Prevalence and Prognostic Impact of Comorbidities in Heart Failure Patients With Implantable Cardioverter-Defibrillator

Christian Bruch;* Chahrebanu Bruch; J?gen Sindermann; G?ter Breithardt; Rainer Gradaus

Europace.  2007;9(8):681-686.  ?2007 Oxford University Press
Posted 09/11/2007

Abstract and Introduction

Abstract

Aims This study assessed the prevalence and the prognostic impact of comorbidities in heart failure patients with implantatable cardioverter?defibrillator (ICD).
Methods and results We prospectively enrolled 146 patients with chronic heart failure, an ICD, and systolic dysfunction (mean ejection fraction 29 ? 10%). Cardiac death was chosen as the primary endpoint. Death or appropriate ICD therapy, i.e. antitachycardia pacing/shock due to sustained ventricular tachycardia or ventricular fibrillation, was chosen as the secondary endpoint. Seventy-five patients (52%) had chronic kidney disease (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m[2]), 39 patients (27%) were anaemic, and 34 patients (23%) had diabetes mellitus. During a follow-up of 663 ? 400 days, 22 patients (15%) died, and 41 patients (28%) received an appropriate ICD therapy. By multivariate Cox analysis, independent predictors of cardiac death were chronic kidney disease, age, and NYHA functional class. Death/appropriate ICD therapy were independently predicted by chronic kidney disease and QRS duration. In the presence of chronic kidney disease, outcome was significantly worse when compared with the absence (event-free survival rate 51 vs. 76%, P < 0.001).
Conclusion In heart failure patients with an ICD, comorbidities are frequent but only the presence of chronic kidney disease is independently associated with increased morbidity and mortality.

Introduction

Despite recent advances in the medical management of patients with chronic heart failure (CHF), morbidity and mortality remain high.[1] Different primary and secondary prevention trials have confirmed that implantable cardioverter?defibrillators (ICDs) may effectively reduce the risk of sudden cardiac death, resulting in an improved prognosis.[2?6] However, in ICD recipients with CHF, annual mortality rates still range ~10%,[6] and ICD discharges and re-hospitalizations due to CHF are indicative of a significant morbidity.[7] Thus, risk stratification remains of particular importance in this subpopulation.

Several authors have attempted to identify risks that predict outcome in such patients, including NYHA functional class,[8] ejection fraction (EF),[9] and QRS duration derived from the 12-lead ECG.[10] Recent evidence suggests that comorbidities such as kidney disease, anaemia, and diabetes mellitus have a pivotal role in determining the prognosis of patients with different cardiovascular disorders.[11?13] Surprisingly, data on the prevalence and the prognostic impact of comorbidities in ICD recipients with underlying CHF are scarce.[14?16]

This prospective study was designed to assess the prevalence and the prognostic impact of kidney disease, anaemia, and diabetes mellitus in CHF patients with ICD and to compare it against traditional markers such as NYHA functional class, EF, and QRS duration.

Methods

Study Patients

The study patients were selected from 273 patients who were followed after receiving ICDs between March 2002 and September 2004 in our institution (Hospital of the University of M?ster). Of those patients, 158 subjects fulfilled the inclusion criteria comprising a history of CHF according to published criteria,[17] left ventricular EF <50% as detected by echocardiography, and clinical stability as well as stable creatinine values after at least 2 months on standard medical therapy.[17] Patients with congenital heart disease (n = 4), malignancy (n = 2), and severe heart valve disease (n = 6) were excluded. Using these selection criteria, a total of 146 subjects formed the final study cohort. Of these patients, 88 subjects (60%) received ICDs for secondary prevention and 58 (40%) for primary prevention of sudden cardiac death. In 33 patients (23%), biventricular devices for cardiac resynchronization therapy were implanted. In patients who received ICDs for primary prevention, the programmed detection zones were >170 bpm for ventricular tachycardia and >200 bpm for ventricular fibrillation. In patients who received ICDs for secondary prevention, the detection zone for ventricular tachycardia was programmed 20?30 bpm below the frequency of the detected/documented ventricular tachycardia.

All implanted devices were capable of storing intracardiac electrograms, and all patients had anti-tachycardia pacing capabilities in combination with cardioversion/defibrillation treatment features. All treated episodes were classified as inappropriate or appropriate by one experienced cardiologist (R.G.), who had no knowledge of the clinical data.

