Relationship between serum iron level and physical function in heart failure patients is lost by presence of diabetes

Abstract

Aims

Iron deficiency (ID) is common in patients with heart failure (HF) and is reportedly associated with exercise intolerance and impaired quality of life. Iron supplementation therapy in HF patients with ID improves exercise capacity. Conversely, protective roles of iron depletion in the development of diabetes mellitus (DM) and its complications have been proposed. This study aimed to determine the impact of ID on physical function in HF patients with and without DM.

Methods and results

We enrolled consecutive patients who were admitted to our institute for HF diagnosis and management. The short physical performance battery (SPPB) was used to evaluate physical function, and low physical function was defined as an SPPB score of <10 points as individuals with SPPB scores of <10 points are most likely to be classified as frail and are at high risk for disability and future adverse events, including death. ID was defined as serum ferritin < 100 or 100–299 ng/mL when transferrin saturation (TSAT) was <20% according to the HF guidelines. Among the 562 HF patients (72 ± 14 years old; 56% male), 329 patients (58%) and 191 patients (34%) had ID and low physical function, respectively. Multivariate logistic regression analysis showed that TSAT as a continuous variable, but not ID, was a predictor of low physical function (odds ratio: 0.980, P = 0.024). Subgroup analysis showed that a significant association between low TSAT and low physical function was lost in HF patients with DM (P for interaction < 0.001). A spline dose–response curve for the relationship between TSAT and risk of low physical function with adjustments for covariates associated with low physical function in non‐DM patients was almost linear with an increase in the risk of low physical function as the TSAT increased, but such a relationship was not found in the analyses of DM patients. A lack of close TSAT–SPPB relationship in HF patients with DM was confirmed also in a propensity‐score‐matched cohort.

Conclusions

TSAT as a continuous variable, but not ID, was independently associated with physical function in HF patients, and a significant association was lost in patients with HF and DM, suggesting a limited impact of iron supplementation therapy in HF patients with DM.

Introduction

Heart failure (HF) is a systemic disorder affecting approximately 26 million people worldwide, and it is a leading cause of morbidity and mortality.^1,2 The primary event of HF is reduction in cardiac output and elevated ventricular filling pressure, leading to systemic disorders, such as renal dysfunction, chronic inflammation, and malnutrition. Among them, declined physical function leading to frailty and sarcopenia has received much attention as it is frequently observed in patients with HF, especially in elderly HF patients.^3–6 Physical function, which is defined as the capacity to perform physical activities of daily living, is an independent predictor of functional independence, disability, morbidity, and mortality, and maintenance of physical function is a common target for treating multiple diseases including HF.^3–7 Although favourable effects of comprehensive cardiac rehabilitation on clinical outcomes, including reduced physical function, have been shown,^8,9 no additional therapy has focused on improving physical function.

Iron is a highly abundant element in the human body and is pivotal for various physiological functions such as erythropoiesis and oxidative metabolism including mitochondrial respiration.^10–13 Although a typical manifestation of iron deficiency (ID) is iron-deficiency anaemia, maintenance of iron metabolism is necessary for the proper cellular functioning, especially cells subjected to high energy demand, such as cardiomyocytes and skeletal myocytes.^10–14 Indeed, ID is associated with increased mortality and reduced quality of life (QOL) in patients with HF regardless of the presence of anaemia.^15–18 However, conflicting findings have also been reported: the presence of ID was not necessarily an explanatory factor for exercise capacity in patients with HF with preserved ejection fraction (HFpEF).^19,20 Thus, the relationship between iron level and physical function may not be straightforward and may be modulated by HF co-morbidities. Intriguingly, the protective roles of iron depletion in the development of diabetes mellitus (DM) and its complications have been proposed.^21–23 This is a critical issue as patients with DM have been shown to have an approximately two- to four-fold higher risk of incident HF, and the presence of DM is a strong risk factor for reduced physical function, HF hospitalization, cardiovascular death, and all-cause mortality in patients with DM.^24,25

The study aimed to determine the impact of serum iron level on physical function using the short physical performance battery (SPPB) in patients with HF. The SPPB is a well-established tool for assessing physical function, frailty, and QOL in addition to all-cause mortality.^26–30 Herein, we analysed the dose-dependent association between serum transferrin saturation (TSAT), an ID index, and SPPB to determine an optimal TSAT level cut-off value for maintaining physical function in patients with HF. The impact of DM on the association of ID with physical function was analysed.

