Skip Navigation

European Journal of Heart Failure 2008 10(12):1236-1245; doi:10.1016/j.ejheart.2008.09.008
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Störk, S.
Right arrow Articles by Angermann, C. E.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Störk, S.
Right arrow Articles by Angermann, C. E.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2008 European Society of Cardiology

Pharmacotherapy according to treatment guidelines is associated with lower mortality in a community-based sample of patients with chronic heart failure A prospective cohort study

Stefan Störka,*, Hans Werner Henseb, Claudia Zentgrafa, Iris Uebelackera, Roland Jahnsa, Georg Ertla and Christiane E. Angermanna

a Department of Internal Medicine I/Center for Cardiovascular Medicine, University of Würzburg Klinikstrasse 6-8, D-97070 Würzburg, Germany
b Institute of Epidemiology and Social Medicine, University of Münster Domagkstr. 3, D-48129 Münster, Germany

* Corresponding author. University of Würzburg, Department of Internal Medicine I/Center for Cardiovascular Medicine, Klinikstrasse 6-8, D-97070 Würzburg, Germany. Tel.: +49 931 201 36147; fax: +49 931 201 70380. E-mail address: stoerk_s{at}klinik.uni-wuerzburg.de (S. Störk)


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Role of funding source
 Conflicts of interest
 References
 
Background: The effectiveness of chronic heart failure (CHF) pharmacotherapy in unselected cohorts is unknown.

Aims: To estimate the association between quality of CHF pharmacotherapy and all-cause mortality risk.

Methods and results: In a prospective cohort study, 1054 unselected patients with CHF (61% with reduced and 39% with normal left ventricular ejection fraction (LVEF)) were consecutively enrolled. Quality of pharmacotherapy was assessed by calculating a guideline adherence indicator (GAI-3, range 0–100%) based on prescription of beta blockers, angiotensin converting enzyme inhibitors or angiotensin receptor II type-1 blockers, and mineralocorticoid receptor antagonists. Median follow-up in survivors was 595 days (100% complete). In patients with reduced LVEF the median GAI-3 was 67%, and inversely associated with age, CHF severity, and important comorbidities. Mortality rates in GAI-3 categories low/medium/high were 79/30/11 per 100 person-years. In multivariable Cox regression, high GAI-3 was independently predictive of lower mortality risk: hazard ratio (HR) 0.50 (95% confidence interval [CI] 0.32–0.74; P<0.001) vs low GAI-3. This association was also observed in subgroups of high age (HR 0.42, 95%CI 0.27–0.66; P<0.001) and women (HR 0.42, 95%CI 0.23–0.79; P=0.007).

Conclusions: In this community-based cohort with CHF, better implementation of pharmacotherapy was associated with better prognosis in patients with reduced LVEF, irrespective of age and sex.

Key Words: Chronic heart failure • Pharmacotherapy • Prognosis • Survival • Left ventricular function

Received March 20, 2008; Revised July 3, 2008; Accepted September 22, 2008


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 Role of funding source
 Conflicts of interest
 References
 
Beta blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor II type-1 blockers (ARB), and mineralocorticoid receptor (MR) blockers improve survival in patients with chronic heart failure (CHF) and reduced left ventricular ejection fraction (LVEF) [1-3]. Based on numerous randomised controlled trials, the guidelines for the treatment of CHF with reduced LVEF recommend the use of these substance classes depending on the NYHA functional status [1]. The degree of guideline implementation across Europe is still unsatisfactory, although more recent surveys have shown some progress [4-7]. According to the MAHLER study, superior guideline implementation was associated with reduced rehospitalisation rates in the following six months [8]. However, compared to MAHLER and the randomised trials on which the guidelines are based, patients with CHF both in the general population and population-based cohorts are older, more often female, of higher functional class, and they suffer from multiple comorbidities [1,9-16]. In such cohorts, information on the prognostic yield of guideline implementation is scarce [3,6,10,11], and it has been questioned whether the guidelines should be applied to these patients at all. In addition, up to 40% of patients with CHF have a normal LVEF. For this subgroup, no evidence-based treatment guidelines are available [1-3].