The study complies with the Declaration of Helsinki, and our research protocol was in agreement with the regulations provided by the Institutional Review Board. Informed consent of all study subjects was obtained.

Electrocardiogram Analysis

The QRS duration for each patient was derived as a mean of at least 3 QRS complexes examined in a 12-lead ECG. Left bundle branch block was diagnosed on the basis of QRS duration >120 ms, absent Q waves and wide slurred R waves in V5 and V6, and monophasic QS or rS waves in leads V1 and V2.

Laboratory Values

As a measure of renal function, the baseline glomerular filtration was estimated (eGFR) using the abbreviated Modification of Diet in Renal Disease (MDRD) Study Equation:[18] eGFR (mL/min/1.73 m[2] of body surface area) = 186 x (serum creatinine in mg/dL)[?1.154] x (age in years)[?0.203] x 0.742 in female subjects. Patients with an eGFR <60 mL/min/1.73 m[2] were considered as having chronic kidney disease (CKD).[19] CKD was further subdivided into moderate CKD (stage III, eGFR 30?60 mL/min/1.73 m[2]), severe CKD (stage IV, eGFR 15?30 mL/min/1.73 m[2]), and end-stage CKD (stage V, eGFR <15 mL/min/1.73 m[2).19]

Serum creatinine, electrolytes, haemoglobin, and glucose values were determined by standard methods. Diabetes mellitus was diagnosed according to established criteria.[20] Anaemia was defined as a haemoglobin <12 g/dL in women and <13 g/dL in men.[21]

Study Schedule and Statistical Analysis

The follow-up period started with the first ICD interrogation at a mean interval of 265 ? 117 days after implantation of the device. The index venous blood sample was taken at the day of the first ICD interrogation. During follow-up, patients were seen regularly on an outpatient basis in 3?6 months intervals, and the device was interrogated for treated episodes at each visit. Detailed follow-up information was also obtained by telephone contact with patients or their physicians.

Cardiac death was chosen as the primary endpoint. Death or appropriate ICD therapy, i.e. anti-tachycardia pacing/shock due to ventricular tachycardia or ventricular fibrillation, was chosen as the combined secondary endpoint.

Numerical values were expressed as mean ? SD. Continuous variables were compared between groups using an unpaired t-test (for normally distributed variables) or Mann?Whitney U test (for non-normally distributed variables). To compare categorical variables, χ[2] analysis was used. Clinical, ECG, and echo variables were evaluated for the study endpoints using Cox proportional hazard models. Receiver operating characteristic curves were generated to define the cut-off values for variables with a significant association with the endpoint (P < 0.05). Multivariable regression analysis was performed to identify the independent predictors of outcome. Event-free survival was analysed by the Kaplan?Meier method, and survival curves were compared by the log-rank test. A P-value of <0.05 was considered significant.

Results

The baseline characteristics of the study population are presented in Table 1 . The cause of CHF was ischaemic cardiomyopathy in 62% of the patients and non-ischaemic cardiomyopathy in the remaining 38%. The vast majority of patients were treated with diuretics (89%), ß-blockers (92%) and angiotensin-converting enzyme inhibitors (ACE-Is) or angiotensin receptor blockers (ARBs) (96%). In our study cohort, a wide spectrum of renal function was present (eGFRs ranging from 19.0 to 98.8 mL/min/1.73 m[2], mean 58.6 ? 18.0 mL/min/1.73 m[2]). A total of 75 patients (52%) were found to have CKD, of whom 6 patients had severe CKD (mean eGFR 24.9 ? 3.8 mL/min/1.73 m[2]) and 69 patients had moderate CKD (mean eGFR 46.5 ? 8.8 mL/min/1.73 m[2]). No patient required haemodialysis due to end-stage CKD. In the entire cohort, 39 patients (27%) were anaemic and 34 patients (23%) had diabetes mellitus.

During a follow-up of 663 ? 400 days, 22 patients (15%) suffered of cardiac death and 41 patients (28%) received an appropriate ICD therapy. The total number of anti-tachycardia treated episodes were 678, and the total number of shocks were 53. Four patients underwent anti-tachycardia pacing with subsequent shock due to accelerated ventricular tachycardia. Five patients, who underwent appropriate ICD shocks, died due to pump failure subsequently. Thus, a total of 58 patients (40%) reached the secondary endpoint of death/appropriate ICD therapy.

