Abstract

Aims

Beyond erythropoiesis, iron is involved in numerous biological processes crucial for maintenance of homeostasis. Patients with chronic heart failure (CHF) are prone to develop iron deficiency (ID), and iron supplementation improves their functional status and quality of life. We sought to examine the relationship between ID and survival in patients with systolic CHF.

Methods and results

In a prospective observational study, we evaluated 546 patients with stable systolic CHF [age: 55 ± 11 (mean ± standard deviation) years, males: 88%, left ventricular ejection fraction: 26 ± 7%, New York Heart Association (NYHA) class (I/II/III/IV): 57/221/226/42]. Iron deficiency was defined as: ferritin <100 µg/L, or 100–300 µg/L with transferrin saturation <20%. The prevalence of ID was 37 ± 4% [±95% confidence intervals (CI)] in the entire CHF population (32 ± 4 vs. 57 ± 10%—in subjects without vs. with anaemia defined as haemoglobin level <12 g/dL in women and <13 g/dL in men, P < 0.001). In a multiple logistic model, ID was more prevalent in women, those in the advanced NYHA class, with higher plasma N-terminal pro-type B natriuretic peptide and higher serum high-sensitivity C-reactive protein (all P < 0.05). At the end of follow-up (mean duration: 731 ± 350 days), there were 153 (28%) deaths and 30 (6%) heart transplantations (HTX). In multivariable models, ID (but not anaemia) was related to an increased risk of death or HTX (adjusted hazard ratio 1.58, 95% CI 1.14–2.17, P < 0.01).

Conclusion

In patients with systolic CHF, ID is common and constitutes a strong, independent predictor of unfavourable outcome. Iron supplementation may be considered as a therapeutic approach in these patients to improve prognosis.

Introduction

Iron is a metabolically active micronutrient. One of its crucial properties is the ability to shuttle between two oxidative states (ferric and ferrous iron), which makes it an efficient cofactor for several enzymes and the catalyst of numerous biochemical reactions.1,2 Iron plays a crucial role in oxygen transport (as a component of haemoglobin), oxygen storage (as a component of myoglobin), oxidative metabolism in the skeletal and heart muscle (as a component of oxidative enzymes and respiratory chain proteins),3,4 and also is involved in the synthesis and degradation of lipids, carbohydrates, DNA, and RNA.1,2 The maintenance of normal iron metabolism is particularly important for cells that are characterized by high mitogenic potential (neoplastic cells, haematopoietic cells, including immune competent cells) and high energy demand (hepatocytes, adipocytes, renal cells, immune cells, skeletal myocytes, and cardiomyocytes).1,2,5–8

Iron deficiency (ID) is the most common nutritional disorder, affecting more than one-third of the general population.9–11 Iron deficiency has been also recognized to complicate chronic diseases (e.g. inflammatory bowel disease, Parkinson's diseases, rheumatoid diseases, and chronic renal failure), with or without concomitant anaemia.12–16

The presence of ID may have multifaceted clinical consequences, not only directly related to impaired erythropoiesis, but also to marked impairment of oxidative metabolism, cellular energetics, and cellular immune mechanisms.1–8,17 Iron deficiency with and without anaemia is accompanied by reduced aerobic performance and subjective complaints of poor physical condition18 and its correction improves cognitive, symptomatic, and exercise performance.19,20

Until recently there has been little interest in the potential importance of ID in the syndrome of chronic heart failure (CHF).21–23 Recently, however it has been shown that intravenous iron supplementation in iron-deficient patients with CHF exerts favourable effects on functional status and quality of life.19,24–28 Iron deficiency may have other detrimental effects in CHF, including on survival. For that reason, we undertook a prospective study to verify the hypothesis that ID unfavourably affected prognosis in patients with systolic CHF.

Methods

Study sample

The recruitment phase of the study was conducted among patients with systolic CHF attending outpatient clinics or admitted electively in two tertiary referral cardiology centres (Wroclaw and Zabrze, Poland). The criteria for study inclusion were: (i) a documented history of CHF of ≥6 months; (ii) left ventricular ejection fraction (LVEF) ≤45% as assessed by echocardiography (performed at the time of screening using Simpson's planimetric method to determine LVEF); (iii) clinical stability and unchanged medications for ≥1 month preceding the study. Exclusion criteria included: (i) acute coronary syndrome, coronary revascularization or any major surgery within the 3 months preceding the study; (ii) unplanned hospitalization due to HF deterioration or any other cardiovascular reason within 1 month preceding the study; (iii) any acute/chronic illness that might influence iron metabolism (including known malignancy, infection, severe renal disease requiring dialysis, and haematological diseases); (iv) any anaemia or/and ID treatment either at the time of the study or in the past 12 months.

When patients were screened for this project, they were asked in detail about blood transfusions, erythropoietin therapy, intravenous iron infusions, and also any nutritional supplements potentially containing iron. None of patients included in the study received such therapy.

Additionally, all anaemic patients included into the study underwent a routine clinical evaluation in order to detect any potential secondary causes of anaemia and subsequently patients with an evidence of active bleeding were not included into the study. No routine endoscopy was required for the inclusion into the present study.

The study protocol was approved by the local ethics committees, and all subjects gave written informed consent. The study was conducted in accordance with the Helsinki Declaration.

Iron status and other laboratory measurements

In all patients, venous blood samples were taken in the morning following an overnight fast and after a supine rest of at least 15 min. Haematinics were assessed from fresh venous blood with EDTA. After centrifugation, serum was collected and frozen at −70°C until being analysed (other laboratory measures).

The following haematinics were measured using an automatic system ADVIA 120 (Siemens, Healthcare Diagnostics, Deerfield, IL, USA): haemoglobin concentration (g/dL), haematocrit (%), red blood cells (RBC, T/L), mean corpuscular volume (MCV, fL), mean corpuscular haemoglobin (MCH, pg), and mean corpuscular haemoglobin concentration (MCHC, g/L). Anaemia was defined as haemoglobin level <12 g/dL in women and <13 g/dL in men.29

The following blood biomarkers reflecting iron metabolism were assessed directly: serum concentrations of iron (μg/L), ferritin (μg/L), and total iron-binding capacity (TIBC, μg/L). Transferrin saturation (Tsat) was calculated as a ratio serum iron (μg/L) and TIBC (μg/L), multiplied by 100 and expressed in per cent. Serum ferritin was measured using immunoassay based on electrochemiluminescence on the Elecsys 2010 System (Roche Diagnostics GmbH, Mannheim, Germany). Serum iron and TIBC were assessed using a substrate method with Feren S (Thermo Fisher Scientific, Waltham, MA, USA). Iron deficiency was defined prospectively as serum ferritin <100 µg/L, or serum ferritin ≥100 µg/L and ≤300 µg/L with Tsat <20%.

Plasma concentration of N-terminal pro-type B natriuretic peptide (NT-proBNP, pg/mL) was measured using immunoassay based on electrochemiluminescence on the Elecsys 1010/2010 System (Roche Diagnostics GmbH).

