Cited by 154Diabetes Treatment and ManagementHeart Failure Treatment and ManagementCardiovascular Function and Risk Factors

Heart failure risk stratification and efficacy of sodium-glucose cotransporter-2 inhibitors in patients with type 2 diabetes mellitus

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Berg, David D., Wiviott, Stephen D., Scirica, Benjamin M., Gurmu, Yared, Mosenzon, Ofri, Murphy, Sabina A., Bhatt, Deepak L., Leiter, Lawrence A. +8 more·2019·Circulation

Abstract

Background: Patients with type 2 diabetes mellitus (T2DM) are at increased risk of developing heart failure. Sodium-glucose cotransporter-2 inhibitors reduce the risk of hospitalization for heart failure (HHF) in patients with T2DM. We aimed to develop and validate a practical clinical risk score for HHF in patients with T2DM and assess whether this score can identify high-risk patients with T2DM who have the greatest reduction in risk for HHF with a sodium-glucose cotransporter-2 inhibitor. Methods: We developed a clinical risk score for HHF in 8212 patients with T2DM in the placebo arm of SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients With Diabetes Mellitus–Thrombolysis in Myocardial Infarction 53). Candidate variables were assessed using multivariable Cox regression, and independent clinical risk indicators achieving statistical significance of P <0.001 were included in the risk score. We externally validated the score in 8578 patients with T2DM in the placebo arm of DECLARE-TIMI 58 (Dapagliflozin Effect on Cardiovascular Events–Thrombolysis in Myocardial Infarction 58). The relative and absolute risk reductions in HHF with the sodium-glucose cotransporter-2 inhibitor dapagliflozin were assessed by baseline HHF risk. Results: Five clinical variables were independent risk predictors of HHF: prior heart failure, history of atrial fibrillation, coronary artery disease, estimated glomerular filtration rate, and urine albumin-to-creatinine ratio. A simple integer-based score (0–7 points) using these predictors identified a >20-fold gradient of HHF risk ( P for trend <0.001) in both the derivation and validation cohorts, with C indices of 0.81 and 0.78, respectively. Although relative risk reductions with dapagliflozin were similar for patients across the risk scores (25%–34%), absolute risk reductions were greater in those at higher baseline risk (1-sided P for trend=0.04), with high-risk (2 points) and very-high-risk (≥3 points) patients having 1.5% and 2.7% absolute reductions in Kaplan-Meier estimates of HHF risk at 4 years, respectively. Conclusions: Risk stratification using a novel clinical risk score for HHF in patients with T2DM identifies patients at higher risk for HHF who derive greater absolute benefit from sodium-glucose cotransporter-2 inhibition. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifiers: NCT01107886 and NCT01730534.

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Crossref · 10.1161/circulationaha.119.042685

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  • While greater reductions in HF hospitalization risk are observed with SGLT2 inhibitor therapy in individuals with higher baseline HF risk, some benefit is observed across the full range of HF risk.

    “Similarly, while greater reductions in HF hospitalization risk are observed with SGLT2 inhibitor therapy in individuals with higher baseline HF risk, some benefit is observed across the full range of HF risk (135).”

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Research works printed but not linked: 14

