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European Heart Journal Advance Access published online on August 12, 2008
European Heart Journal, doi:10.1093/eurheartj/ehn359
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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2008. For permissions please email: journals.permissions@oxfordjournals.org

Chronic heart failure leads to an expanded plasma volume and pseudoanaemia, but does not lead to a reduction in the body’s red cell volume

Christopher Adlbrecht1,{dagger}, Spyridoula Kommata2,{dagger}, Martin Hülsmann1,*, Thomas Szekeres3, Christian Bieglmayer3, Guido Strunk4, Georgios Karanikas2, Rudolf Berger1, Deddo Mörtl1, Kurt Kletter2, Gerald Maurer1, Irene M. Lang1 and Richard Pacher1

1 Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
2 Department of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
3 Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Vienna, Vienna, Austria
4 Research Institute for Health Care Management and Economics, Vienna University of Economics and Business Administration, Vienna, Austria

Received 11 February 2008; revised 9 July 2008; accepted 17 July 2008.

* Corresponding author. Tel: +43 1 40 400 4614, Fax: +43 1 40 400 4216, Email: martin.huelsmann{at}meduniwien.ac.at


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Limitations
 Conclusion
 References
 
Aims: Chronic heart failure (CHF) is frequently associated with a decreased haemoglobin level, whereas the mechanism remains largely unknown.

Methods and results: One hundred consecutive CHF patients without anaemia or renal dysfunction based on non-cardiac reasons were enrolled. We explored determinants of anaemia (as iron parameters, erythropoietin, hepcidin and kidney function) including red cell volume (RCV) (by a 51 Cr assay) as well as related markers and plasma volume. The influence of each factor on haemoglobin concentrations was determined in a multiple regression model. Mean haemoglobin concentrations were 11.7 ± 0.8 mg/dL in anaemic CHF patients and 14.4 ± 1.2 mg/dL in non-anaemic patients. Corrected reticulocytes were lower in anaemic patients (35.1 ± 15.7 vs. 50.3 ± 19.2 G/L, P = 0.001), but the RCV was not reduced (1659.3 ± 517.6 vs. 1826.4 ± 641.3 mL, P = 0.194). We found that plasma volumes were significantly higher in anaemic CHF patients (70.0 ± 2.4 vs. 65.0 ± 4.0%, P < 0.001). Plasma volume was the best predictor of haemoglobin concentrations in the regression model applied (B = –0.651, P < 0.001, R2 = 0.769).

Conclusion: Haemodilution appears to be the most potent factor for the development of low haemoglobin levels in patients with CHF. Our data support an additional independent, but minor influence of iron deficiency on haemoglobin concentrations in CHF patients.

Key Words: Anaemia • Heart failure • Erythropoietin • Plasma volume • Hepcidin • Haemodilution


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Limitations
 Conclusion
 References
 
Low haemoglobin is observed in patients suffering from chronic heart failure (CHF).1 Data vary from 4–29% prevalence, dependent on the definition and the severity of the disease.2,3 Low haemoglobin has also been linked to increased mortality and reduced exercise capacity,4 but it is not known whether these relationships are causal. Since the pathophysiology of low haemoglobin in CHF is not well understood,5 therapeutic interventions are currently not based on evidence related to the relevant underlying mechanism. Consequently, results of such studies are conflicting.

The administration of erythropoiesis stimulating agents (ESAS) to correct haemoglobin levels in CHF patients is currently a major issue6–8 with promising surrogate endpoints, but a reduction in morbidity and mortality has, to date, not been proven.

Substitution of iron alone improves haemoglobin levels comparable with a combination of erythropoietin and iron9,10 suggesting that iron deficiency may be key in lowering haemoglobin in CHF. This directs the focus to the iron regulating system. Hepcidin was recently described as the central regulator of iron homeostasis11 and probably is responsible for several reasons of chronic anaemia. Hepcidin has never been described in patients diagnosed with CHF. The main trigger of hepcidin expression is IL-6,12 which is elevated in CHF. Thus, it can be hypothesized that IL-6 activates hepcidin, which suppresses iron uptake and release. On the other hand hepcidin is down-regulated by anaemia and hypoxia. Thus, if anaemia occurs before iron deficiency, hepcidin should be depressed. In this context, hepcidin could probably be used as a marker of iron deficiency anaemia in CHF, as the definition of iron deficiency in CHF currently remains a challenge.