Renal function was assessed using the estimated glomerular filtration rate (eGFR, mL/min/1.73 m2), calculated from the Modification of Diet in Renal Disease equation.30 Serum concentration of sodium (Na, mmol/L) and high-sensitivity C-reactive protein (hs-C-reactive protein, mg/L) were assessed using standard methods.

Clinical follow-up

Patients were seen regularly by the study investigators in outpatient CHF clinics with follow-up duration ≥12 months in all survivors. Both in Wroclaw and Zabrze, patients with heart failure are usually seen every 3–4 months, unless there is a clinical need for an extra visit. Information regarding survival was obtained directly from patients or their relatives, from the CHF clinic database, or from the hospital system. No patient was lost to follow-up. The primary endpoint was all-cause death or heart transplantation (HTX) (whatever occurred first). The length of follow-up of survivors and patients in whom events occurred after 3 years were censored at 1095 days.

Statistical analyses

Continuous variables with a normal distribution [age, LVEF, eGFR, body mass index (BMI), serum Na, haemoglobin, haematocrit, RBC, MCV, MCH, and MCHC] were expressed as means (x) with standard deviations. The inter-group differences were tested using Student's t-test. The remaining continuous variables had a skewed distribution (plasma NT-proBNP and serum hs-C-reactive protein), and were expressed as medians with lower and upper quartiles. The inter-group differences were tested using the Mann–Whitney U-test. For further analyses, these variables were log transformed in order to normalize their distribution. The categorical variables were expressed as numbers with percentages. The inter-group differences were tested using the χ2 test.

Clinical determinants of ID in patients with CHF were established using univariate and multiple logistic regression models, including both continuous and dichotomized determining variables. In these analyses, we included the following parameters: centre, age, sex, BMI, CHF aetiology, New York Heart Association (NYHA) class, LVEF, plasma NT-proBNP (log), serum Na, serum hs-C-reactive protein (log), renal function assessed using eGFR, the presence of diabetes mellitus, therapy with angiotensin-converting enzyme (ACE) inhibitors and/or angiotensin receptor blockers (ARBs), aldosterone antagonist, β-blocker, loop diuretic, statin, antiplatelet drug, and anticoagulant drug. It has been commonly established that anaemia is related to ID, but being rather a consequence of ID than its cause, anaemia was not included in these models intentionally.

The associations between analysed variables and survival were established using Cox proportional hazards analyses (both univariate and multivariable models). In these analyses, we included the following parameters as potential prognosticators: centre, age, sex, BMI, CHF aetiology, NYHA class, LVEF, plasma NT-proBNP (log), serum Na, serum hs-C-reactive protein (log), renal function assessed using eGFR, the presence of diabetes mellitus, the presence of anaemia, and the presence of ID. The assumptions of the proportional hazard were tested for all the covariates.

In order to illustrate the effect of the presence of ID on 3-year event-free survival rates, Kaplan–Meier curves for cumulative survival were constructed for patients with CHF varying the iron status (as described above). Differences in event-free survival rates were tested using the Cox–Mantel log-rank test.

All statistical analyses were performed by using Statistica 7.1 and StatView 5.0. All tests were two-sided. A value of P < 0.05 was considered statistically significant.

Results

Prevalence of iron deficiency, and its associations with clinical indices in patients with systolic chronic heart failure

The baseline clinical characteristics of the 546 recruited patients are shown in Table 1. Iron deficiency was diagnosed in 199 of patients with systolic CHF, which corresponds to a prevalence of 37 ± 4% [±95% confidence intervals (CI)]: 40 ± 8% in Wroclaw and 35 ± 5% in Zabrze (P > 0.2). Iron deficiency was associated with lower haemoglobin, haematocrit, MCV, MCH, and MCHC. The prevalence of ID was 57 ± 10 vs. 32 ± 4% in subjects with vs. without anaemia (P < 0.001).

Table 1

Baseline clinical characteristics of patients with systolic chronic heart failure, also in subgroups varying of iron status

Variables All studied patients with CHF (n = 546) Patients with CHF and no IDa (n = 347) Patients with CHF and IDa (n = 199) 
Age, years 55 ± 11 55 ± 27 56 ± 11 
Sex, males 480 (88) 315 (91) 165 (83)** 
BMI, kg/m2 26.7 ± 4.4 27.0 ± 4.3 26.2 ± 4.5* 
CHF aetiology, ischaemic 367 (67) 226 (65) 141 (71) 
NYHA class, I/II/III/IV 57/221/226/42 (10/41/41/8) 44/152/133/21 (12/44/38/6) 16/69/93/21 (8/35/47/10)* 
LVEF, % 26 ± 7 26 ± 7 25 ± 8 
Diabetes mellitus 149 (27) 96 (28) 53 (27) 
NT-proBNP, pg/mL 1570 (656–3723) 1369 (580–3268) 2029 (798–4478)*** 
Na, mmol/L 138 ± 4 137 ± 4 138 ± 4 
Hs-C-reactive protein, mg/L 2.6 (1.3–6.2) 2.4 (1.2–5.2) 3.3 (1.4–8.0)** 
eGFR, mL/min/1.73 m2 80.5 ± 26.0 81.7 ± 25.9 78.4 ± 26.2 

 
Treatment    
 ACE-I and/or ARB 516 (95) 328 (95) 188 (95) 
 β-Blocker 537 (98) 342 (99) 195 (98) 
 Aldosterone antagonist 418 (77) 272 (78) 146 (73) 
 Loop diuretic 437 (80) 279 (80) 158 (79) 
 Statin 380 (70) 237 (68) 143 (72) 
 Antiplatelet drug 290 (53) 182 (53) 108 (54) 
 Anticoagulant drug 207 (38) 135 (39) 72 (36) 
 Haemoglobin, g/dL 14.1 ± 1.7 14.4 ± 1.6 13.6 ± 1.6*** 
 Haematocrit, % 42 ± 5 42 ± 4 41 ± 5*** 
 RBC, T/L 4.56 ± 0.55 4.59 ± 0.54 4.51 ± 0.56 
 MCV, fL 91.5 ± 6.7 92.3 ± 6.7 90.1 ± 6.5*** 
 MCH, pg 31.1 ± 2.7 31.6 ± 2.7 30.2 ± 2.5*** 
 MCHC, g/L 34.0 ± 1.9 34.2 ± 2.0 33.6 ± 1.5*** 
Variables All studied patients with CHF (n = 546) Patients with CHF and no IDa (n = 347) Patients with CHF and IDa (n = 199) 
Age, years 55 ± 11 55 ± 27 56 ± 11 
Sex, males 480 (88) 315 (91) 165 (83)** 
BMI, kg/m2 26.7 ± 4.4 27.0 ± 4.3 26.2 ± 4.5* 
CHF aetiology, ischaemic 367 (67) 226 (65) 141 (71) 
NYHA class, I/II/III/IV 57/221/226/42 (10/41/41/8) 44/152/133/21 (12/44/38/6) 16/69/93/21 (8/35/47/10)* 
LVEF, % 26 ± 7 26 ± 7 25 ± 8 
Diabetes mellitus 149 (27) 96 (28) 53 (27) 
NT-proBNP, pg/mL 1570 (656–3723) 1369 (580–3268) 2029 (798–4478)*** 
Na, mmol/L 138 ± 4 137 ± 4 138 ± 4 
Hs-C-reactive protein, mg/L 2.6 (1.3–6.2) 2.4 (1.2–5.2) 3.3 (1.4–8.0)** 
eGFR, mL/min/1.73 m2 80.5 ± 26.0 81.7 ± 25.9 78.4 ± 26.2 

