Skip to main content
Log in

Do Cardioselective β-Adrenoceptor Antagonists Reduce Mortality in Diabetic Patients with Congestive Heart Failure?

  • Original Research Article
  • Published:
American Journal of Cardiovascular Drugs Aims and scope Submit manuscript

Abstract

Background

The relative benefits of cardioselective β-adrenoceptor antagonists (CSB) among patients with congestive heart failure (CHF) and diabetes mellitus are not firmly established.

Objective

To determine whether diabetic patients with CHF accrue the same mortality benefit from CSB therapy as non-diabetic patients.

Methods

Between October 1999 and November 2000 consecutive patients with CHF at the Veteran’s Affairs Medical Center in Indianapolis, IN, USA, were enrolled in a randomized controlled trial and prospectively followed for 5 years. Disease severity and CHF-specific functional status were obtained from patients at baseline. Medical records were accessed for data regarding co-morbidities, medications, and mortality. Propensity-score analysis was used to balance co-variates because of the observational nature of CSB use, given this was a post hoc analysis. A multivariate Cox proportional hazards model was used to compare survival between diabetic and non-diabetic patients stratified by whether they were or were not receiving CSB therapy.

Results

Of the 412 evaluable patients, 222 (54%) had diabetes and 212 (51%) were taking a CSB. At 5-year follow-up, 186 (45%) patients had died. In the multivariate analysis, using propensity scores to balance covariates, CSB therapy was an independent predictor of survival in patients without diabetes (hazard ratio 0.60; p =0.054) only.

Conclusions

These results extend prior observations that patients with diabetes and CHF may not accrue the same mortality benefit from CSB therapy as patients without diabetes, and warrant further prospective investigation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Table I
Table II
Table III
Fig. 1

Similar content being viewed by others

References

  1. Kamalesh M, Nair G. Increasing prevalence of diabetes among patients with congestive heart failure. Int J Cardiol 2005; 104(1): 77–80.

    Article  PubMed  Google Scholar 

  2. Adams Jr KF, Fonarow GC, Emerman CL, et al. ADHERE Scientific Advisory Committee and Investigators. Characteristics and outcomes of patients hospitalized for heart failure in the United States: rationale, design, and preliminary observations from the first 100 000 cases in the Acute Decompensated Heart Failure National Registry (ADHERE). Am Heart J 2005; 149(2): 209–16.

    Article  PubMed  Google Scholar 

  3. Hunt SA, Abraham WT, Chin MH, et al. American College of Cardiology; American Heart Association Task Force on Practice Guidelines; American College of Chest Physicians; International Society for Heart and Lung Transplantation; Heart Rhythm Society. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult. J Am Coll Cardiol 2005; 46(6): 1116–43.

    Article  Google Scholar 

  4. Satwani S, Dec GW, Narula J. Beta-adrenergic blockers in heart failure: review of mechanisms of action and clinical outcomes. J Cardiovasc Pharmacol Ther 2004; 9: 243–55.

    Article  PubMed  CAS  Google Scholar 

  5. Deedwania PC, Giles TD, Klibaner M, et al. MERIT-HF Study Group. Efficacy, safety and tolerability of metoprolol CR/XL in patients with diabetes and chronic heart failure: experiences from MERIT-HF. Am Heart J 2005; 149(1): 159–67.

    Article  PubMed  CAS  Google Scholar 

  6. CIBIS-II Investigators and Committees. The cardiac insufficiency and bisoprolol study II (CIBIS II): a randomized trial. Lancet 1999; 353: 9–13

    Article  Google Scholar 

  7. MERIT-HF Study Group. Effects of metoprolol CR/XL in chronic heart failure. Metoprolol CR/XL Randomized Intervention Trial in congestive Heart Failure. (MERIT-HF). Lancet 1999; 353: 2001–7

    Article  Google Scholar 

  8. Mohacsi P, Fowler MB, Krum H, et al. Should physicians avoid the use of beta blockers in patients with heart failure who have diabetes? Results of the COPERNICUS Study [abstract no. 3551]. Circulation 2001; 104:II–754.

    Google Scholar 

  9. Bell DS, Lukas MA, Holdbrook FK, et al. The effect of carvedilol on mortality risk in heart failure patients with diabetes: results of a meta-analysis. Curr Med Res Opin 2006; 22: 287–96.