Methods

Study subjects

This study was a single-centre, ambispective (combined retrospective and prospective), and observational study. We retrospectively enrolled consecutive patients who were admitted to our institute for HF diagnosis and management and underwent SPPB assessment between 1 January 2016 and 1 October 2022. The retrospective study was conducted between 1 January 2016 and 10 April 2019, and the prospective study was conducted between 11 April 2019 and 1 October 2022. HF was diagnosed according to the 2016 European Society of Cardiology Guidelines for diagnosing and treating acute and chronic HF.³¹ Patients with serum ferritin concentration > 1000 ng/mL and missing data were excluded (Figure 1). This study was conducted in strict adherence to the principles of the Declaration of Helsinki and was approved by the Clinical Investigation Ethics Committee of Sapporo Medical University Hospital (Number 302-243).

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Biochemical analysis, echocardiography, and muscle mass assessment

Patient information, such as DM diagnosis and data for blood tests, including data for N-terminal pro-brain natriuretic peptide (NT-proBNP), TSAT, and ferritin after stabilization of HF, were collected from the patients' medical records. TSAT was calculated as the ratio of serum iron concentration to serum total iron-binding capacity. ID was defined as either serum ferritin concentration < 100 or 100–299 ng/mL with TSAT < 20% according to the definition by HF guidelines.^31,32 Anaemia was defined as a haemoglobin concentration of <13.0 g/dL in men and <12.0 g/dL in women. Creatinine-based estimated glomerular filtration rate (eGFR) was calculated using the following equation developed for Japanese patients: eGFR (mL/min/1.73 m²) = 194 × Scr^−1.094 × age^−0.287(×0.739 if woman).³³ Transthoracic echocardiography was performed by the standard protocol, and the left ventricular ejection fraction (LVEF) was measured using the modified Simpson method. HF with reduced ejection fraction (HFrEF) and HFpEF were defined as LVEF < 40% and LVEF ≧ 50%, respectively.

Whole and regional lean masses of patients were analysed by using the Horizon A DXA System (HOLOGIC, Waltham, MA, USA) as previously reported,^34,35 and lean mass was defined as a muscle mass index. Appendicular skeletal muscle mass (ASM) was calculated as the sum of bone-free lean masses in the arms and legs. The ASM index (ASMI) was defined as ASM/height². The cut-off values of ASMI for muscle wasting were <7.00 and <5.40 kg/m² in men and women, respectively, according to the criteria of the Asian Working Group for Sarcopenia.³⁶

Assessment of nutritional status

Nutritional status after stabilization of HF was assessed using the Mini Nutritional Assessment Short-Form (MNA-SF), as previously described.^37,38 The MNA-SF comprises six questions about reduced food intake over the past 3 months, weight loss during the past 3 months, mobility, psychological stress or acute disease in the past 3 months, neuropsychological problems, and body mass index (BMI). The MNA-SF is scored 0–14, and nutritional status is categorized as normal nutritional status, at risk of malnutrition, and malnourished based on the MNA-SF scores of 12–14, 8–11, and 0–7, respectively, as previously described.^37,38

Assessment of short physical performance battery and gait speed

As previously reported, trained personnel assessed SPPB after HF stabilization.^27–29 SPPB comprises three components: (i) balance tests in a side-by-side stand, semi-tandem stand, and tandem stand for assessing whether or not patients can maintain their balance for at least 10 s with their feet together; (ii) 4 m gait speed test; and (iii) a repeated chair stand test for assessing lower extremity strength by measuring the time it takes to sit down and stand up five times. SPPB is scored 0–12 and the extent of limited physical function is generally categorized as no, minimal, mild, moderate, and severe based on SPPB scores of 10–12, 7–9, 4–6, and 0–3, respectively, based on results of epidemiological studies.²⁶ Additionally, results of previous studies show that individuals with SPPB scores of <10 points are most likely to be classified as frail and are at high risk for disability and future adverse events, including death.^26–30 Therefore, we defined low physical function as an SPPB score of <10.

Usual gait speed was assessed by having the patients walk at their usual pace over 14 m and calculating the gait speed during the middle 10 m.