 
Treatment    
 ACE-I and/or ARB 516 (95) 328 (95) 188 (95) 
 β-Blocker 537 (98) 342 (99) 195 (98) 
 Aldosterone antagonist 418 (77) 272 (78) 146 (73) 
 Loop diuretic 437 (80) 279 (80) 158 (79) 
 Statin 380 (70) 237 (68) 143 (72) 
 Antiplatelet drug 290 (53) 182 (53) 108 (54) 
 Anticoagulant drug 207 (38) 135 (39) 72 (36) 
 Haemoglobin, g/dL 14.1 ± 1.7 14.4 ± 1.6 13.6 ± 1.6*** 
 Haematocrit, % 42 ± 5 42 ± 4 41 ± 5*** 
 RBC, T/L 4.56 ± 0.55 4.59 ± 0.54 4.51 ± 0.56 
 MCV, fL 91.5 ± 6.7 92.3 ± 6.7 90.1 ± 6.5*** 
 MCH, pg 31.1 ± 2.7 31.6 ± 2.7 30.2 ± 2.5*** 
 MCHC, g/L 34.0 ± 1.9 34.2 ± 2.0 33.6 ± 1.5*** 

CHF, chronic heart failure; ID, iron deficiency; BMI, body mass index; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; NT-proBNP, N-terminal pro-B type natriuretic peptide; hs-C-reactive protein, high-sensitivity C-reactive protein; eGFR, estimated glomerular filtration rate; ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; RBC, red blood cells; MCV, mean corpuscular volume; MCH, mean corpuscular haemoglobin; MCHC, mean corpuscular haemoglobin concentration.

aID was defined as ferritin <100 µg/L, or ferritin 100–300 µg/L and Tsat <20%. Data are presented as means ± standard deviations, medians (with lower and upper quartiles), or numbers (with percentages), where appropriate.

*P < 0.05.

**P < 0.01.

***P < 0.001.

In the univariate logistic regression models, we found the following variables to be associated with ID: female sex, NYHA classes III and IV, high plasma NT-proBNP, high serum hs-C-reactive protein, and low BMI (Table 2). Based on a multiple logistic regression model, the following independent clinical associates with ID in patients with CHF were established: female sex, advanced NYHA class, high plasma NT-proBNP, and high serum hs-C-reactive protein (all P < 0.05) (Table 2). The prevalence of ID in the subgroups corresponding to the clinical associates established in the multiple logistic regression model ranged from 31 ± 5 to 52 ± 12% (Figure 1).

Table 2

Clinical determinants of iron deficiency (defined as ferritin <100 µg/L, or ferritin 100–300 µg/L and transferrin saturation <20%) in patients with systolic chronic heart failure (univariate and multivariable logistic regression models)

Determinants, categories/units Univariate models
 
Multivariable model
 
 OR 95% CI χ2 P OR 95% CI χ2 P 
Centre, Zabrze vs. Wroclaw 0.80 0.55–1.17 1.29 0.26 1.02 0.59–1.76 0.003 0.96 
Age, 10 years 1.08 0.91–1.27 0.78 0.38 0.92 0.74–1.14 0.62 0.43 
Sex, males vs. females 0.49 0.29–0.83 7.16 0.008 0.50 0.29–0.87 5.93 0.02 
BMI, 1 kg/m2 0.96 0.92–0.99 4.53 0.03 0.98 0.93–1.02 1.11 0.29 
CHF aetiology, ischaemic vs. non-ischaemic 1.30 0.89–1.90 1.88 0.17 1.34 0.82–2.17 1.38 0.24 

 
NYHA class 
 II vs. I 1.16 0.61–2.22 0.21 0.65 1.19 0.60–2.39 0.25 0.62 
 III vs. I 1.79 0.95–3.38 3.24 0.07 1.85 0.87–3.89 2.58 0.11 
 IV vs. I 2.56 1.11–5.92 4.86 0.03 2.92 1.06–8.03 4.29 0.04 

 
LVEF, 1% 0.99 0.97–1.02 0.37 0.54 1.00 0.97–1.03 0.01 0.92 
Diabetes mellitus, yes vs. no 0.95 0.64–1.41 0.07 0.79 0.75 0.47–1.19 1.51 0.22 
NT-proBNP, 1 log pg/mL 1.33 1.14–1.56 12.71 <0.001 1.25 1.00–1.55 3.95 0.047 
Na, 1 mmol/L 1.01 0.97–1.05 0.26 0.61 1.04 0.98–1.09 1.57 0.21 
Hs-C-reactive protein, 1 log mg/L 1.41 1.14–1.56 11.70 <0.001 1.37 1.09–1.71 7.56 0.006 
eGFR, 5 mL/min/1.73 m2 0.96 0.94–1.01 2.09 0.15 1.00 0.96–1.04 0.001 0.98 
Therapy with ACE-I and/or ARB, yes vs. no 0.99 0.46–2.13 0.001 0.98 1.47 0.62–3.46 0.77 0.38 
Therapy with β-blocker, yes vs. no 0.71 0.19–2.69 0.25 0.62 0.57 0.14–2.37 0.60 0.44 
Therapy with aldosterone antagonist, yes vs. no 0.76 0.51–1.14 1.77 0.18 0.71 0.40–1.27 1.34 0.25 
Therapy with loop diuretic, yes vs. no 0.94 0.61–1.45 0.08 0.78 0.80 0.45–1.41 0.61 0.43 
Therapy with statin, yes vs. no 1.19 0.81–1.74 0.76 0.38 1.37 0.88–2.13 1.90 0.17 
Therapy with antiplatelet drug, yes vs. no 1.08 0.76–1.53 0.17 0.68 1.12 0.70–1.80 0.22 0.64 
Therapy with anticoagulant drug yes vs. no 0.89 0.62–1.28 0.40 0.53 0.98 0.63–1.51 0.01 0.91 
Determinants, categories/units Univariate models
 
Multivariable model
 
 OR 95% CI χ2 P OR 95% CI χ2 P 
Centre, Zabrze vs. Wroclaw 0.80 0.55–1.17 1.29 0.26 1.02 0.59–1.76 0.003 0.96 
Age, 10 years 1.08 0.91–1.27 0.78 0.38 0.92 0.74–1.14 0.62 0.43 
Sex, males vs. females 0.49 0.29–0.83 7.16 0.008 0.50 0.29–0.87 5.93 0.02 
BMI, 1 kg/m2 0.96 0.92–0.99 4.53 0.03 0.98 0.93–1.02 1.11 0.29 
CHF aetiology, ischaemic vs. non-ischaemic 1.30 0.89–1.90 1.88 0.17 1.34 0.82–2.17 1.38 0.24 