In order to assess the quality of CHF pharmacotherapy in the general population we recruited a consecutive community-based cohort of patients with CHF of any aetiology and severity. We hypothesized that many patients with CHF do not receive the drugs recommended by current guidelines due to drug contraindications, intolerance, or a variety of other reasons including advanced age. Three principal questions were addressed: a) how well are guidelines implemented in patients with reduced LVEF in general, and in subgroups of very old and female patients in particular? b) How does the quality of guideline implementation relate to disease outcome measured by all-cause death after adjustment for potential confounders, and how is this relation affected by age and sex? c) How are CHF patients with a normal LVEF treated in clinical practice, and to what extent do they benefit if managed according to guidelines for systolic CHF?


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 Role of funding source
 Conflicts of interest
 References
 
2.1. Study design, patients and measurements
Between June 2002 and December 2003, all patients presenting with CHF of any cause and severity at two Würzburg University Medical Hospitals were consecutively included (n=1054). Both centres offer unrestricted access to the general population for inpatient cardiac care and outpatient CHF assessment. Patients were identified using dedicated hospital software screening for ICD codes I11.0, I11.9, I13.2, I13.9, I25.5, I42.x, I50.x, I51.9, I97.1, and O90.3. Subjects were eligible regardless of their mode of admission. No exclusion criteria were specified, and all patients underwent an echocardiogram. LVEF was calculated using Simpson's biplane or monoplane method or the Teichholz formula or qualitative measurement (i.e., eyeballing) in 58%, 31%, and 11% of cases, respectively. Reduced LVEF was diagnosed below a cut-off value of 45% (n=641; 60.8% of the total cohort). CHF with normal LVEF was accepted if LVEF was >45% (n=413; 39.2% of the total cohort) in the presence of symptoms of heart failure and at least one of the following clinical signs: raised jugular venous pressure, peripheral oedema, third heart sound, pulmonary congestion (clinical examination or chest X-ray). Baseline laboratory parameters, medication at study entry and medical history were collected using standardised questionnaires. Survival status was ascertained in all subjects between May and August 2005 by personal contact or in case of patient death by obtaining written information from the attending general practitioner or from hospital letters describing the circumstances of death. No patient was lost to follow-up.

Anaemia was defined according to WHO criteria as haemoglobin levels <12 mg/dl for women and <13 mg/dl for men [17]. The estimated glomerular filtration rate (eGFR) was calculated according to the MDRD formula [18]. Patients were grouped according to the K/DOQI guidelines in stages I-IV of renal insufficiency using cut-offs of >90, 60-90, 30-59, 15-29, <15 ml/min/1.73 m2 [18]. Patients gave written informed consent with their treatment contract signed at hospital entry or at the occasion of registration with the outpatient department. The local Ethics Committee of the University of Würzburg approved the study protocol.

2.2. Calculation of the pharmacological guideline adherence indicator
The treatment guidelines of the European Society of Cardiology [1], applicable when the study was initiated, were used. The quality of pharmacotherapy was assessed by calculating the GAI (range from 0% to 100%) [8] as number of drugs taken divided by number of drugs indicated. For this calculation, the medication prescribed to the patient at study entry (ie, entering the hospital as in- or outpatient) was used. The study was observational, and potential changes of the therapeutic regimen that occurred in the course of the study were entirely due to the independent medical decision of the patients' general practitioner. The GAI in our study was computed as described by Komajda et al [8] considering also the following: a) patients in NYHA functional class I were included requiring the use of ACE inhibitor or ARB, and beta blockers post myocardial infarction; b) bradycardia below 50 beats per minute, systolic blood pressure below 90 mmHg, severe chronic obstructive pulmonary disease and asthma were considered contraindications for beta blockers; c) systolic blood pressure <90 mmHg, eGFR <30 ml/min/1.73 m2, and serum potassium >5.5 mmol/l were considered contraindications for ACE inhibitors or ARB; d) eGFR <30 ml/min/1.73 m2, and potassium >5.5 mmol/l were considered contraindications for MR blockers. Two versions of the GAI were calculated: GAI-3 considered the three substance classes with strong evidence to improve outcome: beta blockers, ACE inhibitor or ARB, and MR blocker. Hence, the main analyses of this paper were restricted to the GAI-3. The GAI-5, in addition, considered the use of diuretic and cardiac glycoside, which predominantly target at improving symptoms. The appendix shows the algorithms employed for the computation of GAI-3 and GAI-5 in patients with reduced LVEF. We also explored the association between GAI and outcome in patients with normal LVEF using the same GAI-3 but a slightly changed version of GAI-5 in which a cardiac glycoside was considered indicated in NYHA functional class III and IV with either atrial fibrillation or resting heart rate >80 beats/min.

