin treatment on RV parameters (including RV mass) on 90 patients with diabetes and coronary artery disease(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, the number of included studies for some parameters\u0026mdash;particularly right ventricular volumes, strain, and tissue characterization markers\u0026mdash;was limited, reducing the statistical power of the analysis. Heterogeneity was also moderate to high for several outcomes, potentially reflecting differences in patient populations, imaging protocols, follow-up durations, and background therapies. However, the sensitivity analysis performed failed to identify studies that would significantly affect our results. The meta-regression of pre-specified and other variables did not identify any significant moderator; however, confounding cannot be ruled out. Finally, some of the included studies had relatively small sample sizes and were not blinded or randomized, increasing the risk of bias. Prospective studies with standardized CMR endpoints and longer follow-up will certainly provide more information, particularly regarding effects on tissue-level changes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis meta-analysis demonstrated an association between SGLT2i treatment and decrease of LVEDV and LVM, reinforcing the mechanistic plausibility of reverse LV cardiac remodeling as a contributor to the cardiovascular benefits of SGLT2i therapy.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eConflicts of interest:\u003c/h2\u003e\n\u003cp\u003eAll authors have reported that they have no relationships relevant to the contents of this paper to disclose.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by grants from the Italian Ministry of University and Research (PNRR\u0026mdash;National Center for Gene Therapy and Drugs based on RNA Technology No. CN00000041) and from the Italian Ministry of Health (POS4 \u0026lsquo;Cal-Hub-Ria\u0026rsquo; No. T4-AN-09; PNRRMAD-2022-12376814).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eI.L.: conceptualization, statistical analysis, drafting of the main manuscript. N.S.: conceptualization, drafting main manuscript. A.C. and J.I.: systematic review, data extraction, figure preparation. S.F., K.S., S.D.R., S.D, G.C., critical revision of the manuscript.C.B.D. and D.T.: Senior review, and critical revision of the manuscript. All authors contributed to manuscript review and approved the final version.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data underlying this article will be shared on reasonable request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, B\u0026ouml;hm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021;42(36):3599\u0026ndash;726.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, B\u0026ouml;hm M, et al. 2023 Focused Update of the 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2023;44(37):3627\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCersosimo A, Salerno N, Sabatino J, Scatteia A, Bisaccia G, De Rosa S, et al. Underlying mechanisms and cardioprotective effects of SGLT2i and GLP-1Ra: insights from cardiovascular magnetic resonance. Cardiovasc Diabetol. 2024;23(1):94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAimo A, Gaggin HK, Barison A, Emdin M, Januzzi JL. Imaging, Biomarker, and Clinical Predictors of Cardiac Remodeling in Heart Failure With Reduced Ejection Fraction. 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Dapagliflozin Versus Placebo on Left Ventricular Remodeling in Patients With Diabetes and Heart Failure: The REFORM Trial. Diabetes Care. 2020;43(6):1356\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee MMY, Brooksbank KJM, Wetherall K, Mangion K, Roditi G, Campbell RT, et al. Effect of Empagliflozin on Left Ventricular Volumes in Patients With Type 2 Diabetes, or Prediabetes, and Heart Failure With Reduced Ejection Fraction (SUGAR-DM-HF). Circulation. 2021;143(6):516\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerma S, Mazer CD, Yan AT, Mason T, Garg V, Teoh H, et al. Effect of Empagliflozin on Left Ventricular Mass in Patients With Type 2 Diabetes Mellitus and Coronary Artery Disease: The EMPA-HEART CardioLink-6 Randomized Clinical Trial. Circulation. 2019;140(21):1693\u0026ndash;702.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukuda T, Bouchi R, Terashima M, Sasahara Y, Asakawa M, Takeuchi T, et al. Ipragliflozin Reduces Epicardial Fat Accumulation in Non-Obese Type 2 Diabetic Patients with Visceral Obesity: A Pilot Study. Diabetes Ther. 2017;8(4):851\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouchi R, Terashima M, Sasahara Y, Asakawa M, Fukuda T, Takeuchi T, et al. Luseogliflozin reduces epicardial fat accumulation in patients with type 2 diabetes: a pilot study. Cardiovasc Diabetol. 2017;16(1):32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen ND, Gutman SJ, Briganti EM, Taylor AJ. Effects of empagliflozin treatment on cardiac function and structure in patients with type 2 diabetes: a cardiac magnetic resonance study. Intern Med J. 2019;49(8):1006\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConnelly KA, Mazer CD, Puar P, Teoh H, Wang CH, Mason T, et al. Empagliflozin and Left Ventricular Remodeling in People Without Diabetes: Primary Results of the EMPA-HEART 2 CardioLink-7 Randomized Clinical Trial. Circulation. 