 
NYHA class 
 II vs. I 1.16 0.61–2.22 0.21 0.65 1.19 0.60–2.39 0.25 0.62 
 III vs. I 1.79 0.95–3.38 3.24 0.07 1.85 0.87–3.89 2.58 0.11 
 IV vs. I 2.56 1.11–5.92 4.86 0.03 2.92 1.06–8.03 4.29 0.04 

 
LVEF, 1% 0.99 0.97–1.02 0.37 0.54 1.00 0.97–1.03 0.01 0.92 
Diabetes mellitus, yes vs. no 0.95 0.64–1.41 0.07 0.79 0.75 0.47–1.19 1.51 0.22 
NT-proBNP, 1 log pg/mL 1.33 1.14–1.56 12.71 <0.001 1.25 1.00–1.55 3.95 0.047 
Na, 1 mmol/L 1.01 0.97–1.05 0.26 0.61 1.04 0.98–1.09 1.57 0.21 
Hs-C-reactive protein, 1 log mg/L 1.41 1.14–1.56 11.70 <0.001 1.37 1.09–1.71 7.56 0.006 
eGFR, 5 mL/min/1.73 m2 0.96 0.94–1.01 2.09 0.15 1.00 0.96–1.04 0.001 0.98 
Therapy with ACE-I and/or ARB, yes vs. no 0.99 0.46–2.13 0.001 0.98 1.47 0.62–3.46 0.77 0.38 
Therapy with β-blocker, yes vs. no 0.71 0.19–2.69 0.25 0.62 0.57 0.14–2.37 0.60 0.44 
Therapy with aldosterone antagonist, yes vs. no 0.76 0.51–1.14 1.77 0.18 0.71 0.40–1.27 1.34 0.25 
Therapy with loop diuretic, yes vs. no 0.94 0.61–1.45 0.08 0.78 0.80 0.45–1.41 0.61 0.43 
Therapy with statin, yes vs. no 1.19 0.81–1.74 0.76 0.38 1.37 0.88–2.13 1.90 0.17 
Therapy with antiplatelet drug, yes vs. no 1.08 0.76–1.53 0.17 0.68 1.12 0.70–1.80 0.22 0.64 
Therapy with anticoagulant drug yes vs. no 0.89 0.62–1.28 0.40 0.53 0.98 0.63–1.51 0.01 0.91 

OR, odds ratio; CI, confidence interval; BMI, body mass index; CHF, chronic heart failure; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; NT-proBNP, N-terminal pro-B type natriuretic peptide; hs-C-reactive protein, high-sensitivity C-reactive protein; eGFR, estimated glomerular filtration rate; ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker.

Figure 1

Prevalence of iron deficiency in patients with chronic heart failure (CHF), also in clinical subgroups (percentages ± 95% confidence intervals). In the case of plasma N-terminal pro-type B natriuretic peptide (NT-proBNP) and serum high-sensitivity C-reactive protein (hs-C-reactive protein), medians were used as cut-off values.

Figure 1

Prevalence of iron deficiency in patients with chronic heart failure (CHF), also in clinical subgroups (percentages ± 95% confidence intervals). In the case of plasma N-terminal pro-type B natriuretic peptide (NT-proBNP) and serum high-sensitivity C-reactive protein (hs-C-reactive protein), medians were used as cut-off values.

Iron deficiency and prognosis in patients with systolic chronic heart failure

The mean follow-up was 731 ± 350 days (median 800 days, range: 1–1095 days). The proportion of patients surviving free from death or HTX was 62% (95% CI: 58–67%). The proportion of surviving was 67% (95% CI: 62–71%).

The proportionality assumption and the assumption of a log-linear relationship between the prognosticators and the hazard function were fulfilled for all tested variables.

Univariate analyses

In univariate Cox proportional hazard regression models, the following variables were shown to predict increased rate of death and HTX: low BMI, high NYHA class, low LVEF, high plasma NT-proBNP, high serum hs-C-reactive protein, reduced serum Na, reduced eGFR, and the presence of anaemia (Table 3). The same variables predicted all-cause mortality in the studied cohort (Table 3).

Table 3

Prognosticators of event rates in patients with systolic chronic heart failure (Cox proportional hazard regression models)

Prognosticators, units Univariate models
 
Multivariable model
 
 HR 95% CI χ2 P HR 95% CI χ2 P 
Events: all-cause death or HTX (primary analyses) 
 Centre, Zabrze vs. Wroclaw 1.00 0.74–1.36 0.00004 0.99 0.82 0.55–1.20 1.06 0.30 
 Age, 10 years 0.97 0.85–1.11 0.21 0.65 1.03 0.87–1.21 0.10 0.76 
 Sex, men vs. women 1.34 0.82–2.18 1.38 0.24 1.46 0.87–2.43 2.05 0.15 
 BMI, 1 kg/m2 0.95 0.92–0.98 8.49 0.004 1.01 0.97–1.05 0.17 0.68 
 CHF aetiology, ischaemic vs. non-ischaemic 0.82 0.61–1.11 1.62 0.20 1.00 0.71–1.41 0.0001 0.99 
 NYHA class   44.05 <0.001   7.14 0.07 
  IV vs. I 4.52 2.24–9.10 17.81 <0.001 1.86 0.83–4.21 2.24 0.13 
  III vs. I 2.71 1.49–4.94 10.58 <0.001 1.32 0.69–2.56 0.70 0.41 
  II vs. I 1.14 0.61–2.15 0.18 0.68 0.88 0.46–1.70 0.14 0.71 
 LVEF, 1% 0.93 0.91–0.95 41.85 <0.001 0.96 0.94–0.98 11.04 <0.001 
 NT-proBNP, 1 log pg/mL 1.76 1.53–2.02 65.45 <0.001 1.42 1.19–1.71 14.44 <0.001 
 Na, 1 mmol/L 0.93 0.90–0.96 23.75 <0.001 0.96 0.93–0.99 4.00 0.046 
 Diabetes mellitus, yes vs. no 1.26 0.92–1.72 2.06 0.15 1.11 0.80–1.57 0.38 0.54 
 eGFR, 5 mL/min/1.73 m2 0.96 0.94–0.99 5.87 0.02 1.01 0.97–1.04 0.07 0.79 
 Hs-C-reactive protein, 1 log mg/L 1.35 1.16–1.56 15.69 <0.001 1.06 0.88–1.26 0.37 0.54 
 Anaemia,a yes vs. no 1.54 1.10–2.16 6.37 0.01 1.07 0.74–1.54 0.12 0.74 
 ID,b yes vs. no 1.74 1.30–2.33 13.97 <0.001 1.58 1.14–2.17 7.74 0.005 
χ2 of the multivariable model       118.29 <0.001 