Yet, low haemoglobin concentrations may also be the consequence of fluid retention and consecutively increased plasma volume. Haemodilution in anaemic patients with advanced CHF has already been suggested.13–15 Unfortunately, patients have, in past trials, been pre-selected and only included a limited number of patients, and the role of haemodilution has never been directly compared with other contributing factors of low haemoglobin. If the hypothesis of the predominance of haemodilution is true, therapeutic implications would change dramatically. Thus, instead of increasing erythropoiesis, the correction of fluid homoeostasis would be the main target in patients with low haemoglobin.

The aim of the present study was therefore to analyse, for the first time, variables of erythropoiesis and haemodilution in one model to prove its importance and relative influence on low haemoglobin concentrations observed in CHF patients.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Limitations
 Conclusion
 References
 
Patients
Consecutive patients diagnosed with systolic CHF [left ventricular ejection fraction (LVEF) < 45%] were prospectively included in the study after providing signed informed consent. Exclusion criteria were defined as potential child bearing or pregnancy, non-cardiac illness limiting life expectancy to <1 year, renal disease of a non-cardiac reason, malignancy, chronic inflammatory disease, acute infection, clinical signs of fluid overload, ESAS therapy or iron substitution within the last 6 months as well as any history of disorders known to cause anaemia. Initially 125 patients were approached for consent, of these 19 were ineligible (five chronic inflammatory disease, six patients were under erythropoietin therapy, eight patients had clinical signs of fluid overload) and six patients refused to give their consent.

Determination of haematological parameters
Haemoglobin concentrations, reticulocyte counts, and erythropoietin levels were assessed using standard procedures of the hospitals own laboratory. Anaemia was defined in accordance with the World Health Organization (WHO) as haemoglobin levels <13.0 g/dL in men and 12.0 g/dL in women. Anaemia was confirmed in a second determination of haemoglobin levels within 2 weeks of initial testing and without changes in drug regime (especially diuretics).

Measurement of total red cell volume
The measurements of red cell volume (RCV) were obtained using chromium 51-labelled red cells following the guidelines proposed by the International Committee for Standardization in Haematology16,17 for RCV determination. In general, 15 mL blood was obtained via vein puncture. Samples were first incubated with a small volume of acid–citrate–dextrose solution and washed, followed by adding 2 MBq of chromium 51 which was subsequently well mixed. The tagged blood was re-injected into the patients’ circulation through another vein than from which it was taken. Samples were drawn at 10, 20 and 30 min post-injection intervals from the initial vein. The packed cell volume was obtained for all samples using the microhaematocrit method and the mean of the three measurements was calculated. The measured haematocrit was corrected for trapped plasma and mean body haematocrit.

Total plasma volume (mL) was calculated from measured total blood volume (mL) minus measured total RCV (mL). The percentage of plasma volume (%) was calculated as total plasma volume (mL) divided by total blood volume (mL). For a long time, there has been an ongoing debate on whether and how RCV measurements should be normalized18 and recently others have stated that total RCV might be the better parameter to look at.19 For this reason, total RCV as well as normalized values (RCV/kg)16,20 are reported for this study population.

An additional method favours correcting RCV measurements for body surface area (RCV/BSA). The advantage of this method is the possibility to calculate individual normal values. Therefore, to answer the question whether RCV are decreased below normal, based on the expert panel formula RCV/BSA was calculated in the third step.21 Moreover these volumes were classified to be normal according to the recommendation of the expert panel.

Variables of iron status
Serum iron, ferritin and transferrin were assessed in the local laboratory. Furthermore, serum and urine prohepcidin was measured by enzyme linked immunosorbent assay (ELISA) (DRG Instruments GmbH, Germany).

Iron deficiency was defined as a ferritin level <30 µg/L or transferrin saturation <15%.

Determination of other possible influencing factors of anaemia
In order to evaluate tissue hypoxia arterial (obtained form the radial artery) and venous (obtained form a peripheral vein, mostly an antecubital vein) blood gas analysis was performed and arterio-venous oxygen content difference (AVDO2) calculated. IL-6 and soluble tumor necrosis factor (TNF) alpha receptor levels were measured by ELISA (Bender Med, Vienna, Austria). Plasma NT-proBNP was determined using the Elecsys test (Roche Diagnostics, Austria). Glomerular filtration rates (GFR) were estimated using the Cockroft–Gault formula based on serum creatinine, age, sex, and body weight. Copeptin, in turn, was determined in plasma samples as a surrogate marker for vasopressin (BRAHMS AG, Henningsdorf, Germany).22 Venous blood samples were drawn from the antecubital veins whereas arterial blood was drawn from the radial artery.