    Article  PubMed  CAS  Google Scholar 

  10. Subramanian U, Fihn S, Weinberger M, et al. A controlled trial of including symptom data in computer-based care suggestions for managing patients with chronic heart failure. Am J Med 2004; 116: 375–80.

    Article  PubMed  Google Scholar 

  11. Subramanian U, Fihn S, Weinberger M, et al. Diagnostic challenges defining chronic heart failure when using echocardiograms. Am J Cardiol 2003; 91(8): 1015–7.

    Article  PubMed  Google Scholar 

  12. Martin DK. Making the connection: the VA-Regenstrief project. MD Comput 1992; 9: 91–6.

    PubMed  CAS  Google Scholar 

  13. Fisher SG, Weber L, Goldberg J, et al. Mortality ascertainment in veteran population: alternatives to the National Death Index. Am J Epidemiol 1995; 141: 242–50.

    PubMed  CAS  Google Scholar 

  14. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40: 373–83.

    Article  PubMed  CAS  Google Scholar 

  15. Polanczyk CA, Rohde LE, Philbin EA, et al. A new casemix adjustment index for hospital mortality among patients with congestive heart failure. Med Care 1998; 36: 1489–99.

    Article  PubMed  CAS  Google Scholar 

  16. Iezzoni LI, Ash AS, Shwartz M, et al. Predicting who dies depends on how severity is measured: implications for evaluating patient outcomes. Ann Intern Med 1995; 123: 763–70.

    PubMed  CAS  Google Scholar 

  17. Pine M, Norusis M, Jones B, et al. Predictions of hospital mortality rates: a comparison of data sources. Ann Intern Med 1997; 126: 347–54.

    PubMed  CAS  Google Scholar 

  18. Tierney WM, Takesue BY, Vargo DL, et al. Using electronic medical records to predict mortality in primary care patients with heart disease: prognostic power and pathophysiologic implications. J Gen Intern Med 1996; 11: 83–91.

    Article  PubMed  CAS  Google Scholar 

  19. Freedland KE, Carney RM. Psychosocial considerations in elderly patients with heart failure. Clin Geriatr Med 2000; 16: 649–61.

    Article  PubMed  CAS  Google Scholar 

  20. Goodlin SJ, Hauptman PJ, Arnold R, et al. Consensus statement conference on palliative and supportive care in advanced heart failure. J Cardiac Fail 2004; 10(3): 200–9.

    Article  Google Scholar 

  21. Gavazzi A, De Maria R, Parolini M, et al. Alcohol abuse and dilated cardiomyopathy in men. Am J Cardiol 2000; 85: 1114–8.

    Article  PubMed  CAS  Google Scholar 

  22. Carney RM, Freedland KE, Miller GE, et al. Depression as a risk factor for cardiac mortality and morbidity: a review of potential mechanisms. J Psychosom Res 2002; 53: 897–902.

    Article  PubMed  Google Scholar 

  23. Murberg TA, Bru E, Svebak S, et al. Depressed mood and subjective health symptoms as predictors of mortality in patients with congestive heart failure: a two-year follow- up study. Int J Psychiatry Med 1999; 29: 311–26.

    Article  PubMed  CAS  Google Scholar 

  24. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992; 45: 613–9.

    Article  PubMed  CAS  Google Scholar 

  25. Bouvy ML, Heerdink ER, Leufkens HG, et al. Predicting mortality in patients with heart failure: a pragmatic approach. Heart 2003; 89: 605–9.

    Article  PubMed  CAS  Google Scholar 

  26. Tierney WM, Brunt M, Kesterson J, et al. Quantifying risk of adverse clinical events with one set of vital signs among primary care patients with hypertension. Ann Fam Med 2004; 2: 209–17.

    Article  PubMed  Google Scholar 

  27. Ware J. SF-36 Physical and mental health summary scale: a user’s manual. Boston (MA): Health Assessment Lab, New England Medical Center, 1994.

    Google Scholar 

  28. Guyatt G. Measurement of health-related quality of life in heart failure. J Am Coll Cardiol 1993; 22: 185–91A.

    Article  Google Scholar 

  29. Green CP, Porter CB, Bresnahan DR, et al. Development and evaluation of the Kansas City Cardiomyopathy Questionnaire: a new health status measure for heart failure. J Am Coll Cardiol 2000; 35: 1245–55.

    Article  PubMed  CAS  Google Scholar 

  30. D’Agostino Jr RB. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med 1998; 17: 2265–81.

    Article  PubMed  Google Scholar 

  31. Subramanian U, Eckert G, Yeung A, et al. A single health status question has important prognostic value among outpatients with chronic heart failure. J Clin Epidemiol 2007; 60(8): 803–11.

