Skip to content
2000
image of Sodium-Glucose Co-transporter-2 Inhibitors and Cardiac Function Parameters: A Network Meta-analysis and Trial Sequential Analysis of Randomized Clinical Trials

Abstract

Background

Sodium-glucose Co-transporter-2 Inhibitors (SGLT2is) are recommended for heart failure based on clinical outcomes. However, there is a lack of evidence linking SGLT2is with changes in cardiac function parameters.

Aim

This study aimed to systematically evaluate the literature assessing the impact of SGLT2is on various cardiac parameters.

Methods

Randomized clinical trials assessing any of the cardiac function parameters (atrial, valvular, pulmonary artery, and left ventricular) with SGLT2is were included. Mixed treatment comparison pooled estimates (mean differences (MD); 95% confidence intervals (95% CI)) were generated using a random-effects model and validated using trial sequential and bootstrap analyses. Intraclass differences and sub-group analysis in heart failure were evaluated.

Results

Thirty-four studies (2930 participants) were included in the review, of which 31 (2616 participants) were included in the meta-analysis. SGLT2is were associated with a significant increase in left ventricular ejection fraction (MD: 0.73; 95% CI: 0.09, 1.37%) and reductions in left ventricular mass (MD: -0.21; 95% CI: -0.39, -0.03 g), left ventricular mass index (MD: -0.22; 95% CI: -0.36, -0.08 g/m2), left ventricular end-diastolic diameter (MD: -0.71; 95% CI: -1.29, -0.13 cm), left ventricular end-diastolic volume (MD: -0.56; 95% CI: -1.02, -0.1 ml), left atrial volume index (MD: -0.35; 95% CI: -0.58, -0.04 ml/m2), and pulmonary artery systolic pressure (MD: -1.08; 95% CI: -1.94, -0.21 mmHg). Significant improvements in various cardiac parameters were observed in studies conducted on heart failure.

Conclusion

The findings of this study assessing cardiac function parameters support the guidelines recommending SGLT2 inhibitors in heart failure, which are primarily based on clinical outcomes.

Loading

Article metrics loading...

/content/journals/crcep/10.2174/0127724328337478250604061355
2025-06-16
2025-09-29
Loading full text...

Full text loading...