Statistical analysis
For an expected medium effect (f2 = 0.2), alpha = 0.05, and beta = 0.20 a sample size between 100 and 130 were calculated to be sufficient for regression models with up to 12 variables.

For tests of whether the distribution of categorical variables differed within anaemic and non-anaemic patients, the Fisher exact test was used. The Student t-test was used for comparison of means between two groups (two-tailed). Summary statistics for the continuous variables are presented as mean ± standard deviation. Non-normally distributed variables are presented as median (25th–75th percentile). A P-value <0.05 was regarded as statistically significant.

Exploratory analysis of influencing factors on anaemia in CHF and their interrelations was performed by using two correlation techniques. A first exploration was based on simple bivariate correlations.

The multiple regression models were performed as full models, entering all factors, which showed associations in bivariate correlations on the single dependent variable haemoglobin into the model. Additionally the multiple regression models were corrected for age and sex. Linearity assumption for continuous variables was assessed graphically. Also normal distribution was tested using the Kolmogorov–Smirnov test. Some variables are log transformed before entering the calculation to get the linearity assumption satisfied. In order to determine the validity of the regression model, we applied bootstrapping analysis picking 500 random bootstrap samples. Each of these samples was used for a recalculation of the model parameters. Final parameters based on the bootstrap calculations were estimated using the percentile method.

Binary variables are correlated with metric variables using point biserial correlation coefficients which are mathematically identical with Pearson product moment correlation coefficients in case of a coding with 0–1 values.

All results from the regression models were presented using standardized beta weights (B). For statistical analysis SPSS version 16.0 and MLwiN 2.02 was used.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Limitations
 Conclusion
 References
 
Patient clinical characteristics
From January until March 2007, 100 patients matching all inclusion and exclusion criteria were included in the study. One patient was excluded from analysis as a result of a formerly unknown thalassemia minor. Mean age was 61.0 ± 10.6 years, weight 88.2 ± 20.9 kg, BSA 2.01 ± 0.24 m2 and 82 (83%) were male. The median NT-proBNP levels were 803.0 (404.0–1942.0) pg/mL. New York Heart Association (NYHA) class I was present in 18 (18%), class II in 41 (41%), and class III in 40 (40%). None of the patients were in NYHA class IV. According to the protocol, none of the patients had elevated jugular veins or apparent clinical oedema. LVEF was 33.1 ± 9.7% as assessed by echocardiography and the average body mass index was 29.3 ± 6.0 kg/m2. Further baseline characteristics are presented in Table 1, whereas haematological parameters of the CHF population are summarized in Table 2.


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  		Table 1 Baseline clinical characteristics of 99 patients with chronic heart failure

 

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  		Table 2 Haematological parameters of 99 chronic heart failure patients

 
Haemoglobin levels, but not total body red cell volume are decreased in chronic heart failure patients
Haemoglobin concentrations were 13.7 ± 1.6 mg/dL and haemoglobin concentrations below the WHO cutoff levels for anaemia were found in 26 (26%) of the CHF patients. Haemoglobin concentrations in these patients were 11.7 ± 0.8 mg/dL compared with 14.4 ± 1.2 mg/dL in the normal haemoglobin level CHF patients. Besides haemoglobin, no variables of blood cell count were decreased below normal values on an average (Table 2).

In contrast to haemoglobin levels, total body RCVs as a function of erythropoiesis did not differ between low haemoglobin CHF patients and CHF patients with normal haemoglobin levels (1659.3 ± 517.6 vs. 1826.4 ± 641.3 mL, P = 0.194, Figure 1). This also held true if RCV was normalized to body weight (19.0 ± 4.5 vs. 21.0 ± 5.2 mL/kg, P = 0.104) and to body mass index (56.91 ± 14.63 vs. 63.87 ± 19.70 mL/kg/m2 P = 0.116).


Figure 1
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  		Figure 1 Comparison of haemoglobin concentration, red cell volume (RCV) and plasma volume in chronic heart failure (CHF) patients without anaemia and anaemic CHF patients: (A) Haemoglobin concentrations in anaemic and non-anaemic CHF patients; (B) there were no significant differences in total RCV between the two groups; (C) Anaemic CHF patients had higher plasma volumes than CHF patients without anaemia.