2.3. Data analysis
Data are presented as mean±SD, median (25th, 75th percentile), or n (%), as appropriate. Groups were compared using t-test after Levine's test, Mann-Whitney U-test, and Chi-square test or Fisher's exact test, as appropriate. When comparing the quality of pharmacotherapy between groups, the GAI was used as a non-parametric continuous variable. In patients with reduced LVEF, the GAI-3 fell into tertiles of "low" (0-49% adherence) vs "medium" (50-79%) vs "high" (80-100%); detailed data are shown in Table 2. These cut-off values were also applied to the GAI-5. Determinants of low guideline adherence were sought by logistic regression, and odds ratios (OR) with respective 95% confidence intervals (CI) are reported. Age and sex were forced into all models. Cox proportional hazards regression was applied to estimate the association of GAI-3 and GAI-5 (used as indicator variables rather than continuous variables) with time to all-cause death, and hazard ratios (HR) with 95% CI are reported. Predictors of all-cause death were sought from the variables listed in Table 1 using the likelihood-ratio criterion in backward-selection with P<0.10. The aim was to examine the relationship between the quality of pharmacotherapy and outcome disregarding the interpretation of the significance of other variables in the multivariable model. All tests were two-sided. Graphical methods were used to assess model assumptions and all were satisfied. In survival plots, curves were estimated by use of the mean values of the covariates in the respective Cox model. All reported mortality rates were standardised to 100 person-years of follow-up. All analyses were performed using SPSS (version 15.0.1).


View this table:
[in this window]
[in a new window]

  		Table 1 Characteristics of consecutive heart failure patients (n=1054) with reduced or normal left ventricular ejection fraction

 

   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 Role of funding source
 Conflicts of interest
 References
 
Table 1 summarizes the important baseline characteristics of the entire cohort and of the subpopulations with reduced vs normal LVEF. The median age was 71 and 75 years, respectively. The majority of patients was mainly cared for by general practitioners or physicians and only a minority by cardiologists (95% vs 5%). 62% of all patients were seen on an outpatient basis and/or were referred by a resident doctor for evaluation, whereas 39% of all patients were referrals from other hospitals/institutions. 37% of all subjects had either unscheduled visits at the outpatient clinics or were emergency admissions. In patients with reduced LVEF, 33% were female, and ischaemia was the leading cause of heart failure. In patients with normal LVEF, 52% were women, and more patients had hypertension as the primary cause. In 8% and 6%, respectively, the leading cause was not identified. NYHA functional classes were similarly distributed and comorbid conditions were frequent in both subpopulations. Mean (median) values were also similar regarding markers of body composition, renal function, and markers of inflammation (C-reactive protein).

3.1. Pharmacotherapy in patients with reduced LVEF
3.1.1. Baseline
74% of patients with reduced LVEF were treated with an ACE inhibitor or ARB (Table 2, top section). Of these, all but 10% of patients received "evidence-based" substances (enalapril 42%, ramipril 37%, captopril 8%, lisinopril 3%). 63% of all patients were on beta blockers, and all but 7% received "evidence-based" substances (metoprolol succinate 41%, bisoprolol 27%, carvedilol 25%, nebivolol 0.5%. Fig. 1 (left panel) displays the pharmacotherapy at baseline according to NYHA functional class. Therapy with a beta blocker or ACE inhibitor/ARB decreased with increasing NYHA functional class. Intake of MR blockers was evenly distributed across NYHA classes, and about 50% of the patients received a cardiac glycoside in NYHA class III-IV.