Survivors and non-survivors did not differ significantly with respect to sex, aetiology of CHF, frequency of a biventricular ICD, resting heart rate, EF, blood pressure, serum electrolytes, serum haemoglobin, or drug therapy. The average doses of furosemide did not differ between survivors and non-survivors (60 ? 33 vs. 56 ? 43 mg/day, P = ns). There was a trend towards longer QRS duration in non-survivors, but the difference was not statistically significant. Non-survivors were older and in a poorer NYHA functional class than survivors. In such patients, serum creatinine was higher, the eGFR was lower, and CKD was more frequent in comparison with survivors. Both groups did not differ with respect to the prevalence of anaemia or diabetes mellitus.

When the analysis was conducted for patients, who reached the combined secondary endpoint, there were significant differences with respect to QRS duration (155 ? 38 vs. 137 ? 18 ms, P = 0.004), eGFR (53.6 ? 16.9 vs. 61.7 ? 10.9 mL/min/1.73 m[2], P = 0.038), and the presence of CKD (62 vs. 44%, P = 0.04). Other clinical variables did not differ significantly between subjects with or without death/appropriate ICD therapy.

Predictors of Prognosis and Survival Analysis

On univariate Cox analysis, age, NYHA functional class, the eGFR, and the presence of CKD were significantly associated with cardiac death ( Table 2 ). By multivariate analysis, independent prognostic predictors were age (hazard ratio (HR): 1.07, 95% CI 1.02?1.13, P = 0.009), NYHA functional class (HR: 8.10, 95% CI 1.34?49.2, P = 0.023), and CKD (HR: 3.55, 95% CI 1.03?12.2, P = 0.045).

In the presence of CKD, the outcome was markedly poorer when compared with the absence (event-free survival rate 51 vs. 76%, P < 0.001) (Figure 1). The prognosis was also markedly worse in patients >64 years (cut-off value derived from ROC analysis) (n = 63) in comparison with those ≤64 years (n = 83), with an event-free survival rate of 22 vs. 88% (P < 0.001) (Figure 2). Likewise, in patients who were in NYHA class III/IV (n = 95), the outcome was markedly poorer as compared with those in NYHA class I/II (n = 51), with an event-free survival rate of 47 vs. 97% (P = 0.001) (Figure 3). To better stratify the individual risk for cardiac death, we constructed a risk model based on three independent predictors (presence of CKD, age >64 years, and NYHA class III/IV) derived from the multivariate analysis. A combination of these variables increased the predictive accuracy, as groups with very low, low, intermediate, and high risk could be identified with event-free survival of 100, 97, 34, and 15%, respectively (overall P < 0.001) (Figure 4). Notably, in the absence of any risk factor or the presence of only one risk factor, outcome was favourable (no and only one cardiac death during follow-up, respectively). In contrast, in the presence of two or three risk factors, the prognosis was poor (8 and 13 deaths, respectively).

Figure 1. 

Event-free survival in subgroups of patients according to the presence or absence of chronic kidney disease. Time to first event analysis by the Kaplan?Meier method.

     

Figure 2. 

Outcome in subgroups of patients according to their age. The event-free survival in patients aged >64 years was significantly worse in comparison with those aged ≤64 years.

     

Figure 3. 

Outcome in subgroups of patients according to their NYHA functional class. Subjects in NYHA functional class III/IV had a significantly worse prognosis in comparison with those in NYHA functional class I/II.

     

On univariate analysis, QRS duration, eGFR, and the presence of CKD were significantly associated with the combined secondary endpoint (death/appropriate ICD therapy). By multivariate analysis, independent prognostic predictors were CKD (HR: 1.73, 95% CI 1.004?2.99, P = 0.046) and QRS duration (HR: 1.008, 95% CI 1.001?1.015, P = 0.049). When death/appropriate ICD therapy was considered as an event, outcome was poorer in the presence of CKD (event-free survival rate of 25 vs. 39%, log rank: 4.00, P = 0.045). In patients with QRS duration >138 ms (cut-off value derived from ROC analysis), there was a trend towards a less-favourable outcome than in those with QRS duration ≤138. However, Kaplan?Meier analysis yielded no statistically significant difference (event-free survival rate of 28 vs. 51%, P = 0.18 by log-rank testing).