2023;147(4):284\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaborit B, Ancel P, Abdullah AE, Maurice F, Abdesselam I, Calen A, et al. Effect of empagliflozin on ectopic fat stores and myocardial energetics in type 2 diabetes: the EMPACEF study. Cardiovasc Diabetol. 2021;20(1):57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHassan A, Samaan K, Asfour A, Baghdady Y, Samaan AA. Ventricular remodeling and hemodynamic changes in heart failure patients with non-ischemic dilated cardiomyopathy following dapagliflozin initiation. Egypt Heart J. 2024;76(1):76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu JC, Wang CY, Su MYM, Lin LY, Yang WS. Effect of Empagliflozin on Cardiac Function, Adiposity, and Diffuse Fibrosis in Patients with Type 2 Diabetes Mellitus. Sci Rep. 2019;9(1):15348.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOldgren J, Laurila S, \u0026Aring;kerblom A, Latva-Rasku A, Rebelos E, Isackson H, et al. Effects of 6 weeks of treatment with dapagliflozin, a sodium‐glucose co‐transporter‐2 inhibitor, on myocardial function and metabolism in patients with type 2 diabetes: A randomized, placebo‐controlled, exploratory study. Diabetes Obes Metab. 2021;23(7):1505\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThirunavukarasu S, Jex N, Chowdhary A, Hassan IU, Straw S, Craven TP, et al. Empagliflozin Treatment Is Associated With Improvements in Cardiac Energetics and Function and Reductions in Myocardial Cellular Volume in Patients With Type 2 Diabetes. Diabetes. 2021;70(12):2810\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang DD, Naumova AV, Isquith D, Sapp J, Huynh KA, Tucker I, et al. Dapagliflozin reduces systemic inflammation in patients with type 2 diabetes without known heart failure. Cardiovasc Diabetol. 2024;23(1):197.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSatoh T, Yaoita N, Higuchi S, Nochioka K, Yamamoto S, Sato H, et al. Impact of Sodium-Glucose Co‐Transporter‐2 Inhibitors on Exercise‐Induced Pulmonary Hypertension. Pulm Circ. 2024;14(4):e70026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarluccio E, Biagioli P, Reboldi G, Mengoni A, Lauciello R, Zuchi C, et al. Left ventricular remodeling response to SGLT2 inhibitors in heart failure: an updated meta-analysis of randomized controlled studies. Cardiovasc Diabetol. 2023;22(1):235.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKramer DG, Trikalinos TA, Kent DM, Antonopoulos GV, Konstam MA, Udelson JE. Quantitative Evaluation of Drug or Device Effects on Ventricular Remodeling as Predictors of Therapeutic Effects on Mortality in Patients With Heart Failure and Reduced Ejection Fraction. J Am Coll Cardiol. 2010;56(5):392\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBellenger N. Comparison of left ventricular ejection fraction and volumes in heart failure by echocardiography, radionuclide ventriculography and cardiovascular magnetic resonance. Are they interchangeable? Eur Heart J. 2000;21(16):1387\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDhingra NK, Mistry N, Puar P, Verma R, Anker S, Mazer CD, et al. SGLT2 inhibitors and cardiac remodelling: a systematic review and meta-analysis of randomized cardiac magnetic resonance imaging trials. ESC Heart Fail. 2021;8(6):4693\u0026ndash;700.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoulet J, Mehra MR. Left Ventricular Reverse Remodeling in Heart Failure: Remission to Recovery. Struct Heart. 2021;5(5):466\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMc Causland FR, Claggett BL, Vaduganathan M, Desai AS, Jhund P, De Boer RA, et al. Dapagliflozin and Kidney Outcomes in Patients With Heart Failure With Mildly Reduced or Preserved Ejection Fraction: A Prespecified Analysis of the DELIVER Randomized Clinical Trial. JAMA Cardiol. 2023;8(1):56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnker SD, Butler J, Filippatos G, Ferreira JP, Bocchi E, B\u0026ouml;hm M, 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\u003ePacker M, Anker SD, Butler J, Filippatos G, Pocock SJ, Carson P, 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\u003eSolomon SD, McMurray JJV, Claggett B, De Boer RA, DeMets D, Hernandez AF, et al. Dapagliflozin in Heart Failure with Mildly Reduced or Preserved Ejection Fraction. N Engl J Med. 2022;387(12):1089\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcMurray JJV, Solomon SD, Inzucchi SE, K\u0026oslash;ber L, Kosiborod MN, Martinez FA, 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\u003eXu B, Li S, Kang B, Zhou J. The current role of sodium-glucose cotransporter 2 inhibitors in type 2 diabetes mellitus management. Cardiovasc Diabetol. 2022;21(1):83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnsary TM, Nakano D, Nishiyama A. Diuretic Effects of Sodium Glucose Cotransporter 2 Inhibitors and Their Influence on the Renin-Angiotensin System. Int J Mol Sci. 2019;20(3):629.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoares RN, Ramirez-Perez FI, Cabral-Amador FJ, Morales-Quinones M, Foote CA, Ghiarone T, et al. SGLT2 inhibition attenuates arterial dysfunction and decreases vascular F-actin content and expression of proteins associated with oxidative stress in aged mice. GeroScience. 