References

  1. Pradhan A. Vohra S. Vishwakarma P. Sethi R. Review on sodium-glucose cotransporter 2 inhibitor (SGLT2i) in diabetes mellitus and heart failure. J. Family Med. Prim. Care 2019 8 6 1855 1862 10.4103/jfmpc.jfmpc_232_19 31334145
    [Google Scholar]
  2. Chen Y Peng D New insights into the molecular mechanisms of SGLT2 inhibitors on ventricular remodeling. Int. Immunopharmacol. 2023 118 110072 10.1016/j.intimp.2023.110072
    [Google Scholar]
  3. Talha K.M. Anker S.D. Butler J. SGLT-2 inhibitors in heart failure: A review of current evidence. Int. J. Heart Fail. 2023 5 2 82 90 10.36628/ijhf.2022.0030 37180562
    [Google Scholar]
  4. Wee C.F. Teo Y.H. Teo Y.N. Syn N.L.X. See R.M. Leong S. Yip A.S.Y. Ong Z.X. Lee C.H. Chan M.Y.Y. Poh K.K. Ong C.C. Teo L.L.S. Singh D. Tan B.Y.Q. Yeo L.L.L. Kong W.K.F. Yeo T.C. Wong R.C.C. Chai P. Sia C.H. Effects of Sodium/Glucose cotransporter 2 (SGLT2) inhibitors on cardiac imaging parameters: A systematic review and meta-analysis of randomized controlled trials. J. Cardiovasc. Imaging 2022 30 3 153 168 10.4250/jcvi.2021.0159 35879251
    [Google Scholar]
  5. Theofilis P. Antonopoulos A.S. Katsimichas T. Oikonomou E. Siasos G. Aggeli C. Tsioufis K. Tousoulis D. The impact of SGLT2 inhibition on imaging markers of cardiac function: A systematic review and meta-analysis. Pharmacol. Res. 2022 180 106243 10.1016/j.phrs.2022.106243 35523389
    [Google Scholar]
  6. Carluccio E. Biagioli P. Reboldi G. Mengoni A. Lauciello R. Zuchi C. D’Addario S. Bardelli G. Ambrosio G. Left ventricular remodeling response to SGLT2 inhibitors in heart failure: An updated meta-analysis of randomized controlled studies. Cardiovasc. Diabetol. 2023 22 1 235 10.1186/s12933‑023‑01970‑w 37660005
    [Google Scholar]
  7. Sridharan K. Risk of infectious adverse events with SGLT-2 inhibitors: A systematic review and network meta-analysis 2024 Available from: https://osf.io/5fwyk
  8. Verde P.E. Ohmann C. Combining randomized and non‐randomized evidence in clinical research: A review of methods and applications. Res. Synth. Methods 2015 6 1 45 62 10.1002/jrsm.1122 26035469
    [Google Scholar]
  9. Hutton B. Salanti G. Caldwell D.M. Chaimani A. Schmid C.H. Cameron C. Ioannidis J.P.A. Straus S. Thorlund K. Jansen J.P. Mulrow C. Catalá-López F. Gøtzsche P.C. Dickersin K. Boutron I. Altman D.G. Moher D. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: Checklist and explanations. Ann. Intern. Med. 2015 162 11 777 784 10.7326/M14‑2385 26030634
    [Google Scholar]
  10. Higgins J.P.T. Altman D.G. Gøtzsche P.C. Jüni P. Moher D. Oxman A.D. Savovic J. Schulz K.F. Weeks L. Sterne J.A.C. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011 343 d5928 10.1136/bmj.d5928 22008217
    [Google Scholar]
  11. Lin L. Chu H. Quantifying publication bias in meta-analysis. Biometrics 2018 74 3 785 794 10.1111/biom.12817 29141096
    [Google Scholar]
  12. Introduction to GRADE handbook 2013 Available from: https://gdt.gradepro.org/app/handbook/handbook.html
  13. Luo D. Wan X. Liu J. Tong T. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat. Methods Med. Res. 2018 27 6 1785 1805 10.1177/0962280216669183 27683581
    [Google Scholar]
  14. Wan X. Wang W. Liu J. Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med. Res. Methodol. 2014 14 1 135 10.1186/1471‑2288‑14‑135 25524443
    [Google Scholar]
  15. Bhatt D.L. Szarek M. Steg P.G. Cannon C.P. Leiter L.A. McGuire D.K. Lewis J.B. Riddle M.C. Voors A.A. Metra M. Lund L.H. Komajda M. Testani J.M. Wilcox C.S. Ponikowski P. Lopes R.D. Verma S. Lapuerta P. Pitt B. Sotagliflozin in patients with diabetes and recent worsening heart failure. N. Engl. J. Med. 2021 384 2 117 128 10.1056/NEJMoa2030183 33200892
    [Google Scholar]
  16. Azevedo P.S. Polegato B.F. Minicucci M.F. Paiva S.A.R. Zornoff L.A.M. Cardiac remodeling: Concepts, clinical impact, pathophysiological mechanisms and pharmacologic treatment. Arq. Bras. Cardiol. 2016 106 1 62 69 10.5935/abc.20160005 26647721
    [Google Scholar]
  17. Kramer D.G. Trikalinos T.A. Kent D.M. Antonopoulos G.V. Konstam M.A. Udelson J.E. 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: A meta-analytic approach. J. Am. Coll. Cardiol. 2010 56 5 392 406 10.1016/j.jacc.2010.05.011 20650361
    [Google Scholar]