Discussion

This study addresses the prevalence and the prognostic impact of comorbidities, namely CKD, diabetes mellitus, and anaemia in CHF patients who received an ICD for primary or secondary prevention of sudden cardiac death. In this patient population, CKD, anaemia, and diabetes mellitus were frequent, but only CKD was independently associated with increased morbidity and mortality. Notably, CKD as defined by a reduction in the eGFR <60 mL/min/m[2] was a stronger predictor of cardiac death than established markers such as EF and QRS duration. The presence of CKD was also independently associated with the combined secondary endpoint consisting of death or appropriate ICD therapies.

Risk Stratification in CHF Patients Treated with an ICD

In patients with CHF, indications for ICD implantation have greatly expanded in the recent years. However, despite this proven benefit, the prognosis of CHF patients with an ICD remains severe, with a mortality rate of ~15% during an average follow-up of 20 months in a recent large multi-centre trial.[5] In many of such patients, ICD treatment is associated with re-hospitalizations due to worsening CHF and multiple ICD discharges indicating excess morbidity,[7] so that an appropriate risk stratification remains of particular importance.

In such patients, prognostic factors include the clinical status (i.e. NYHA functional class), EF, QRS duration and, in a small series from our institution, a restrictive mitral filling pattern.[7?10,22] Only few studies have addressed the prognostic impact of CKD, anaemia, or diabetes mellitus in this patient population, which is in contrast to the pivotal prognostic role of those comorbidities in other CHF populations.[11?13,23,24]

To identify the prevalence and prognostic impact of comorbidities in patients with CHF and/or ICD,[24,25] some previous analyses focussed on diagnostic and procedural codes using International Classification of Diseases (ICD-9/10) coding algorithms. However, it has been shown that comorbidities tend to be under-reported in administrative data when compared with patient chart data.[26] Using ICD-9 codes, Eckardt et al.[25] assessed the prevalence and prognostic impact of renal insufficiency in 741 ICD recipients. In this large retrospective series, patients with renal insufficiency had a significantly higher mortality, a higher rate of health care resource utilization, and more heart failure admissions when compared with patients with normal renal function. In another retrospective analysis on 469 consecutive ICD recipients, age >80 years, NYHA functional class III/IV, history of atrial fibrillation, and a serum creatinine >1.8 mg/dL independently predicted a high risk of early mortality after ICD implantation.[14] In a smaller study by Wase et al.,[15] the prognostic impact of CKD was studied in 95 patients who underwent ICD implantation after fulfilling MADIT or AVID criteria. In this analysis, the presence of CKD and end-stage renal disease were related to overall poor survival, arrhythmic death, and higher defibrillation thresholds.

In our study, age >64 years, NYHA class III/IV, and the presence of CKD also independently predicted cardiac death, confirming those previous findings. However, we were able to better stratify the individual risk by constructing a risk model based on those independent prognostic predictors (Figure 4). Notably, in the absence of any or the presence of only one risk factor, outcome was favourable. In contrast, the presence of two or three risk factors indicated a poor prognosis.

Figure 4. 

Outcome in subgroups of patients according to the presence of risk factors (presence of chronic kidney disease, age >64 years, and NYHA class III/IV). Note the favourable prognosis in the absence of any or presence of 1 risk factor (RF). Outcome is poor in the presence of 2 or 3 RFs.

     

In our study, the presence of CKD was also independently associated with the combined secondary endpoint (death/appropriate ICD therapy), which we considered as a marker of mortality and morbidity. Our study is the first to use the MDRD formula for assessment and classification of CKD, which is in agreement with current recommendations.[19] In contrast to previous analyses, the vast majority of our patients were under ACE-I/ARB and ß-blocker treatment ( Table 1 ). Thus, the prognostic impact of CKD could be studied in a representative cohort receiving contemporary therapy for CHF.[17] Notably, in our ICD cohort, CKD was a stronger predictor of adverse cardiac events than established markers such as QRS duration or EF?a finding that is in agreement with results reported in other CHF populations.[11,27] In our view, future research should clarify whether the benefit gained from ICD implantation is comparable in patients with vs. without CKD.