View this table:
[in this window]
[in a new window]

  		Table 2 Pharmacotherapy, guideline adherence indicator and mortality rates in patients with reduced and normal left ventricular ejection fraction

 


Figure 01
View larger version (43K):
[in this window]
[in a new window]
[Download PowerPoint slide]
  		Fig. 1 Pharmacotherapy at baseline in patients with reduced and normal left ventricular ejection fraction. Bars are means with 95% confidence intervals.

 
3.1.2. Quality of pharmacotherapy and its determinants
The overall quality of pharmacotherapy at baseline expressed by the median GAI-3 and GAI-5 values was 67% and 75%, respectively (Table 2, mid section). Determinants (OR [95%CI]) of low guideline adherence were (ordered by the strength of association): worsening renal function (2.56 per K/DOQI stage [1.92-3.42], P<0.001), NYHA functional class (2.25 per class [1.74-2.90], P<0.001), anaemia (2.70 [1.76-4.15], P<0.001), age (1.03 per decade [1.02-1.05], P<0.001), ischaemic cause of heart failure (1.18 [1.10-1.27], P<0.001), chronic respiratory disease (1.66 [1.08-2.57], P=0.022), and uncured malignancy (1.67 [1.00-2.77], P=0.047). Fig. 2 (left panel) illustrates that patients in higher NYHA classes were less likely to receive the substance classes recommended by the treatment guidelines (all P for trend <0.001). Patients referred from hospitals were somewhat better treated than outpatients: GAI-3 67% vs 60%, P=0.091. Patients who were mainly cared for by a cardiologist were better treated when compared with patients cared for by general practitioners or physicians: GAI-3 77% vs 60%, P=0.010.


Figure 02
View larger version (39K):
[in this window]
[in a new window]
[Download PowerPoint slide]
  		Fig. 2 GAI according to NYHA functional class. GAI-3/GAI-5=guideline adherence indicator based on three/five substance classes, respectively. GAI-3 considers the use of beta blocker, angiotensin converting enzyme inhibitor/angiotensin receptor II type-1 blocker, mineralocorticoid receptor blocker; GAI-5, in addition, considers use of diuretics and cardiac glycosides. NYHA=New York Heart Association. Bars are means with 95% confidence intervals. All P values for trend<0.001, respectively.

 
3.1.3. Effect of pharmacotherapy according to guidelines on mortality risk
The median follow-up of survivors was 595 days (469, 801). Mortality was 31% in the first year, and mortality rate was 30 per 100 person-years of follow-up. Patients in the highest tertile of GAI-3 or GAI-5 had a markedly lower mortality rate during follow-up compared with patients in the lowest tertile (for GAI-3: 11 vs 79 per 100 person-years; Table 2, bottom). In analyses adjusting for age and sex, robust protective effects of a high pharmacotherapeutic treatment quality across all NYHA functional classes were observed. The risk reductions for GAI-3 were: class I, HR 0.23 (95%CI 0.04-0.80; P=0.020); class II, HR 0.27 (95%CI 0.12-0.63; P=0.002); class III, HR 0.38 (95%CI 0.20-0.71; P=0.002); class IV, HR 0.20 (95%CI 0.09-0.46; P<0.001). HRs and CIs for the GAI-5 were very similar (detailed data not shown).

Uni- and multivariable predictors of mortality risk are shown in Table 3A. Besides quality of pharmacotherapy, only NYHA class, renal insufficiency, anaemia, systolic blood pressure, LVEF, C-reactive protein, and albumin remained multivariable predictive. Intake of "evidence-based" vs "non evidence-based drugs" within individual substance classes was not predictive of outcome. However, a trend was observed for higher equivalence doses of ACE-inhibitor being protective (HR per percent 0.98, 95%CI 0.95-1.01; P=0.076), whereas such an association was absent for equivalence doses of beta blockers. The prognostic power of GAI-3 and GAI-5 was comparably strong and was surpassed only by NYHA functional class (Table 3A) Interaction terms (age decade by GAI; sex by GAI) were not significant. In both younger and older patients and in either sex, the prognosis consistently improved with better guideline implementation. The risk reduction in these subgroups varied between 40% and 60% (all P<0.05; detailed data not shown).