Statistical analysis

Data are presented as means (standard deviations) and medians [interquartile ranges (IQRs): 25th–75th percentile] as appropriate and expressed as frequency and percentage. Intergroup differences for continuous variables and categorical variables were tested using the unpaired Student's t-test or Welch's t-test. All variables that did not have a normal distribution were logarithmically transformed for regression analyses. Univariate and multivariate logistic regression analyses were used to evaluate the predictors of low physical function. The dose-dependent associations of TSAT with SPPB were examined using an ordinal regression analysis with a restricted cubic spline function with four knots, as previously described with slight modifications.³⁷ Propensity score matching (1:1 match, nearest neighbour matching, c-statistics = 0.75) was performed according to potential covariates [age, sex, ASMI, LVEF, MNA-SF, HF aetiology, albumin, haemoglobin, eGFR, NT-proBNP, ferritin, and use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACE-Is/ARBs)], as we previously performed,³⁴ and a standardized mean difference of >0.1 was considered meaningful. The statistical significance level was set to P < 0.05. Statistical analyses were performed using JMP Version 14.3.0 (SAS Institute Inc., Cary, NC, USA) and R Version 3.6.2 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Five hundred eighty-six patients met the inclusion criteria, and 24 patients were excluded based on the exclusion criteria. Thus, data from 562 patients were used for the analyses, as shown in Figure 1.

Baseline clinical characteristics and prevalence of iron deficiency and anaemia in heart failure patients

Table 1 shows that the mean age of the patients was 72 ± 14 years and that 56% of the patients were male. The median BMI was 22.5 kg/m² (IQR: 20.0–24.8 kg/m²). Thirty-four per cent of the patients were classified as New York Heart Association class III. The mean LVEF was 46%, and 39% and 45% of the patients met the criteria for HFrEF and HFpEF, respectively. The most frequent HF aetiology was cardiomyopathy (38%), followed by valvular heart disease (34%) and ischaemic heart disease (16%).

Table 1 Patients' background

N	562
Age, years	72 (14)
Male, n (%)	315 (56)
Height, cm	158 (10)
BMI, kg/m2	22.5 [20.0–24.8]
ASMI, kg/m2	5.88 [5.11–6.82]
Muscle wasting, n (%)	347 (61)
SPPB, point	11 [8–12]
Low physical function, n (%)	191 (34)
LVEF, %	46 [32, 62]
LVEF ≥ 50, n (%)	251 (45)
NYHA class III, n (%)	190 (34)
MNA-SF, point	9 [7–11]
Co-morbidity, n (%)
Diabetes mellites	227 (40)
Hypertension	366 (65)
Dyslipidaemia	293 (52)
Atrial fibrillation	242 (43)
Aetiology, n (%)
Cardiomyopathy	216 (38)
Valvular heart disease	195 (34)
Ischaemic heart disease	93 (16)
Other	58 (10)
Laboratory data
Albumin, g/dL	3.6 [3.4–3.9]
Uric acid, mg/dL	5.8 [4.7–7.0]
Haemoglobin, g/dL	12.0 [10.6–13.7]
eGFR, mL/min/1.73 m2	58.2 [40.2–76.4]
NT-proBNP, pg/mL	1279 [522–3018]
Serum iron, mg/dL	67.0 [46.0–92.0]
TSAT, %	22.4 [14.5–30.4]
Ferritin, ng/mL	103 [45–216]
Medications, n (%)
Beta-blocker	356 (63)
ACE-I or ARB	295 (52)
MRA	245 (43)
Loop diuretics	327 (58)

The number of patients with ID and anaemia was 329 (59%) and 339 (60%), respectively (Figure 2). Among the 329 patients with ID, 221 patients, 39% of all HF patients, did not fail the diagnostic criteria of anaemia (Figure 2).

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Relationship between iron status and physical function assessed by short physical performance battery

In univariate logistic regression analyses, anaemia, haemoglobin concentration, ID, and TSAT, except ferritin level, were significantly associated with low physical function, that is, SPPB score of <10 (Table 2 and Supporting Information, Table S1). Conversely, only TSAT was selected as an independent explanatory factor for the presence of low physical function in the multivariate logistic regression models into which age, sex, ASMI, LVEF, HF aetiologies, NT-proBNP, eGFR, DM, albumin, MNA-SF, and ACE-I/ARB use were incorporated as covariates (Table 2). A spline dose–response curve for the relationship between TSAT and risk of low physical function with adjustments for age, sex, ASMI, LVEF, HF aetiologies, NT-proBNP, eGFR, DM, albumin, nutritional status, and ACE-I/ARB use in addition to ferritin was almost linear with an increase in the risk of low physical function as TSAT increased (Figure 3).