To the best of our knowledge, our study is the first to systematically analyse the prevalence and prognostic role of anaemia in a CHF cohort treated with an ICD. In our population, 27% of the patients were anaemic, which is in line with the prevalence of anaemia that has been found in other CHF cohorts.[13] However, although non-survivors had a lower haemoglobin level than survivors ( Table 1 ), the presence of anaemia was not associated with a poor prognosis in our analysis. This is in contrast to the adverse prognostic impact of anaemia reported in other CHF populations[24,28] and may be attributable to the small study sample or the relatively young age of our CHF cohort.

In our analysis, we found no relevant prognostic impact of diabetes, which is in agreement with the results obtained by Wittenberg et al.[16] In a substudy of the MADIT II trial, these investigators compared the efficacy of ICD placement on survival in 489 diabetics against 743 non-diabetics. In their analysis, the hazard ratio for the risk of death in patients treated with an ICD was similar in diabetics (HR: 0.71, 95% CI 0.38?0.98) and non-diabetics (HR 0.71, 95% CI 0.49?1.05). When the outcome was compared, diabetic patients had a 24% greater adjusted risk for death compared with non-diabetics. However, log-rank analysis yielded no statistically significant difference between the diabetic and the non-diabetic group (P = 0.210), indicating that diabetes per se did not independently predict outcome in their patient population.

Study Limitations

Because patients with severe valvular disease or congenital heart disease were excluded, the results of our study should not be extrapolated to these patient populations. In our study cohort, we did not determine the causes for CKD or anaemia, and we did not measure urinary protein loss, kidney size, iron binding capacity, or neurohormonal markers such as ANP, BNP, or NT-proBNP. We did not consider any serial measurements of serum creatinine, eGFR, haemoglobin, or electrolytes, which may have added relevant information. We did not analyse the impact of the pacing mode or the percentage of right ventricular pacing, which may have impacted on the results. Finally, comparatively our study population was rather small, and we reported only a single-centre experience. Thus, our results should be prospectively confirmed in a multi-centre approach, using larger sample sizes and longer follow-up periods.

Conclusions

In patients with CHF and an ICD, CKD, anaemia, and diabetes mellitus are frequent but only the presence of CKD independently predicted morbidity and mortality. Assessment of renal function using the eGFR may be a useful adjunct in the diagnostic work up and risk stratification of such patients.


Table 2. Univariate Cox Regression Analysis: Predictors of Cardiac Death


Table 2: Univariate Cox Regression Analysis: Predictors of Cardiac Death

 