View this table:
[in this window]
[in a new window]

  		Table 3A Univariable* and multivariable* predictors of all-cause mortality in subjects with reduced left ventricular ejection fraction (n=641)

 
3.1.4. Sensitivity analysis
We also explored whether the GAI simply reflected the impact of comorbidities rather than the quality of pharmacotherapy. In a sensitivity analysis, all comorbid conditions as listed in Table 1 were forced into a model, and the independent prognostic contribution of the GAI was estimated. The change in the –2Log-Likelihood after adding the GAI was 15.99 (P=0.0003) for GAI-3, and 11.33 (P=0.003) for GAI-5, respectively. In this extended model, the risk reduction associated with the highest treatment quality was HR 0.23 (95%CI 0.11-0.48; P<0.001) for GAI-3, and HR 0.39 (95%CI 0.16-0.75; P=0.016) for GAI-5, respectively.

3.2. Pharmacotherapy in patients with normal LVEF
3.2.1. Baseline
Patients with normal and reduced LVEF were treated similarly (Table 1, top). 42% received both an ACE inhibitor/ARB and a beta blocker. With respect to prescription rates of beta blocker and ACE inhibitor/ARB and higher use of diuretics with increasing NYHA functional classes, Fig. 1 displays concordant trends in both patient groups. In patients with normal LVEF, median GAI-3 and GAI-5 was 50% and 60%, respectively (Table 2, mid). A similar relationship between GAI and NYHA functional class was also evident in patients with normal and reduced LVEF (Fig. 2, right panel).

3.2.2. Pharmacotherapy and mortality risk in patients with normal LVEF
The median follow-up of survivors was 595 days (407, 977). Mortality within the first year was 23%, and the mortality rate was 22 per 100 person-years of follow-up (P=0.015 vs patients with reduced LVEF; Table 2, bottom). The univariable predictors of mortality risk were similar to those identified in patients with reduced LVEF, except that LVEF was not predictive (Table 3B). Compared to patients with reduced LVEF, the performance of GAI-3 and GAI-5 in patients with normal LVEF was similar (detailed data not shown). Patients with the highest level of guideline implementation at baseline had a 63% relative mortality risk reduction over time compared to subjects with the lowest level (P<0.001).


View this table:
[in this window]
[in a new window]

  		Table 3B Univariable* and multivariable* predictors of all-cause mortality in subjects with normal left ventricular ejection fraction (n=413)

 
3.3. Modification of pharmacotherapy during follow-up
Owing to the strictly observational design, decisions to change the pharmacotherapy over time were entirely left to the treating physicians. In 248 subjects (148 with reduced and 100 with normal LVEF) information on medication after 6 months of follow-up was available revealing only minor changes in the respective substance classes in both groups over time (detailed data not shown). In these subgroups, the highest level of guideline implementation (ie, high GAI-3) was associated with a similar risk reduction compared with the whole cohort: HR 0.24 (95%CI 0.05-1.21; P=0.085) for reduced and HR 0.62 (95%CI 0.21-1.29; P=0.191) for normal LVEF, respectively.


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
Role of funding source
 Conflicts of interest
 References
 
To our knowledge, this is the first report on the prognostic benefit associated with better pharmacotherapeutic guideline implementation on all-cause mortality risk in a non-selected community-based cohort with CHF. This effect persisted in analyses after rigorous adjustment for numerous clinical variables known to impact on outcome. Quality of pharmacotherapy emerged as one of the most important prognostic factors. We observed a relative risk reduction of about 50% comparing the best guideline implementation vs the worst, which was consistent across NYHA classes. This is in accordance with the EuroHeart Failure Survey I, which reported a significantly improved short-term mortality during 12 weeks of follow-up for intake of ACE inhibitors (about 20%) and beta blockers (about 10%) although the combined effect of CHF medication was not assessed [19].

We included consecutive in- and outpatients presenting at tertiary care hospitals offering unrestricted access to the inhabitants of a medium sized city. Hence, although the cohort was not recruited in the primary care setting it is likely to be fairly representative of the general CHF population. The characteristics of such patients differ in important aspects [10-13,15,20-22] from participants in randomized trials on which treatment guidelines are based. The latter are younger, more often male and exhibit less comorbidity. This is reflected by the superior prognosis (all-cause death) observed in the placebo arms of randomized trials compared to the general CHF population, which has 2-4 times higher mortality rates [16,23]. The mortality rates in our study (31% and 23% in groups with reduced and normal LVEF, respectively) correspond well with those observed in population-based cohorts. Additionally, we observed multiple comorbidities in our patients comparable to those reported previously for a representative sample of the general CHF population [13].