 
Events: all-cause death (secondary analyses) 
 Centre, Zabrze vs. Wroclaw 0.76 0.55–1.05 2.78 0.10 1.66 1.09–2.53 5.54 0.02 
 Age, 10 years 1.07 0.92–1.24 0.77 0.38 1.13 0.94–1.36 1.61 0.21 
 Sex, men vs. women 1.45 0.84–2.52 1.78 0.18 1.57 0.88–2.81 2.32 0.13 
 BMI, 1 kg/m2 0.96 0.92–0.99 4.68 0.03 1.02 0.98–1.06 0.94 0.33 
 CHF aetiology, ischaemic vs. non-ischaemic 0.83 0.60–1.16 1.20 0.27 1.00 0.69–1.45 0.0001 0.99 
 NYHA class   40.74 <0.001   10.29 0.02 
  IV vs. I 4.58 2.27–9.22 18.09 <0.001 2.01 0.87–4.64 2.66 0.10 
  III vs. I 2.10 1.14–3.87 5.68 0.02 1.04 0.53–2.04 0.01 0.92 
  II vs. I 0.99 0.52–1.87 0.002 0.97 0.75 0.39–1.46 0.71 0.40 
 LVEF, 1% 0.94 0.92–0.96 24.45 <0.001 0.97 0.94–0.99 6.24 0.01 
 NT-proBNP, 1 log pg/mL 1.81 1.56–2.11 60.14 <0.001 1.47 1.21–1.80 14.34 <0.001 
 Na, 1 mmol/L 0.93 0.90–0.96 19.07 <0.001 0.95 0.91–0.98 7.43 0.006 
 Diabetes mellitus, yes vs. no 1.28 0.91–1.79 1.98 0.16 1.03 0.71–1.50 0.02 0.88 
 eGFR, 5 mL/min/1.73 m2 0.95 0.92–0.98 8.66 0.003 1.01 0.97–1.06 0.49 0.48 
 Hs-C-reactive protein, 1 log mg/L 1.38 1.18–1.61 15.63 <0.001 1.08 0.89–1.32 0.58 0.45 
 Anaemia,a yes vs. no 1.62 1.13–2.33 6.79 0.009 1.07 0.72–1.61 0.11 0.74 
 ID,b yes vs. no 1.74 1.27–2.39 11.63 <0.001 1.58 1.11–2.25 6.37 0.01 
χ2 of the multivariable model       114.72 <0.001 
Prognosticators, units Univariate models
 
Multivariable model
 
 HR 95% CI χ2 P HR 95% CI χ2 P 
Events: all-cause death or HTX (primary analyses) 
 Centre, Zabrze vs. Wroclaw 1.00 0.74–1.36 0.00004 0.99 0.82 0.55–1.20 1.06 0.30 
 Age, 10 years 0.97 0.85–1.11 0.21 0.65 1.03 0.87–1.21 0.10 0.76 
 Sex, men vs. women 1.34 0.82–2.18 1.38 0.24 1.46 0.87–2.43 2.05 0.15 
 BMI, 1 kg/m2 0.95 0.92–0.98 8.49 0.004 1.01 0.97–1.05 0.17 0.68 
 CHF aetiology, ischaemic vs. non-ischaemic 0.82 0.61–1.11 1.62 0.20 1.00 0.71–1.41 0.0001 0.99 
 NYHA class   44.05 <0.001   7.14 0.07 
  IV vs. I 4.52 2.24–9.10 17.81 <0.001 1.86 0.83–4.21 2.24 0.13 
  III vs. I 2.71 1.49–4.94 10.58 <0.001 1.32 0.69–2.56 0.70 0.41 
  II vs. I 1.14 0.61–2.15 0.18 0.68 0.88 0.46–1.70 0.14 0.71 
 LVEF, 1% 0.93 0.91–0.95 41.85 <0.001 0.96 0.94–0.98 11.04 <0.001 
 NT-proBNP, 1 log pg/mL 1.76 1.53–2.02 65.45 <0.001 1.42 1.19–1.71 14.44 <0.001 
 Na, 1 mmol/L 0.93 0.90–0.96 23.75 <0.001 0.96 0.93–0.99 4.00 0.046 
 Diabetes mellitus, yes vs. no 1.26 0.92–1.72 2.06 0.15 1.11 0.80–1.57 0.38 0.54 
 eGFR, 5 mL/min/1.73 m2 0.96 0.94–0.99 5.87 0.02 1.01 0.97–1.04 0.07 0.79 
 Hs-C-reactive protein, 1 log mg/L 1.35 1.16–1.56 15.69 <0.001 1.06 0.88–1.26 0.37 0.54 
 Anaemia,a yes vs. no 1.54 1.10–2.16 6.37 0.01 1.07 0.74–1.54 0.12 0.74 
 ID,b yes vs. no 1.74 1.30–2.33 13.97 <0.001 1.58 1.14–2.17 7.74 0.005 
χ2 of the multivariable model       118.29 <0.001 

 
Events: all-cause death (secondary analyses) 
 Centre, Zabrze vs. Wroclaw 0.76 0.55–1.05 2.78 0.10 1.66 1.09–2.53 5.54 0.02 
 Age, 10 years 1.07 0.92–1.24 0.77 0.38 1.13 0.94–1.36 1.61 0.21 
 Sex, men vs. women 1.45 0.84–2.52 1.78 0.18 1.57 0.88–2.81 2.32 0.13 
 BMI, 1 kg/m2 0.96 0.92–0.99 4.68 0.03 1.02 0.98–1.06 0.94 0.33 
 CHF aetiology, ischaemic vs. non-ischaemic 0.83 0.60–1.16 1.20 0.27 1.00 0.69–1.45 0.0001 0.99 
 NYHA class   40.74 <0.001   10.29 0.02 
  IV vs. I 4.58 2.27–9.22 18.09 <0.001 2.01 0.87–4.64 2.66 0.10 
  III vs. I 2.10 1.14–3.87 5.68 0.02 1.04 0.53–2.04 0.01 0.92 
  II vs. I 0.99 0.52–1.87 0.002 0.97 0.75 0.39–1.46 0.71 0.40 
 LVEF, 1% 0.94 0.92–0.96 24.45 <0.001 0.97 0.94–0.99 6.24 0.01 
 NT-proBNP, 1 log pg/mL 1.81 1.56–2.11 60.14 <0.001 1.47 1.21–1.80 14.34 <0.001 
 Na, 1 mmol/L 0.93 0.90–0.96 19.07 <0.001 0.95 0.91–0.98 7.43 0.006 
 Diabetes mellitus, yes vs. no 1.28 0.91–1.79 1.98 0.16 1.03 0.71–1.50 0.02 0.88 
 eGFR, 5 mL/min/1.73 m2 0.95 0.92–0.98 8.66 0.003 1.01 0.97–1.06 0.49 0.48 
 Hs-C-reactive protein, 1 log mg/L 1.38 1.18–1.61 15.63 <0.001 1.08 0.89–1.32 0.58 0.45 
 Anaemia,a yes vs. no 1.62 1.13–2.33 6.79 0.009 1.07 0.72–1.61 0.11 0.74 
 ID,b yes vs. no 1.74 1.27–2.39 11.63 <0.001 1.58 1.11–2.25 6.37 0.01 
χ2 of the multivariable model       114.72 <0.001 

HTX, heart transplantation; HR, hazard ratio; CI, confidence interval; BMI, body mass index; CHF, chronic heart failure; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; NT-proBNP, N-terminal pro-B type natriuretic peptide; eGFR, estimated glomerular filtration rate; hs-C-reactive protein, high-sensitivity C-reactive protein; ID, iron deficiency.

aAnaemia was defined as haemoglobin level <12 g/dL in women and <13 g/dL in men.

bID was defined as ferritin <100 µg/L, or ferritin 100–300 µg/L and Tsat (transferrin saturation) <20%.