References

  1. Packer M, Coats AJ, Fowler MB, Katus HA, Krum H, Mohacsi P et al. Effect of carvedilol on survival in severe chronic heart failure. N Engl J Med 2001;344:1651?8.
  2. Buxton AE, Lee KL, Fisher JD, Josephson ME, Prystowsky EN, Hafley G. A randomized study of the prevention of sudden death in patients with coronary artery disease. N Engl J Med 1999;341:1882?90.
  3. Moss AJ, Hall WJ, Cannom DS, Daubert JP, Higgins SL, Klein H et al. Improved survival with an implanted defibrillator in patients with coronary disease at high risk for ventricular arrhythmia. N Engl J Med 1996;335:1933?40.
  4. The Antiarrhythmic Versus Implantable Defibrillators (AVID) Investigators. A comparison of antiarrhythmic drug therapy with implantable defibrillators in patients resuscitated from near-fatal ventricular arrhythmias. N Engl J Med 1997;337:1576?83.
  5. Moss AJ, Zareba W, Hall WJ, Klein H, Wilber DJ, Cannom DS et al. Multicenter Automatic Defibrillator Implantation Trial II Investigators. Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. N Engl J Med 2002;346:877?83.
  6. Bardy GH, Lee KL, Mark DB, Poole JE, Packer DL, Boineau R et al. Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) Investigators. Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure. N Engl J Med 2005;352:225?37.
  7. Buxton AE, Sweeney MO, Wathen MS, Josephson ME, Otterness MF, Hogan-Miller E et al. QRS duration does not predict occurrence of ventricular tachyarrhythmias in patients with implanted cardioverterdefibrillators. J Am Coll Cardiol 2005;46:310?6.
  8. Whang W, Mittleman MA, Rich DQ, Wang PJ, Ruskin JN, Tofler GH et al. Heart failure and the risk of shocks in patients with implantable cardioverter defibrillators: results from the Triggers Of Ventricular Arrhythmias (TOVA) study. Circulation 2004;109:1386?91.
  9. Grimm W, Flores BT, Marchlinski FE. Shock occurrence and survival in 241 patients with implantable cardioverter-defibrillator therapy. Circulation 1993;87:1880?8.
  10. Bode-Schnurbus L, Bocker D, Block M, Gradaus R, Heinecke A, Breithardt G et al. QRS duration: a simple marker for predicting cardiac mortality in ICD patients with heart failure. Heart 2003;89:1157?62.
  11. Anavekar NS, McMurray JJ, Velazquez EJ, Solomon SD, Kober L, Rouleau JL et al. Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction. N Engl J Med 2004;351:1285?95.
  12. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296?305.
  13. Ezekowitz JA,McAlister FA, Armstrong PW. Anemia is common in heart failure and is associated with poor outcomes: insights from a cohort of 12 065 patients with new-onset heart failure. Circulation 2003;107:223?5.
  14. Parkash R, Stevenson WG, Epstein LM, Maisel WH. Predicting early mortality after implantable defibrillator implantation: a clinical risk score for optimal patient selection. Am Heart J 2006;151:397?403.
  15. Wase A, Basit A, Nazir R, Jamal A, Shah S, Khan T et al. Impact of chronic kidney disease upon survival among implantable cardioverterdefibrillator recipients. J Interv Card Electrophysiol 2004;11:199?204.
  16. Wittenberg SM, Cook JR, Hall WJ, McNitt S, Zareba W, Moss AJ. Multicenter Automatic Defibrillator Implantation Trial. Comparison of efficacy of implanted cardioverter-defibrillator in patients with versus without diabetes mellitus. Am J Cardiol 2005;96:417?9.
  17. Swedberg K, Cleland J, Dargie H, Drexler H, Follath F, Komajda M et al. Guidelines for the diagnosis and treatment of chronic heart failure: executive summary (update 2005): The Task Force for the Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology. Eur Heart J 2005;26:1115?40.
  18. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999;130:461?70.
  19. National Kidney Foundation. Clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 2002;2(Suppl. 1):S46?7.
  20. The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 1997;20:1183?97.
  21. World Health Organisation. Nutritional anemias: report of a WHO scientific group. WHO Tech Rep Ser 1968;405:3?37.
  22. Bruch C, Gotzmann M, Sindermann J, Breithardt G, Wichter T, Gradaus R. Prognostic value of a restrictive mitral filling pattern in patients with systolic heart failure and an implantable cardioverter-defibrillator. Am J Cardiol 2006;97:676?80.
  23. Hillege HL, Nitsch D, Pfeffer MA, Swedberg K, McMurray JJ, Yusuf S et al. Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity (CHARM) Investigators. Renal function as a predictor of outcome in a broad spectrum of patients with heart failure. Circulation 2006;113:671?8.
  24. Luthi JC, Flanders WD, Burnier M, Burnand B, McClellan WM. Anemia and chronic kidney disease are associated with poor outcomes in heart failure patients. BMC Nephrol 2006;7:3.
  25. Eckart RE, Gula LJ, Reynolds MR, Shry EA, Maisel WH. Mortality following defibrillator implantation in patients with renal insufficiency. J Cardiovasc Electrophysiol 2006;17:940?3.
  26. Quan H, Parsons GA, Ghali WA. Validity of information derived from ICD-9-CCM administrative data. Med Care 2002;40:675?85.
  27. Hillege H, Girbes ARJ, de Kam PJ, Boomsma F, de Zeeuw D, Charlesworth A et al. Renal function, neurohormonal activation, and survival in patients with chronic heart failure. Circulation 2000;102: 203?10.
  28. Eckardt KU. Managing a fateful alliance: anaemia and cardiovascular outcomes. Nephrol Dial Transplant 2005;20(Suppl. 6):16?20.
Disclaimer

Conflict of interest: none declared

Reprint Address

* Correspondence author: Tel: +49 251 83 47684; fax: +49 251 83 45631. E-mail address: bruchc@uni-muenster.de


Christian Bruch,* Chahrebanu Bruch, J?gen Sindermann, G?ter Breithardt and Rainer Gradaus

Department of Cardiology and Angiology, Hospital of the University of M?ster, Albert-Schweitzer-Str.33, D-48129 M?ster, Germany