 
Correcting RCV to BSA, as recommended by the expert panel,21 mean values were 24.21 ± 2.76 mL (range: 19.0–26.6 mL) for anaemic and 24.36 ± 2.63 mL (range: 19.6–17.4 mL) for non-anaemic patients (P = 0.815). Use of the recommended 99% limits for women and 98% for men to estimate individual patients’ normal range, demonstrated that only two out of 99 patients had RCV values below the expected normal. Both patients had normal values of haemoglobin as well as corrected reticulocytes, erythropoietin levels, and iron variables.

However, corrected reticulocyte counts were significantly lower in anaemic (35.1 ± 15.7 G/L) compared with non-anaemic patients (50.3 ± 19.2 G/L, P = 0.001).

Volume load as a haemoglobin influencing factor in chronic heart failure
In the group of CHF patients with low haemoglobin levels, the percentage of plasma volume was increased to 70.0 ± 2.4%, compared with 65.0 ± 4.0% in CHF patients with normal haemoglobin concentrations (P < 0.001, Figure 1). Results after correction for body weight remained significantly different [43.0 (33.8–55.0) vs. 36.4 (32.6–42.8) mL/kg, P = 0.033]. Copeptin levels were 15.4 ± 17.8 pmol/L in CHF patients and were not different in anaemic CHF patients compared with non-anaemic patients (P = 0.780).

Iron status and erythropoietin as haemoglobin influencing factors in chronic heart failure
By definition iron deficiency was present in 26 (26%) of CHF patients. Twelve (46%) of these had normal haemoglobin levels and 14 (54%) were anaemic according to the WHO definition. Haemoglobin concentrations were 14.1 ± 1.5 mg/dL in non-iron deficient CHF patients and 12.6 ± 1.6 mg/dL in iron deficient patients (P < 0.001), but there was no difference between patients with (1697.9 ± 557.4 mL) and without iron deficiency (1821.3 ± 573.3 mL) concerning RCV (P = 0.360). Correcting RCV for body weight did not change the result (iron deficiency: 20.4 ± 5.3 mL/kg, no iron deficiency: 20.5 ± 5.1 mL/kg, P = 0.898).

On an average, variables of iron status were not decreased to lower than normal values in the total population, as well as in the subpopulation with low haemoglobin (Table 2).

Serum prohepcidin bivariately only correlated with soluble TNF alpha receptor (0.301, P = 0.003) and IL-6 (0.211 P = 0.038), but not with the presence of iron deficiency (0.102, P = 0.333).

Serum erythropoietin levels were significantly higher in CHF patients with low haemoglobin levels [15.7 (9.2–32.5)mU/mL], than in CHF patients with normal haemoglobin levels [11.0 (7.4–15.2)mU/mL, P = 0.010]. Low erythropoietin producers23 were identified in 8 (31%) anaemic CHF patients and in 29 (40%) non-anaemic CHF patients (P = 0.391). In bivariate correlation erythropoietin correlated with GFR (–0.218, P = 0.031), but this correlation was lost while correcting for age and sex (–0.172, P = 0.094).

Relationship between haemoglobin levels, anaemia related parameters in chronic heart failure and volume status
Potential influencing factors on haemoglobin levels correlated bivariately as follows: Plasma volume (–0.777, P < 0.001), GFR (0.383, P < 0.001), presence of iron deficiency (–0.406, P < 0.001), erythropoietin (–0.313, P = 0.002), IL-6 (–0.306, P = 0.002), NT-proBNP (–0.278, P = 0.005), AVDO2 (0.290, P = 0.006), sTNFalpha receptor (–0.280, P = 0.006), age (–0.261, P = 0.009), male sex (0.233, P = 0.020), CRP (–0.202, P = 0.044), serum prohepcidin (–0.152, P = 0.135), copeptin (–0.044, P = 0.665), ACI (angiotensin-converting enzyme inhibitor) dosage (0.017, P = 0.887) and EF (0.014, P = 0.897).