In univariate models, the presence of ID predicted poor outcome in patients with systolic CHF, either when death and HTX or death alone were considered as events in survival analyses (Table 3). When both all-cause death and HTX were considered as events, 3-year event-free survival rates were 54% (95% CI: 46–61%) vs. 67% (95% CI: 61–72%) in patients with vs. without ID (χ2 = 14.34, P = 0.0002) (Figure 2). When only death was considered as an event, 3-year survival rates were 59% (51–67%) vs. 71% (95% CI: 66–77%) in patients with systolic CHF with vs. without ID (χ2 = 11.93, P = 0.0006).

Figure 2

Kaplan–Meier curves reflecting 3-year event-free survival rates in patients with systolic chronic heart failure with vs. without iron deficiency.

Figure 2

Kaplan–Meier curves reflecting 3-year event-free survival rates in patients with systolic chronic heart failure with vs. without iron deficiency.

Multivariable analyses

Iron deficiency remained a significant predictor of death and HTX in patients with systolic CHF also in multivariable models, when adjusted for clinical variables, including the presence of anaemia (Table 3). Iron deficiency was also a predictor of increased all-cause mortality after an adjustment for cofounders (Table 3).

Additive prognostic value of iron deficiency in comparison to New York Heart Association class and plasma N-terminal pro-type B natriuretic peptide

We have compared the χ2 values of the multivariable Cox proportional hazard regression models that included or not the potentially interfering variables, i.e. ID and the NYHA class, ID and plasma NT-proBNP (Table 4). The inclusion of ID as an additional prognosticator to multivariable Cox regression models in patients with systolic CHF resulted in a significant increase in the χ2 values of all these models.

Table 4

Additive prognostic value of the presence of iron deficiency in comparison to New York Heart Association class and plasma N-terminal pro-B type natriuretic peptide (χ2 values for Cox multivariable Cox proportional hazard regression models)

Events Selected group of prognosticators included in multivariable models
 
Significance of differences between χ2 values
 
 A vs. C B vs. D C vs. D A vs. B 
Comparison of ID and NYHA classa 
 Clinical variables Clinical variables + NYHA class Clinical variables + IDb Clinical variables + NYHA class + IDb P-value
 
 Death + HTX (primary analyses) 101.25 109.36 111.82 118.29 0.001 0.003 0.17 0.004 
 Death (secondary analyses) 94.75 107.44 102.98 114.72 0.004 0.007 0.02 <0.001 

 
Comparison of ID and NT-proBNPc 
 Clinical variables Clinical variables + NT-proBNP Clinical variables + IDb Clinical variables + NT-proBNP + IDb P-value
 
 Death + HTX (primary analyses) 94.82 109.36 104.97 118.29 0.001 0.003 <0.001 <0.001 
 Death (secondary analyses) 91.77 107.44 100.46 114.72 0.003 0.007 <0.001 <0.001 
Events Selected group of prognosticators included in multivariable models
 
Significance of differences between χ2 values
 
 A vs. C B vs. D C vs. D A vs. B 
Comparison of ID and NYHA classa 
 Clinical variables Clinical variables + NYHA class Clinical variables + IDb Clinical variables + NYHA class + IDb P-value
 
 Death + HTX (primary analyses) 101.25 109.36 111.82 118.29 0.001 0.003 0.17 0.004 
 Death (secondary analyses) 94.75 107.44 102.98 114.72 0.004 0.007 0.02 <0.001 

 
Comparison of ID and NT-proBNPc 
 Clinical variables Clinical variables + NT-proBNP Clinical variables + IDb Clinical variables + NT-proBNP + IDb P-value
 
 Death + HTX (primary analyses) 94.82 109.36 104.97 118.29 0.001 0.003 <0.001 <0.001 
 Death (secondary analyses) 91.77 107.44 100.46 114.72 0.003 0.007 <0.001 <0.001 

ID, iron deficiency; HTX, heart transplantation; BMI, body mass index; CHF, chronic heart failure; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; NT-proBNP, N-terminal pro-B type natriuretic peptide; Na, sodium; eGFR, estimated glomerular filtration rate; hs-C-reactive protein, high-sensitivity C-reactive protein.

aClinical variables in baseline models: centre, age, sex, BMI, CHF aetiology, LVEF, NT-proBNP, Na, diabetes, eGFR, hs-C-reactive protein, anaemia.

bID was defined as ferritin <100 µg/L, or ferritin 100–300 µg/L and Tsat (transferrin saturation) <20%.

cClinical variables in baseline models: centre, age, sex, BMI, CHF aetiology, LVEF,NYHA class, Na, diabetes, eGFR, hs-C-reactive protein, anaemia.

Discussion

There are two major findings arising from our study. Firstly, ID was common, affecting nearly 40% of the population with systolic CHF recruited for our study. Secondly, we have shown that ID itself, independent of the other already well-established prognosticators, including the presence of anaemia, is related to poor outcome in these patients.

The prevalence and possible consequences of ID complicating CHF syndrome has only recently drawn attention. Data on the epidemiology and pathophysiology of ID in CHF are scarce. Iron deficiency has usually only been considered in the context of anaemia, both generally and in patients with CHF.23,31,32 Thus, to date, the prevalence of ID has been established only in CHF patients with concomitant anaemia. Ezekowitz et al.23 reported that anaemia was present in 17% of incident hospital discharges for heart failure. Iron deficiency was the reported cause of anaemia in 21%.23 Opasich et al.21 demonstrated that among 148 patients with CHF and a low Hb level, majority had anaemia of chronic disease, and in this group nearly all demonstrated defective iron supply for erythropoiesis and/or blunted endogenous erythropoietin production. Nanas et al.22 investigated anaemic patients with advanced CHF admitted to the hospital (NYHA class IV, mean LVEF—22%) and found using bone marrow biopsies that 73% presented with ID.