Table 2 Logistic regression analyses for low physical function

	Univariate model	Multivariate model
Odds ratio	95% CI	P value	Odds ratio	95% CI	P value
Anaemia, yes	2.122	1.458–3.090	<0.001	1.096	0.684–1.755	0.704
Haemoglobin, g/dL	0.777	0.707–0.853	<0.001	0.962	0.848–1.092	0.546
Iron deficiency, yes	1.604	1.116–2.305	0.011	1.031	0.676–1.573	0.885
Log (ferritin)	0.721	0.492–1.058	0.094	1.063	0.673–1.680	0.792
TSAT, %	0.969	0.953–0.985	<0.001	0.980	0.963–0.997	0.023

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The impact of TSAT on decreased physical function in the subgroups of interest was examined (Figure 4). No significant difference in the odds ratios for low physical function among the subgroups, including subgroups for age, sex, and LVEF (HFpEF or non-HFpEF), was found, but TSAT has heterogenic effects on low physical function when HF patients were subdivided into DM and non-DM patients: the significant relationship between TSAT and SPPB was lost in HF patients with DM (Figure 4).

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Impact of diabetes mellitus on the transferrin saturation–short physical performance battery relationship in patients with heart failure

Supporting Information, Table S2 shows that HF patients with DM were older than HF patients without DM and that the percentages of HF patients with DM who had hypertension, dyslipidaemia, and ischaemic heart disease were higher than those of HF patients without DM. ASMI and prevalence of muscle wasting were lower in HF patients with DM than in HF patients without DM, being consistent with our previous findings.³⁹ SPPB score was lower in HF patients with DM than in HF patients without DM, indicating low physical function in DM. LVEF values were comparable in the two groups, but MNA-SF score, albumin concentration, and eGFR were lower, and NT-proBNP was higher in HF patients with DM than in HF patients without DM. Furthermore, there were differences in serum iron status: serum iron, TSAT, and ferritin concentrations were lower in HF patients with DM than in HF patients without DM. The number of DM patients with ID and anaemia was 151 (66%) and 152 (67%), respectively (Supporting Information, Figure S1).

Considering the heterogeneity of baseline characteristics between DM and non-DM patients, two approaches were attempted to demonstrate the impact of DM on the TSAT–SPPB relationship. First, spline dose–response curves with adjustments for age, sex, ASMI, LVEF, HF aetiologies, NT-proBNP, eGFR, DM, albumin, MNA-SF, ferritin, and ACE-I/ARB use were separately analysed in HF patients with DM and those without DM. Consistent with the data derived from all the HF patients, the spline dose–response curve for the relationship between TSAT and risk of low physical function with adjustments for covariates in non-DM patients was almost linear with an increase in the risk of low physical function as TSAT increased. However, such a relationship was absent in the analyses of patients with DM (Figure 5A,B).

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Next, the differences in baseline characteristics between DM and non-DM patients were minimized by using propensity score matching. Consequently, the differences in the incorporated covariates were significantly improved (Supporting Information, Table S3). The results of the spline dose–response curve analyses in the propensity-score-matched cohort also showed a lack of an almost linear TSAT–SPPB relationship in HF patients with DM (Figure 5C,D).

Impact of diabetes mellitus on the relationship between transferrin saturation and gait speed in heart failure patients

The results of the analyses using generalized linear models in which all patients were included showed that TSAT, but not anaemia, haemoglobin concentration, or ferritin level, was selected as an independent explanatory factor for gait speed (Supporting Information, Table S4). However, a close association between TSAT and gait speed was absent in patients with HF and DM (Supporting Information, Table S4), being consistent with the results of analyses in which SPPB served as a physical function indicator.

Discussion

The prevalence of ID in this study cohort was similar to that in previous studies. Physical function assessed using SPPB correlated linearly with TSAT. However, such a relationship between physical function and haemoglobin or ferritin concentration was absent. TSAT as a continuous variable, but not ID, anaemia, or ferritin concentration, was an independent predictor of low physical performance in the model adjusted for confounders that affect physical function including NT-proBNP, renal function, and muscle mass. Conversely, a close association between TSAT and physical function was lost in HF patients with DM. This is the first study showing the lack of an iron–physical function relationship in patients with HF and DM.