2022;44(3):1657\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu L, Nagata N, Nagashimada M, Zhuge F, Ni Y, Chen G, et al. SGLT2 Inhibition by Empagliflozin Promotes Fat Utilization and Browning and Attenuates Inflammation and Insulin Resistance by Polarizing M2 Macrophages in Diet-induced Obese Mice. EBioMedicine. 2017;20:137\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos-Gallego CG, Requena-Ibanez JA, San Antonio R, Ishikawa K, Watanabe S, Picatoste B, et al. Empagliflozin Ameliorates Adverse Left Ventricular Remodeling in Nondiabetic Heart Failure by Enhancing Myocardial Energetics. J Am Coll Cardiol. 2019;73(15):1931\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalerno N, Ielapi J, Cersosimo A, Leo I, Di Costanzo A, Armentaro G, et al. Early hemodynamic impact of SGLT2 inhibitors in overweight cardiometabolic heart failure: beyond fluid offloading to vascular adaptation\u0026ndash; a preliminary report. Cardiovasc Diabetol. 2025;24(1):141.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"heart failure, sodium-glucose transport protein 2, cardiovascular magnetic resonance, reverse cardiac remodeling","lastPublishedDoi":"10.21203/rs.3.rs-6790667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6790667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and aim: \u003c/strong\u003eSodium-glucose cotransporter-2 inhibitors (SGLT2i) improve outcomes in patients with heart failure (HF) but underlying mechanisms remain incompletely understood. Cardiac magnetic resonance (CMR) is key in evaluating cardiac structure and function, enabling accurate assessment of reverse remodeling. Aim of this systematic review and meta-analysis was to assess the effects of SGLT2i on cardiac remodeling evaluated by CMR changes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a systematic review and meta-analysis of studies assessing changes in CMR parameters in patients treated with SGLT2i (PROSPERO registration: CRD42024574302). \u0026nbsp;Databases were searched through April 30, 2025. Random-effects models were used to pool mean changes in left and right ventricular volumes, mass, function, stroke volume, global longitudinal strain, left atrial volume, and tissue characterization indices. Meta-regression and sensitivity analyses were performed to evaluate potential sources of heterogeneity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nTwenty-one studies and 1008 patients were included. Treatment with SGLT2i was associated with significant reductions in left ventricular (LV) end-diastolic volume (−7.10 mL; 95% CI: −13.01 to −1.19, p=0.023) and left ventricular mass (−4.24 g; 95% CI: −7.88 to −0.60, p=0.027). No significant change was noted in other CMR parameters. A subgroup analysis in patients with reduced LV ejection fraction showed improvement in LV stroke volume. Meta-regression revealed no significant effect of age, male sex or diabetes prevalence on pooled estimates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003cbr\u003e\nSGLT2i are associated with favorable reverse remodeling effects as assessed by CMR, including reductions in LV volumes and mass.\u003c/p\u003e","manuscriptTitle":"Effect of SGLT2 Inhibitors on Cardiac Structure and Function Assessed by Cardiac Magnetic Resonance: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 11:24:09","doi":"10.21203/rs.3.rs-6790667/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-30T12:26:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-29T23:24:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-26T13:41:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120166929295413962576705969989904023423","date":"2025-06-21T16:02:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87590366241828516204115659458771222427","date":"2025-06-20T18:13:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84694724267506883891805425356582539500","date":"2025-06-18T12:17:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-14T18:26:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272972376059687053710387233358055800172","date":"2025-06-04T12:56:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60055233996417887390027869793381721451","date":"2025-06-03T19:10:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-03T19:01:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-31T13:07:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-31T12:29:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Diabetology","date":"2025-05-31T11:16:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"45c0b791-7928-413f-8278-ea7cff4bafa6","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-25T16:35:19+00:00","versionOfRecord":{"articleIdentity":"rs-6790667","link":"https://doi.org/10.1186/s12933-025-02904-4","journal":{"identity":"cardiovascular-diabetology","isVorOnly":false,"title":"Cardiovascular Diabetology"},"publishedOn":"2025-08-21 16:29:26","publishedOnDateReadable":"August 21st, 2025"},"versionCreatedAt":"2025-06-09 11:24:09","video":"","vorDoi":"10.1186/s12933-025-02904-4","vorDoiUrl":"https://doi.org/10.1186/s12933-025-02904-4","workflowStages":[]},"version":"v1","identity":"rs-6790667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6790667","identity":"rs-6790667","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}