Patients with CHF are prone to become iron deficient as a consequence of a depletion of iron stores (absolute ID) or more frequently as a result of impaired iron metabolism in the course of inflammatory processes characterizing CHF (functional ID).13,16,32,33 In CHF, there is an activation of proinflammatory cytokines that block intestinal absorption of iron and divert iron from the circulation into the reticuloendothelial system, causing reticuloendothelial block.32 Hepcidin, a small hepatic peptide, secreted in response to proinflammatory cytokines, seems to play a key role in the control of these processes.34,35 Decreased intestinal iron absorption together with its accumulation within the reticuloendothelial stores reduces iron availability to its target tissues and organs.32 Thus, functional ID may occur despite adequate iron stores in the body, in contrast to absolute ID, when the body iron stores are significantly depleted. In the present study, we have applied a definition of ID taking account of both absolute (serum ferritin <100 µg/L) and functional ID (serum ferritin ≥100 µg/L and ≤300 µg/L when Tsat <20%). Similar definitions have been already applied in recent intervention trials, which showed that repletion of ID resulted in improvement in exercise capacity and quality of life.19,24–28 Using this definition, we have demonstrated that the prevalence of ID in the whole cohort of CHF patients was 37 ± 4%, with a significant difference between anaemic vs. non-anaemic patients—57 ± 10 vs. 32 ± 4%, respectively. The high prevalence of ID in non-anaemic patients is a new and important finding. Additionally, we have identified also the following variables associated with ID: female sex, advanced NYHA class, high plasma NT-proBNP, and high serum hs-C-reactive protein. Even in subgroups that have been shown to be characterized by the lower prevalence of ID (e.g. men, those in NYHA class I–II), the frequency of ID diagnosis did not drop below 30% (Figure 1).

Anaemia was established as a strong risk factor of increased mortality in patients with cardiovascular disease, including CHF, a long time ago.23,31,36,37 It has been a subject of dispute as to what extent ID might be responsible for anaemia in these subjects. In contrast, our report is the first one providing evidence that ID independent of anaemia also poses detrimental effects on prognosis in patients with CHF. Interestingly, the impact of ID on outcome in patients with CHF appeared to be significantly stronger for a 6-month follow-up as compared with a 3-year follow-up (data not shown). Moreover, the inclusion of ID as an additional prognosticator to multivariable Cox regression models in patients with systolic CHF resulted in a significant increase in the χ2 values of these models. It was demonstrated that ID had the significant and independent input to the survival models in patients with CHF, either when anaemia was or was not included as a covariable, and either death and HTX or death alone were considered as events. In contrast, the inclusion of anaemia as an additional prognosticator to multivariable models did not change significantly the χ2 values, indicating the minor significance of this variable as a potential independent predictor of events in the studied cohort.

In a multivariable logistic regression model, we have shown that patients with ID have higher plasma NT-proBNP and there is a borderline trend towards the more advanced NYHA class in these patients. As there might be interactions between these variables, we have estimated an independent incremental input of these pairs of prognosticators (ID and NYHA class, ID and plasma NT-proBNP) and demonstrated that ID had significant and independent input to the survival models in patients with CHF, beyond the set of clinical variables including or not the NYHA class or plasma NT-proBNP.

We may presume that this pathology within iron metabolism would be more prevalent and have more marked prognostic negative consequences in a general population of patients with CHF. Taking this into consideration, the results of our study suggest that in the assessment of patients with systolic CHF, laboratory biomarkers reflecting ID may be useful in routine practice to stratify the risk of subsequent outcome.

Limitation of the study

It should be emphasized that our cohort differs from the general population of patients with systolic CHF. In real life, such patients are older, more frequently females and have frequent comorbidities. Thus, the prevalence of ID observed in our cohort is probably an underestimate of the true frequency of ID in a population of patients with CHF in real life. Indeed, it is confirmed by the observation from Scotland, where the prevalence of ID diagnosed using the same definition among unselected population of stable CHF reached nearly 50% (J.J.V. McMurray et al., unpublished results).

The observational character of our study needs to be acknowledged. The study was not designed to elucidate the underlying detrimental mechanisms of ID in patients with systolic CHF. No simple explanation is evident to explain the findings. We hypothesize that ID with subsequent impairment in iron metabolism is not only directly related to impaired erythropoiesis, but also to oxidative metabolism, cellular energetics and cellular immune mechanisms may play a role.1–8 There are several lines of evidence proving that iron is an exceptional micronutrient, essential for survival on the level of cells, tissues, and the whole organism, and deranged iron metabolism affects critically homeostasis.1–3,17 Iron is able to shuttle between two oxidative states (ferric and ferrous iron), which makes it an efficient cofactor of enzymes and the catalyst of numerous biochemical reactions irreplaceable by any other micronutrient. Therefore, iron stands in the centre of cellular metabolism and provides an enzymatic platform for optimal energetics and oxidative balance across various tissues, being also involved in the synthesis and degradation of lipids, carbohydrates, DNA, and RNA.1–4,17

Impaired energy metabolism is a feature of CHF syndrome. Thus, we hypothesize that patients with CHF may become particularly susceptible to any abnormalities in iron metabolism, which further aggravates already impaired energetics and oxidative balance, having further unfavourable functional consequences. There is evidence from experimental studies, that molecular elements of the iron metabolism system are present within healthy and diseased myocardium38–40 and ID-induced aberrations within the cardiovascular system have been described.38,41,42 Left ventricular hypertrophy and dilatation occurring in iron-deficient rats is accompanied by disrupted energetics and oxidative imbalance in exercising myocardium.41 In an experimental rat model, an induction of ID and anaemia results in a depletion of available iron within myocardium, oxidative stress, inflammation, apoptosis along with myocardial remodelling and heart dysfunction.38 There is also evidence suggesting that normal iron status, irrespective of haemoglobin level, determines endurance and optimal energetics of skeletal muscles.18 However, the precise mechanisms underlying such ID-induced changes still remain unknown. Particularly, it is not clear to what extent such maladaptive changes are due to low haemoglobin level (ID anaemia) or related to depleted iron stores themselves. Further studies are warranted.

Clinical perspectives

Current guidelines for the management of CHF provide no specific recommendations, neither for the evaluation of iron status nor for potential repletion of ID in patients with CHF who demonstrate ID.43 To date, five studies have reported benefits in functional status from iron therapy in patients with CHF, in three of them reduced haemoglobin level was one of inclusion criteria.19,24–28 The presented results may become the premises to consider an iron supplementation as a therapeutic approach in patients with CHF regardless of anaemia, aiming at an improvement in prognosis. This hypothesis needs to be prospectively verified.

Conclusions

In patients with systolic CHF, ID is common and constitutes a predictor of unfavourable outcome, irrespective of the presence of anaemia and the severity of heart disease. Further studies are needed to explain the origin of depleted iron store seen in the course of heart failure and the detailed pathophysiological mechanisms linked to detrimental effects of ID. Pharmacological interventions aimed to optimally replete ID in patients with CHF will be a challenging task.

Funding

This research was financially supported by the Ministry of Science and Higher Education (Poland) grant no. 4022/B/T02/2008/34.