    Article  PubMed  Google Scholar 

  32. Haas SJ, Vos T, Gilbert RE, et al. Are beta blockers as efficacious in patients with diabetes as in patients without diabetes who have chronic heart failure? A meta-analysis of large scale clinical trials. Am Heart J 2003; 146: 848–53.

    Article  PubMed  CAS  Google Scholar 

  33. Zacà V, Rastogi S, Mishra S, et al. Atenolol is inferior to metoprolol in improving left ventricular function and preventing ventricular remodeling in dogs with heart failure. Cardiology 2009; 112: 294–302.

    Article  PubMed  Google Scholar 

  34. Nishio Y, Kashiwagi A, Kida Y, et al. Deficiency of cardiac beta-adrenergic receptor in streptozocin-induced diabetic rats. Diabetes 1988; 37: 1181–7.

    Article  PubMed  CAS  Google Scholar 

  35. Gotzsche O. The adrenergic beta-receptor adenylate cyclase system in heart and lymphocytes from streptozotocin-diabetic rats: in vivo and in vitro evidence for a desensitized myocardial beta-receptor. Diabetes 1983; 12: 1110–6.

    Article  Google Scholar 

  36. Cros GH, Chanez PO, Michel A, et al. Cardiac beta-adrenergic receptors in diabetic rats: alteration of guanyl nucleotide regulation. J Pharmacol 1986; 17: 595–600.

    PubMed  CAS  Google Scholar 

  37. Lowes BD, Baker ML, Blaxall BC. Gene expression profile of the recovering human heart. Eur Heart J 2007; 28(5): 522–4.

    Article  PubMed  CAS  Google Scholar 

  38. Dulin BR, Haas SJ, Abraham WT, et al. Do elderly systolic heart failure patients benefit from beta blockers to the same extent as the non-elderly? Meta-analysis of >12 000 patients in large-scale clinical trials. Am J Cardiol 2005; 95: 896–8.

    Article  PubMed  CAS  Google Scholar 

  39. Bristow MR. Changes in myocardial and vascular receptors in heart failure. J Am Coll Cardiol 1993; 4: 61–71A.

    Article  Google Scholar 

  40. Yoshikawa T, Port JD, Asano K, et al. Cardiac adrenergic receptor effects of carvedilol. Eur Heart J 1996; 17 Suppl. B: 8–16.

    Article  PubMed  CAS  Google Scholar 

  41. Jugdutt BI, Joljart MJ, Khan MI. Rate of collagen deposition during healing and ventricular remodeling after myocardial infarction in rat and dog models. Circulation 1996; 94: 94–101.

    Article  PubMed  CAS  Google Scholar 

  42. Doering CW, Jalil JE, Janicki JS, et al. Collagen network remodeling and diastolic stiffness of the rat left ventricle with pressure overload hypertrophy. Cardiovasc Res 1988; 22: 686–95.

    Article  PubMed  CAS  Google Scholar 

  43. Wei S, Chow LT, Sanderson JE. Effect of carvedilol in comparison with metoprolol on myocardial collagen post infarction. J Am Coll Cardiol 2000; 36: 276–81.

    Article  PubMed  CAS  Google Scholar 

  44. Freemantle N, Cleland J, Young P, et al. Beta blockade after myocardial infarction: systematic review and meta regression analysis. BMJ 1999; 318: 1730–7.

    Article  PubMed  CAS  Google Scholar 

  45. Brophy JM, Joseph L, Rouleau JL. Beta-blockers in congestive heart failure: a Bayesian meta-analysis. Ann Intern Med 2001; 134: 550–60.

    PubMed  CAS  Google Scholar 

  46. Luellen JK, Shadish WR, Clark MH. Propensity scores: an introduction and experimental test. Eval Rev 2005; 29: 530–58.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors have no conflicts of interest that are directly relevant to the content of this study. No sources of funding were used to assist in the preparation of this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masoor Kamalesh.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Subramanian, U., Kamalesh, M., Temkit, M. et al. Do Cardioselective β-Adrenoceptor Antagonists Reduce Mortality in Diabetic Patients with Congestive Heart Failure?. Am J Cardiovasc Drugs 9, 231–240 (2009). https://doi.org/10.2165/1006180-000000000-00000

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2165/1006180-000000000-00000

Keywords

Navigation