  1. [4]Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, O’Flaherty M, Pandey A, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani SS, American Heart Association Council on E, Prevention Statistics C and Stroke Statistics S. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation. 2019; 139: e56– e528. 30700139
  2. [5]Boudina S and Abel ED. Diabetic cardiomyopathy revisited. Circulation. 2007; 115: 3213– 3223. 17592090
  3. [6]McMurray JJ, Gerstein HC, Holman RR and Pfeffer MA. Heart failure: a cardiovascular outcome in diabetes that can no longer be ignored. Lancet Diabetes Endocrinol. 2014; 2: 843– 851. 24731668
  4. [10]Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, Shaw W, Law G, Desai M, Matthews DR and Group CPC. Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes. N Engl J Med. 2017; 377: 644– 657. 28605608
  5. [11]Wiviott SD, Raz I, Bonaca MP, Mosenzon O, Kato ET, Cahn A, Silverman MG, Zelniker TA, Kuder JF, Murphy SA, Bhatt DL, Leiter LA, McGuire DK, Wilding JPH, Ruff CT, Gause-Nilsson IAM, Fredriksson M, Johansson PA, Langkilde AM, Sabatine MS and Investigators D-T. Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med. 2019; 380: 347– 357. 30415602
  6. [13]Scirica BM, Bhatt DL, Braunwald E, Steg PG, Davidson J, Hirshberg B, Ohman P, Frederich R, Wiviott SD, Hoffman EB, Cavender MA, Udell JA, Desai NR, Mosenzon O, McGuire DK, Ray KK, Leiter LA, Raz I, Committee S-TS and Investigators. Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus. N Engl J Med. 2013; 369: 1317– 1326. 23992601
  7. [14]Bertoni AG, Hundley WG, Massing MW, Bonds DE, Burke GL and Goff DC, Jr. Heart failure prevalence, incidence, and mortality in the elderly with diabetes. Diabetes Care. 2004; 27: 699– 703. 14988288
  8. [15]Carr AA, Kowey PR, Devereux RB, Brenner BM, Dahlof B, Ibsen H, Lindholm LH, Lyle PA, Snapinn SM, Zhang Z, Edelman JM and Shahinfar S. Hospitalizations for new heart failure among subjects with diabetes mellitus in the RENAAL and LIFE studies. Am J Cardiol. 2005; 96: 1530– 1536. 16310435
  9. [16]Rodrigues B, Cam MC and McNeill JH. Myocardial substrate metabolism: implications for diabetic cardiomyopathy. J Mol Cell Cardiol. 1995; 27: 169– 179. 7760340
  10. [17]Bahrami H, Bluemke DA, Kronmal R, Bertoni AG, Lloyd-Jones DM, Shahar E, Szklo M and Lima JA. Novel metabolic risk factors for incident heart failure and their relationship with obesity: the MESA (Multi-Ethnic Study of Atherosclerosis) study. J Am Coll Cardiol. 2008; 51: 1775– 1783. 18452784
  11. [18]Masoudi FA, Inzucchi SE, Wang Y, Havranek EP, Foody JM and Krumholz HM. Thiazolidinediones, metformin, and outcomes in older patients with diabetes and heart failure: an observational study. Circulation. 2005; 111: 583– 590. 15699279
  12. [19]Lago RM, Singh PP and Nesto RW. Congestive heart failure and cardiovascular death in patients with prediabetes and type 2 diabetes given thiazolidinediones: a meta-analysis of randomised clinical trials. Lancet. 2007; 370: 1129– 1136. 17905165
  13. [20]Scirica BM. The Safety of Dipeptidyl Peptidase 4 Inhibitors and the Risk for Heart Failure. JAMA Cardiol. 2016; 1: 123– 125. 27437882
  14. [22]From AM, Scott CG and Chen HH. The development of heart failure in patients with diabetes mellitus and pre-clinical diastolic dysfunction a population-based study. J Am Coll Cardiol. 2010; 55: 300– 305. 20117433 PMC3878075

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Authors
Berg, D. D., Wiviott, S. D., Scirica, B. M., Gurmu, Y., Mosenzon, O., Murphy, S. A., Bhatt, D. L., Leiter, L. A., McGuire, D. K., Wilding, J. P. H., Johanson, P., Johansson, P. A., Langkilde, A. M., Raz, I., Braunwald, E., & Sabatine, M. S.
Affiliations
  • Brigham and Women's Hospital (US)
  • Hadassah Medical Center (IL)
  • St. Michael's Hospital (CA)
  • The University of Texas Southwestern Medical Center (US)
  • University of Liverpool (GB)
  • AstraZeneca (Sweden) (SE)
  • TIMI Study Group, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (D.D.B., S.D.W., B.M.S., Y.G., S.A.M., D.L.B., E.B., M.S.S.).
Venue
Circulation
Published
2019-11-05
Volume
140
Issue
19
Pages
1569-1577
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
OpenAlex
W2970346174
Cited by
154
References
8
Citations by year
2026: 20 · 2025: 16 · 2024: 16 · 2023: 18 · 2022: 24 · 2021: 32 · 2020: 25 · 2019: 2
FWCI
16.83
Type
journal article
Language
en
Open access
Locations
  • Circulation (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Heart, Lung, and Blood Institute (T32HL007604)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Failure Treatment and Management
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Function and Risk Factors
Keywords
heart failure risk stratification, SGLT2 inhibitors, dapagliflozin, type 2 diabetes, heart failure hospitalization, clinical risk score, risk prediction model, atrial fibrillation, coronary artery disease, estimated glomerular filtration rate, albuminuria, SAVOR-TIMI 53, DECLARE-TIMI 58
MeSH terms
Clinical Decision-Making, Sodium-Glucose Transporter 2 Inhibitors, Adamantane, Aged, Benzhydryl Compounds, Decision Support Techniques, Diabetes Mellitus, Type 2, Dipeptides, Female, Glucosides, Health Status, Heart Failure, Humans, Male, Middle Aged, Predictive Value of Tests, Risk Factors, Time Factors, Reproducibility of Results, Randomized Controlled Trials as Topic, Treatment Outcome, Risk Assessment, Patient Selection, Dipeptidyl-Peptidase IV Inhibitors, Diabetic Cardiomyopathies

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