Conflict of interest: A.W. reports receiving fee from Vifor Pharma. G.F. reports receiving grants from Vifor Pharma. S.D.A. reports receiving consulting fees from Amgen, Inc., Fresenius Kabi, Professional Dietetics, Vifor Pharma, and honoraria from Amgen, Inc., Fresenius Kabi, and Vifor Pharma. P.P. reports receiving consulting fees from Vifor Pharma and Amgen, Inc., honoraria from Vifor Pharma, and travel/accommodation expensed covered by Vifor Pharma and Amgen, Inc. All the other authors report no conflict of interest related to the content of this manuscript.

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Comments

2 Comments
Iron supplementation to correct iron deficiency in patients with systolic chronic heart failure
26 July 2010
Dietmar Fuchs (with Katharina Kurz, Guenter Weiss)

With great interest we read the recent article on iron deficiency (ID) in patients with systolic chronic heart failure (CHF) by Jankowska et al. [1] ID was more prevalent in CHF patients with advanced NYHA class, with higher plasma N-terminal pro-type B natriuretic peptide and higher serum C-reactive protein concentrations. Moreover, in multivariable models, ID was related to an increased risk of heart transplantation and/or death. Authors concluded that iron supplementation may be considered as a therapeutic approach in these patients to improve prognosis. There is some doubt to be raised on the background of ID in these patients. The association of ID with higher CRP suggests a link to inflammation and immune activation, which play a prominent role in the pathogenesis of CHD. In fact, a disturbed iron metabolism together with inflammation and immune activation have been observed in various diseases such as infections, autoimmune syndromes and also malignant diseases [2]. Such clinical conditions go along with an activation of T-cells and macrophages which is reflected by, e.g., elevated neopterin concentrations. This association is of particular interest because not only New York Heart Association class of CHF patients is associated with higher neopterin concentrations, but also abnormalities of left ventricle parameters have been reported to be strongly associated with elevated neopterin serum levels [3,4]. Of note, an inverse relationship between iron availability and neopterin concentrations has been documented in several groups of patients including HIV infection and several malignant tumor diseases: patients with elevated neopterin are more likely to present with low circulating iron and lower transferrin saturation [2]. In patients with anemia ferritin concentrations <30 microg/L are established to be indicative for iron deficiency anemia, while ferritin concentrations >100 microg/L are found in patients with anemia of chronic disease [2]. Thus, we think that the authors' definition of iron deficiency is incorrect and suppose that higher CRP concentrations in patients with 'iron deficiency' rather reflect transfer of iron from sites of erythropoiesis to the reticuloendothelial system (RES) going along with low iron and high ferritin concentrations. Iron regulatory changes are induced during immune response in order to deprive invading pathogens or tumor cells from the essential metal nutrient iron to limit their growth [4]. Furthermore, in vitro studies demonstrate that iron availability also influences immune effector functions: In an iron-deprived situation, macrophages respond stronger to stimulation with Th1-type cytokine interferon-gamma, e.g., enzyme pathways driven by interferon-gamma like neopterin production or activity of tryptophan degrading enzyme indoleamine 2,3-dioxygenase are super-induced in iron-deficiency states [5]. As a net effect, cellular and microbial growth are further restricted. Vice versa, when iron is supplemented, pro-inflammatory cascades are dampened. Therefore, iron supplementation under inflammatory conditions might be effective to slow down deleterious effects of immune activation, which seem to be deeply involved in the pathogenesis of CHD, but in fact iron supplementation may not correct inflammatory anemia due to retention of the metal within the RES, supplemented iron will only insufficiently reach the sites of erythropoiesis but likewise increase the risk for infections.

REFERENCES

[1] Jankowska EA, Rozentryt P, Witkowska A, Nowak J, Hartmann O, Ponikowska B, Borodulin-Nadzieja L, Banasiak W, Polonski L, Filippatos G, McMurray JJ, Anker SD, Ponikowski P. Iron deficiency: an ominous sign in patients with systolic chronic heart failure. Eur Heart J 2010 (in press)

[2] Weiss G, Goodnough LT. Anemia of chronic disease. New Engl J Med 2005,352:1011-1023

[3] Rudzite V, Skards JI, Fuchs D, Reibnegger G, Wachter H. Serum kynurenine and neopterin concentrations in patients with cardiomyopathy. Immunol Lett 1992;32:125-130

[4] Barani J, Mattiasson I, Lindblad B, Gottsaeter A. Cardiac function, inflammatory mediators and mortality in critical limb ischemia. Angiology 2006;57:437-444

[5] Weiss G, Fuchs D, Hausen A, Reibnegger G, Werner ER, Werner- Felmayer G, Wachter H. Iron modulates interferon-gamma effects in the human myelomonocytic cell line THP-1. Exp Hematol 1992;20:605-610

Conflict of Interest:

None declared

Submitted on 26/07/2010 8:00 PM GMT
Re:Iron supplementation to correct iron deficiency in patients with systolic chronic heart failure
14 November 2010
Christopher J Boos

I read with interest your article investigating the prevalence of iron (Fe) deficiency among both anaemic and also non-anaemic patients with heart failure.1 The authors noted that Fe deficiency was present in 37+4% of their entire HF cohort and in 32+4 vs. 57+10% among subjects without vs. with anaemia. This is quite striking and was observed despite excellent background heart failure treatment (95% on angiotensin converting enzyme inhibitors / angiotensin II receptor blockers, 98% on beta blockers and 73% on aldosterone antagonists).

Subgroup comparisons with in the paper would strong suggest that the Fe deficient group were more symptomatic (despite similar ejections fractions) with 53% in NYHA III/IV heart failure and sicker with higher Hs -C-reactive protein and NT-proBNP levels compared with the non Fe deficient group despite similar high intensity of background heart failure medication.

This appears to further support the rationale for consideration of Fe replacement among these patients. Unfortunately, whilst Fe absorption is affected by HF there is a need to consider a trial of oral Fe replacement given the size and cost implications of treating such a large cohort. Moreover, it is currently unknown whether merely improving heart failure treatment per se might reduce the incidence of Fe deficiency. For example, it has been shown that angiotensin II may play a key role in functional Fe deficiency in an animal model.2

References

1. Jankowska EA, Rozentryt P, Witkowska A, Nowak J, Hartmann O, Ponikowska B, Borodulin-Nadzieja L, Banasiak W, Polonski L, Filippatos G, McMurray JJ, Anker SD, Ponikowski P. Iron deficiency: an ominous sign in patients with systolic chronic heart failure. Eur Heart J. 2010;31:1872- 80.

2. Ishizaka N, Saito K, Noiri E, Sata M, Ikeda H, Ohno A, Ando J, Mori I, Ohno M, Nagai R. Administration of ANG II induces iron deposition and upregulation of TGF-beta1 mRNA in the rat liver. Am J Physiol Regul Integr Comp Physiol 2005 ;288:R1063-70.

Conflict of Interest:

None declared

Submitted on 14/11/2010 7:00 PM GMT