In clinical practice, physicians may be reluctant to implement treatment according to guidelines in frail elderly subjects who are prone to falls due to orthostatic hypotension and to complications of oral anticoagulation [13,24]. Our data, however, encourage close adherence to treatment guidelines in very old individuals. Although their life span is limited, they may benefit if they tolerate the CHF medication. Likewise, the benefit observed in females was of similar magnitude compared with males.

Compared with the IMPROVEMENT [21] and the EuroHeart Failure Survey I [4], more of our patients were treated with ACE inhibitors/ARB, beta-blockers or both. Compared with the recent MAHLER study [8], our patients were treated similarly with ACE inhibitors or ARB, but received beta blockers more often (+10%). MAHLER was the first study to devise the GAI as an index of overall treatment quality in CHF. In the present study, the median GAI-3 (67%) and GAI-5 (75%) values were higher by 6% and 11%, respectively, compared to MAHLER [8]. It is important to note, however, that our definition of these indicators differed from MAHLER in that we also considered contraindications against specific components of the recommended treatment in individual patients. Consequently, more patients were classified as being treated according to guidelines. Both GAI-3 and GAI-5 showed a strong association with CHF severity, decreasing from 89% and 88% in NYHA class I to 40% and 53% in NYHA class IV, respectively (Fig. 2). Further, implementation of guidelines was better in patients with lower age, less reduced renal function, and absence of respiratory disease and malignancy, whereas sex did not influence treatment quality. Surprisingly, patients with non-ischaemic cardiomyopathy were more likely to receive guideline-adherent pharmacotherapy. Considering the high proportion of subjects with ischaemic aetiology this suggests an important area for potential improvement.

Our data indicate that guideline implementation is difficult to achieve in more severely ill patients for two main reasons: a) higher NYHA classes demand the use of more substance classes; b) initiation and maintenance of treatment seems more challenging in sicker and elderly patients who often suffer from multiple comorbid conditions. This needs to be considered in the design of future surveys and prospective studies regarding the implementation of guidelines, which should incorporate means to collect information about potential contraindications, relevant comorbidities, and compliance with medication. However, in sensitivity analyses we could show that the quality of pharmacotherapy is an independent predictor of outcome beyond its close association with the burden of comorbidity.

As has been reported by others [6,19,22,23,25], patients with normal LVEF were older and more often female. The main underlying causes of heart failure with normal LVEF were ischaemic heart disease, hypertension, and valvular disease. Thus, pharmacotherapy with ACE inhibitors/ARB and beta blockers was consistent with the guideline recommendation of appropriate treatment of the underlying diseases. However, for CHF with normal LVEF this treatment is less well evidence-based although there is a strong rationale to apply the same therapeutic principles as for reduced LVEF [1-3]. In that respect, control of blood pressure, heart rate and blood volume, neurohormonal blockade, anti-remodelling and anti-fibrotic strategies are established management strategies. In addition, there is a large overlap between groups of CHF with reduced and normal LVEF [25]. Heart failure with normal LVEF may precede heart failure with predominantly reduced LVEF. Consistent with other reports we found that, in clinical practice, patients with normal LVEF are treated similarly [25] and also have a high mortality rate [22].

In multivariable analyses, we observed a relative risk reduction of 63% and 44% for GAI-3 and GAI-5, respectively. This supports the concept that a combination therapy, consisting of beta blocker, ACE inhibitor/ARB and MR blocker, may be beneficial regardless of the type of CHF. This is of practical importance since the type of CHF (i.e., reduced vs normal LVEF) may sometimes be difficult to discern in everyday clinical practice, and may change over time. Based on our results it seems justifiable to tailor individual therapy according to the treatment guidelines once the diagnosis of CHF has been established irrespective of the degree of systolic left ventricular impairment.