Including all potentially related variables which correlated significantly with haemoglobin levels in bivariate analysis into a multiple regression analysis (incorporating percentage of plasma volume, AVDO2, iron deficiency, GFR, erythropoietin, age, soluble TNF alpha receptor, NT-proBNP, IL-6, CRP, and sex), the percentage of plasma volume (B = –0.651, P < 0.001), AVDO2 (B = 0.267, P < 0.001), iron deficiency (B = –0.220, P = 0.002), and GFR (B = 0.267, P = 0.003) were significantly related to haemoglobin concentration (R2 = 0.769, Table 3).


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  		Table 3 Results of multiple regression analysis with haemoglobin concentration as dependent variable

 
Validity testing by application of bootstrap analysis picking 500 random samples proved the robustness of the model (Table 3).


   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Limitations
 Conclusion
 References
 
This is the first cross-sectional study assessing the prevalence and severity of low haemoglobin in relationship to impaired erythropoiesis on one hand and haemodilution on the other hand in a representative group of heart failure outpatients. Moreover, contributing factors for their impairment were evaluated to target new treatment options.

In our study population, consisting of patients with a broad spectrum, but primarily advanced heart failure [median NT-proBNP 803 (range: 9–15797) pg/mL], only 26% had lower than normal haemoglobin levels. This prevalence is much lower than in other diseases with concomitant anaemia such as severe kidney dysfunction24 or rheumatoid arthritis.25 However, our data are in accordance with published data identifying 30% of anaemics in an advanced heart failure population defined as NYHA III/IV and an LVEF of <40%.26

Secondly, in accordance with the lower prevalence, patients with CHF have milder anaemia, also confirmed in our cohort, than patients with kidney dysfunction or malignant disease. Whereas in these populations transfusion is a routine therapeutic option to correct low haemoglobin, this is not matter of debate in CHF patients. The lowest haemoglobin in our cohort was 9.4 mg/dL. Even in unselected cohorts, where co-morbidities were not excluded like in our study haemoglobin did not pass 7.1 mg/dL.26

Concerning the pathophysiology, the concept of low erythropoiesis in CHF is currently favoured. Although from our data this hypothesis is supported by the lower corrected reticulocyte counts in anaemic CHF patients, the fact that total cell volume is not decreased below normal values in any patient with low haemoglobin questions the extent of the erythropoietic impairment.

In our population, similar to the data of Westenbrink et al.,15 erythropoietin—one potential contributor of impaired ertythropoiesis—was rather increased, than decreased. Moreover, low erythropoietin producers were equally distributed in anaemic and non-anaemic CHF patients and, importantly, regression analysis demonstrates that haemoglobin is not influenced by erythropoietin levels.

Although most parameters of iron homoeostasis—a main contributor of erythropoiesis—were slightly lower in anaemic CHF patients, mean values were within the normal range in both groups. Especially hepcidin, as the central regulator of iron utilization,11 was not altered at all.

Nevertheless, iron deficiency is present in CHF in roughly half of the patients, as seen in our data. Interestingly, the distribution of iron deficiency in anaemic and non-anaemic patients is similar, but regression analysis reveals an independent association of iron deficiency and haemoglobin levels. It can be argued, that iron deficiency is the main contributing factor leading to low reticulocytes, but not erythropoietin. If there is any correlation between haemoglobin and erythropoietin, it is a negative one. Unfortunately, due to the lack of an established definition, the incidence of iron deficiency in CHF is unclear. This fact is underlined by our result that 46% of the patients who were defined as iron deficient, had normal haemoglobin levels. On the other hand, this fact could also be explained by the time delay between iron deficiency and the establishment of iron deficiency anaemia. To answer this question, time-line assessments would be necessary.

Iron homeostasis plays a key role not only in oxygen transport but also in oxidative metabolism in the skeletal muscle. Iron deficiency is a much broader term than iron deficiency anaemia and also includes the impaired iron utilization which may be caused by chronic inflammatory processes. Data suggest that already marginal iron deficiency may lead to reduced exercise capacity long before the development of anaemia.27,28 This might explain the increase in exercise capacity in patients treated with erythropoietin and consecutive iron supplement.29–31 Indeed also patients treated solely with iron supplement increased exercise capacity.9 A key regulator associated with iron deficiency is hepcidin. Our hypothesis, of differing serum levels, could not be proven, as there was no difference between anaemic and non-anaemic CHF patients. The reason for this may be that either hepcidin is not at all influenced in CHF, which is unlikely as serum prohepcidin levels correlate with IL-6 bivariately (B = 0.230, P = 0.023) and remain significant if corrected for age and gender (B = 0.204, P = 0.048). An alternative explanation might be that the levels may be balanced out by several opposite triggers. Alternatively, serum levels of prohepcidin might not tell us anything about function. In a clinical model with healthy volunteers, there was also no relationship between iron absorption and serum prohepcidin concentrations.32

In a subset of patients, we also investigated urine levels of prohepcidin (data not shown) and found similar results showing that the mode of determination is also not the essential point.