  18. Theofilis P. Sagris M. Oikonomou E. Antonopoulos A.S. Siasos G. Tsioufis K. Tousoulis D. Pleiotropic effects of SGLT2 inhibitors and heart failure outcomes. Diabetes Res. Clin. Pract. 2022 188 109927 10.1016/j.diabres.2022.109927 35577035
    [Google Scholar]
  19. Yang Z. Li T. Xian J. Chen J. Huang Y. Zhang Q. Lin X. Lu H. Lin Y. SGLT2 inhibitor dapagliflozin attenuates cardiac fibrosis and inflammation by reverting the HIF ‐2α signaling pathway in arrhythmogenic cardiomyopathy. FASEB J. 2022 36 7 e22410 10.1096/fj.202200243R 35713937
    [Google Scholar]
  20. Devereux R.B. Wachtell K. Gerdts E. Boman K. Nieminen M.S. Papademetriou V. Rokkedal J. Harris K. Aurup P. Dahlöf B. Prognostic significance of left ventricular mass change during treatment of hypertension. JAMA 2004 292 19 2350 2356 10.1001/jama.292.19.2350 15547162
    [Google Scholar]
  21. Movahed M.R. Ramaraj R. Manrique C. Hashemzadeh M. Left ventricular hypertrophy is independently associated with all-cause mortality. Am. J. Cardiovasc. Dis. 2022 12 1 38 41 35291507
    [Google Scholar]
  22. Khan M.A. Yang E.Y. Zhan Y. Judd R.M. Chan W. Nabi F. Heitner J.F. Kim R.J. Klem I. Nagueh S.F. Shah D.J. Association of left atrial volume index and all-cause mortality in patients referred for routine cardiovascular magnetic resonance: A multicenter study. J. Cardiovasc. Magn. Reson. 2019 21 1 4 10.1186/s12968‑018‑0517‑0 30612579
    [Google Scholar]
  23. Kranert M. Shchetynska-Marinova T. Liebe V. Doesch C. Papavassiliu T. Akin I. Borggrefe M. Hohneck A. Recurrence of atrial fibrillation in dependence of left atrial volume index. In Vivo 2020 34 2 889 896 10.21873/invivo.11854 32111800
    [Google Scholar]
  24. El Aouar L.M.M. Meyerfreud D. Magalhães P. Rodrigues S.L. Baldo M.P. El Aouar S.M. El Aouar N.A. Mill J.G. Campos Filho O. Campos Filho O. Relationship between left atrial volume and diastolic dysfunction in 500 Brazilian patients. Arq. Bras. Cardiol. 2013 101 1 52 58 10.5935/abc.20130109 23702813
    [Google Scholar]
  25. Hoshida S. Tachibana K. Shinoda Y. Minamisaka T. Yamada T. Higuchi Y. Nakagawa Y. Abe H. Fuji H. Yasumura Y. Hikoso S. Nakatani D. Sakata Y. Left atrial pressure overload and prognosis in elderly patients with heart failure and preserved ejection fraction: A prospective multicenter observational study. BMJ Open 2021 11 9 e044605 10.1136/bmjopen‑2020‑044605 34593483
    [Google Scholar]
  26. D’Amario D. Rodolico D. Delvinioti A. Laborante R. Iacomini C. Masciocchi C. Restivo A. Ciliberti G. Galli M. Paglianiti A.D. Iaconelli A. Zito A. Lenkowicz J. Patarnello S. Cesario A. Valentini V. Crea F. Eligibility for the 4 pharmacological pillars in heart failure with reduced ejection fraction at discharge. J. Am. Heart Assoc. 2023 12 13 e029071 10.1161/JAHA.122.029071 37382176
    [Google Scholar]
  27. Januzzi J.L. Jr Butler J. Jarolim P. Sattar N. Vijapurkar U. Desai M. Davies M.J. Effects of canagliflozin on cardiovascular biomarkers in older adults with type 2 diabetes. J. Am. Coll. Cardiol. 2017 70 6 704 712 10.1016/j.jacc.2017.06.016 28619659
    [Google Scholar]
  28. Chew D.S. Heikki H. Schmidt G. Kavanagh K.M. Dommasch M. Bloch Thomsen P.E. Sinnecker D. Raatikainen P. Exner D.V. Change in left ventricular ejection fraction following first myocardial infarction and outcome. JACC Clin. Electrophysiol. 2018 4 5 672 682 10.1016/j.jacep.2017.12.015 29798797
    [Google Scholar]
  29. Li C. Zhang J. Xue M. Li X. Han F. Liu X. Xu L. Lu Y. Cheng Y. Li T. Yu X. Sun B. Chen L. SGLT2 inhibition with empagliflozin attenuates myocardial oxidative stress and fibrosis in diabetic mice heart. Cardiovasc. Diabetol. 2019 18 1 15 10.1186/s12933‑019‑0816‑2 30710997
    [Google Scholar]
  30. Wilcox C.S. Testani J.M. Pitt B. Pathophysiology of diuretic resistance and its implications for the management of chronic heart failure. Hypertension 2020 76 4 1045 1054 10.1161/HYPERTENSIONAHA.120.15205 32829662
    [Google Scholar]
/content/journals/crcep/10.2174/0127724328337478250604061355
Loading
/content/journals/crcep/10.2174/0127724328337478250604061355
Loading

Data & Media loading...

Supplements

Supplementary material and PRISMA checklist is available on the publisher’s website along with the published article.

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test