Some limitations of our study need to be considered. Information on pharmacotherapy was collected in all patients only once at study entry. Hence, we were unable to systematically account for changes in medication which might have occurred over time. However, in the subgroup with follow-up information on medication after 6 months, only minor changes were observed that did not appear to weaken the profound effect of guideline adherence on mortality risk reduction. Further, the calculation of GAI was based on substance classes only, and did not consider recommended dosages nor stability of a drug (durability of prescription) or prescription adherence by the patient. However, the beneficial effect of guideline implementation was observed across all NYHA functional classes and proved robust to adjustment for important prognostic factors. Residual confounding due to other factors not prospectively assessed in this study cannot be excluded. Finally, the classification of left ventricular function into ‘reduced’ or ‘normal' is arbitrary in patients with LVEF between 40% and 50%, and many patients in this intermediate range may have had a combined functional abnormality. Since detailed echocardiographic assessment of diastolic function parameters was only available in a subgroup of patients, we were unable to classify patients according to stringent criteria. However, repeating the analyses omitting all patients with LVEF of 40-50% left the results unchanged.

In conclusion, this prospective follow-up study demonstrated a strong beneficial effect of the implementation of guideline-based pharmacotherapy on all-cause mortality risk in non-selected consecutive patients with CHF and reduced left ventricular LVEF. The effects were independent of CHF severity and observed in strata of both higher and lower age and in either sex, thus supporting the application of guidelines also in subgroups with less solid evidence from clinical trials.


   Role of funding source
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Role of funding source
Conflicts of interest
 References
 
MERCK KGaA, Darmstadt, Germany, supported the set-up of the CHF outpatient clinics. Merck KGaA, Germany, was not involved in the selection of the variables or the data analysis process or the drafting and writing of the paper.


   Conflicts of interest
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Role of funding source
 Conflicts of interest
References
 
None.


   Acknowledgements
 
We are indebted to the patients participating in this study. We gratefully acknowledge the continuous and efficient support of the study nurses Susanne Hirschmann, Barbara Kschier, and Elsbeth Pfänder.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 Role of funding source
 Conflicts of interest
 References
 