Moreover, we cannot exclude local differences in hepcidin expression. In the first model including hepcidin and the heart, Merle et al.33 found an up-regulation of hepcidin in the heart by hypoxia but at the same time a down-regulation was present in the liver. This implies a more local regulatory importance with probably indirect systemic relevance.

Although erythropoiesis appears to be impaired in heart failure, our data imply that haemodilution is a much stronger influencing factor. Studies with small patient numbers13,14 revealed that anaemia based on haemodilution is present in patients with heart failure, a presence confirmed by our data. Patients with low haemoglobin have significantly increased plasma volumes compared with patients with normal haemoglobin. In contrast to other variables the relationship held true even in a regression model. Increased plasma volume was most significantly related to low haemoglobin concentrations if all presumed co-factors which correlated bivariately with the haemoglobin concentration were included in the model.

Plasma volume was also normalized to body weight and the inclusion of this variable into regression analysis instead of the percent plasma volume revealed that also after normalization plasma volume remained a significant predictor of the haemoglobin levels (B = –0.272, P = 0.008, data not shown). One may of course speculate that a more aggressive diuretic regimen might reduce the number of anaemic patients in this case, but as outlined in Table 1, diuretic use was balanced between anaemic and non-anaemic patients, and patients had no clinical signs of congestion. The mechanism that ACI affect GFR and may represent a link to increased plasma volumes, is plausible, however, the dosage of ACI was similar in anaemic and non-anaemic patients (Table 1).

Getting back to the essential question whether to treat low haemoglobin levels and if yes, which treatment should be chosen, the further question with respect to the cause for an increased plasma volume arises. A regression model (data not shown) including variables of kidney function, diuresis-regulating hormones (the inactive compound of brain natriuretic peptide NT-proBNP and the inactive compound of pro-vasopressin, copeptin) or diuretic treatment reveals that only GFR was associated with plasma volume. This implies that maintaining kidney function is the best therapeutic option to avoid low haemoglobin in heart failure patients. Interestingly, kidney dysfunction plays a major role in low haemoglobin—as already presumed—but different from the current opinion, it is not erythropoietin but fluid retention which appears to be the main link.


   Limitations
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Limitations
Conclusion
 References
 
Limitations to interpretation of the study include single centre design, the absence of a standardized normal range for the total RCV and limited ability to discern abnormalities of iron metabolism and bone marrow red cell production from circulating blood biomarkers. Although all blood samples for analysis were drawn in the morning in all individuals, the results may be influenced by the diurnal variation in the hepcidin secretion.34

Unfortunately, due to the lack of an established definition, the incidence of iron deficiency in CHF is unclear. For instance, ferritin levels are elevated in CHF independent of iron status (reconfirmed by our data), based on its function as an acute phase reactant35 and thereby may not be the best parameter to estimate iron deficiency. Thus our data, although showing a significant influence of iron deficiency on low haemoglobin, are limited by the fact of the arbitrarily chosen definition.

Furthermore, the association of GFR with anaemia could also be linked to the known effects of ACI on GFR and erythropoiesis. Nevertheless it has to be taken into account, that not only the prescription rate, but also the dosage of ACIs were equally distributed in anaemic and non-anaemic patients.


   Conclusion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Limitations
 Conclusion
References
 
Haemodilution appears to be the most potent factor for the development of low haemoglobin levels in patients with a broad spectrum of severity of heart failure. Our data support an additional independent, but minor influence of iron deficiency on lower than normal haemoglobin concentrations in CHF patients. The study results support not administering ESAS to unselected CHF patients with lower than normal haemoglobin levels.

Conflict of interest: there exist no conflicts of interest.


   Footnotes
 
{dagger} C.A. and S.K. contributed equally. Back


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Limitations
 Conclusion
 References
 

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P van der Meer, H F Groenveld, J L Januzzi Jr, and D J van Veldhuisen
Erythropoietin treatment in patients with chronic heart failure: a meta-analysis
Heart, August 15, 2009; 95(16): 1309 - 1314.
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