  1. Remme W.J., Swedberg K. Guidelines for the diagnosis and treatment of chronic heart failure. Eur Heart J (2001) 22:1527–1560.[Free Full Text]
  2. Swedberg K., Cleland J., Dargie H., 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) 26:1115–1140.[Free Full Text]
  3. Hunt S.A. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure). J Am Coll Cardiol (2005) 46:e1–e82.[Free Full Text]
  4. Komajda M., Follath F., Swedberg K., et al. The EuroHeart Failure Survey programme — a survey on the quality of care among patients with heart failure in Europe. Part 2: treatment. Eur Heart J (2003) 24:464–474.[Abstract/Free Full Text]
  5. Cleland J.G., Cohen-Solal A., Aguilar J.C., et al. Management of heart failure in primary care (the IMPROVEMENT of Heart Failure Programme): an international survey. Lancet (2002) 360:1631–1639.[CrossRef][Web of Science][Medline]
  6. Komajda M., Hanon O., Hochadel M., et al. Management of octogenarians hospitalized for heart failure in Euro Heart Failure Survey I. Eur Heart J (2006).
  7. Nieminen M.S., Brutsaert D., Dickstein K., et al. EuroHeart Failure Survey II (EHFS II): a survey on hospitalized acute heart failure patients: description of population. Eur Heart J (2006) 27:2725–2736.[Abstract/Free Full Text]
  8. Komajda M., Lapuerta P., Hermans N., et al. Adherence to guidelines is a predictor of outcome in chronic heart failure: the MAHLER survey. Eur Heart J (2005) 26:1653–1659.[Abstract/Free Full Text]
  9. Lloyd-Jones D.M., Larson M.G., Leip E.P., et al. Lifetime risk for developing congestive heart failure: the Framingham Heart Study. Circulation (2002) 106:3068–3072.[Abstract/Free Full Text]
  10. Sin D.D., McAlister F.A. The effects of beta-blockers on morbidity and mortality in a population-based cohort of 11,942 elderly patients with heart failure. Am J Med (2002) 113:650–656.[CrossRef][Web of Science][Medline]
  11. Jong P., Vowinckel E., Liu P.P., Gong Y., Tu J.V. Prognosis and determinants of survival in patients newly hospitalized for heart failure: a population-based study. Arch Intern Med (2002) 162:1689–1694.[Abstract/Free Full Text]
  12. Havranek E.P., Masoudi F.A., Westfall K.A., Wolfe P., Ordin D.L., Krumholz H.M. Spectrum of heart failure in older patients: results from the National Heart Failure project. Am Heart J (2002) 143:412–417.[CrossRef][Web of Science][Medline]
  13. Braunstein J.B., Anderson G.F., Gerstenblith G., et al. Noncardiac comorbidity increases preventable hospitalizations and mortality among Medicare beneficiaries with chronic heart failure. J Am Coll Cardiol (2003) 42:1226–1233.[Abstract/Free Full Text]
  14. Gambassi G., Forman D.E., Lapane K.L., et al. Management of heart failure among very old persons living in long-term care: has the voice of trials spread? The SAGE Study Group. Am Heart J (2000) 139:85–93.[Web of Science][Medline]
  15. Lien C.T., Gillespie N.D., Struthers A.D., McMurdo M.E. Heart failure in frail elderly patients: diagnostic difficulties, co-morbidities, polypharmacy and treatment dilemmas. Eur J Heart Fail (2002) 4:91–98.[Abstract/Free Full Text]
  16. MacIntyre K., Capewell S., Stewart S., et al. Evidence of improving prognosis in heart failure: trends in case fatality in 66,547 patients hospitalized between 1986 and 1995. Circulation (2000) 102:1126–1131.[Abstract/Free Full Text]
  17. group Ws. Nutritional anaemias. Report of a WHO scientific group (1968) Report No.: 0512-3054 (Print).
  18. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis (2002) 39:S1–S266.[CrossRef][Web of Science][Medline]
  19. Lenzen M.J., Scholte op Reimer W.J., Boersma E., et al. Differences between patients with a preserved and a depressed left ventricular function: a report from the EuroHeart Failure Survey. Eur Heart J (2004) 25:1214–1220.[Abstract/Free Full Text]
  20. Cleland J.G., Swedberg K., Follath F., et al. The EuroHeart Failure survey programme — a survey on the quality of care among patients with heart failure in Europe. Part 1: patient characteristics and diagnosis. Eur Heart J (2003) 24:442—463.
  21. Increasing awareness and improving the management of heart failure in Europe: the IMPROVEMENT of HF initiative. The study group on diagnosis of the working group on heart failure of the European Society of Cardiology. Eur J Heart Fail (1999) 1:139–144.[Abstract/Free Full Text]
  22. Bhatia R.S., Tu J.V., Lee D.S., et al. Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med (2006) 355:260–269.[Abstract/Free Full Text]
  23. Masoudi F.A., Havranek E.P., Wolfe P., et al. Most hospitalized older persons do not meet the enrollment criteria for clinical trials in heart failure. Am Heart J (2003) 146:250–257.[CrossRef][Web of Science][Medline]
  24. Lang C.C., Mancini D.M. NonCardiac comorbidities in heart failure. Heart (2006).
  25. Hogg K., Swedberg K., McMurray J. Heart failure with preserved left ventricular systolic function; epidemiology, clinical characteristics, and prognosis. J Am Coll Cardiol (2004) 43:317–327.[Abstract/Free Full Text]

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Circ Heart FailHome page
G. Guder, S. Frantz, J. Bauersachs, B. Allolio, C. Wanner, M. T. Koller, G. Ertl, C. E. Angermann, and S. Stork
Reverse Epidemiology in Systolic and Nonsystolic Heart Failure: Cumulative Prognostic Benefit of Classical Cardiovascular Risk Factors
Circ Heart Fail, November 1, 2009; 2(6): 563 - 571.
[Abstract] [Full Text] [PDF]

Home page
 Eur J Heart Fail SupplHome page
C.E. Angermann
Comorbidities in heart failure: a key issue
Eur J Heart Fail Suppl, April 1, 2009; 8(suppl_1): i5 - i10.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Störk, S.
Right arrow Articles by Angermann, C. E.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Störk, S.
Right arrow Articles by Angermann, C. E.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?