Significance of iron deficiency in heart failure patients

Solid evidence shows an association between ID and reduced exercise capacity using a cardiopulmonary exercise test and a 6 min walking test.^15,16 However, ID was not selected as an independent predictor of low physical performance using SPPB. Instead, TSAT, as a continuous variable, was selected as an independent explanatory factor for low physical function in patients with HF (Table 2). Although there are several definitions of ID, the ferritin concentration-based diagnosis of ID is widely accepted in HF patients,^31,32 and it was used in this study. Ferritin is a carrier of most of the iron in the blood, but serum ferritin is also an inflammatory marker: serum ferritin concentration is elevated in chronic inflammatory conditions, including HF.⁴⁰ ID in patients with hyperferritinaemia was demonstrated in a study using a diagnosis based on bone marrow biopsy, that is, the gold standard for diagnosing ID.⁴¹ Noteworthy, serum ferritin concentration is elevated in older adults, possibly through age-associated subclinical inflammation.⁴² Altogether, serum ferritin concentration is not an ideal surrogate marker of iron status in the body, especially when it is complicated by chronic inflammatory conditions, including those associated with age. Thus, a significant linear relationship between SPPB and TSAT, but not ferritin, was expected in this study, considering the many elderly HF patients included in the study. Therefore, if the ferritin concentration-based diagnosis of ID, which has been adopted in HF guidelines,^31,32 is used to detect candidates for iron supplementation therapy, some patients, especially elderly HF patients, who would receive benefits in terms of physical function from iron supplementation might be missed. Conversely, there are conflicting data regarding the relationship between serum iron status and prognosis. A study by Grote Beverborg et al. demonstrated that low iron storage, defined as a bone marrow-validated combination of TSAT < 20% and a serum ferritin concentration of ≤128 ng/mL, was an independent predictor of all-cause mortality or HF hospitalization, whereas defective iron utilization, defined as TSAT < 20% and a serum ferritin concentration of >128 ng/mL, was not.⁴³ In contrast, a study by Masini et al. showed that serum ferritin concentration of <100 ng/mL tended to be associated with lower mortality.⁴⁴ Further analyses to demonstrate the complex relationship between serum iron status and clinical outcomes in patients with HF are needed.

Mechanism of a lack of an independent association between transferrin saturation and physical function in patients with heart failure and diabetes mellitus

In this study, the mechanism of the lack of an independent association of TSAT with physical function in patients with HF and DM was not characterized. However, it is not merely attributable to significant differences in baseline characteristics between HF patients with DM and those without DM because the lack of a linear correlation between TSAT and SPPB score in HF patients with DM was shown using the spline dose–response curve analysis with adjustments for covariates, including renal function and nutritional status (Figure 5B,D).

In studies using skeletal muscle tissue, the skeletal muscle of patients with HF and DM showed more skeletal muscle atrophy, lower mitochondrial respiratory capacity, increased mitochondria-derived reactive oxygen species (ROS), and reduced gene expression of antioxidants compared with patients with HF or DM alone.⁴⁵ As mitochondrial iron overload is also considered as a major mechanism for increased mitochondria-derived ROS,¹² the skeletal muscle of patients with HF and DM is probably highly susceptible to a mild increase in iron levels, leading to further oxidative stress in the skeletal muscle, which then contributes to impaired physical function. This is assumed to be the main reason for the lack of a linear correlation between the TSAT and SPPB scores in HF patients with DM. Furthermore, the regulation of serum iron status in DM is highly complex. Consistent with the study's findings, TSAT is low in obese, prediabetic, and DM patients in previous studies, although a contradicting finding also exists.^46–49 Hepcidin, a circulating antimicrobial peptide, is primarily produced by the liver and regulates iron metabolism by inhibiting intestinal iron absorption and ferroportin-mediated cellular iron export; that is, hepcidin negatively controls serum iron status.^12,49 Activation of inflammatory pathways, mainly the interleukin-6 pathway, promotes hepcidin synthesis, reducing serum iron levels and iron accumulation in the tissue.⁵⁰ Thus, reduced serum iron content in patients with DM may be explained by the up-regulation of hepcidin synthesis by subclinical inflammation. Conversely, insulin positively regulates hepcidin synthesis in the liver, and impaired insulin receptor signalling caused by perturbation of insulin secretion and abnormality of the downstream pathway of the insulin receptor theoretically down-regulates the hepcidin–ferroportin axis.⁴⁹ Thus, as serum and tissue iron contents in DM are likely context dependent (duration of DM, types of DM, obese or lean, gender, and presence of complications), TSAT is not necessarily a surrogate marker of tissue iron content in patients with DM. Therefore, proper markers of serum and tissue iron contents in patients with DM should be explored in the future.

Insight into iron supplementation therapy in heart failure patients with diabetes mellitus: favourable or detrimental?

Although much attention has been given to iron depletion in the treatment for HF, excess iron, that is, iron overload, causes oxidative stress by catalysing the toxic hydroxy-radical production via the Fenton reaction, causing cell damage and malfunction.^14,22 Several evidences suggest the involvement of iron overload in DM pathophysiology and its complications. Systemic/mitochondrial iron overload induced by genetic disorders, such as mutations in the gene encoding the hereditary hemochromatosis protein, and repetitive transfusion reduces insulin secretion through β-cell dysfunction and provokes insulin resistance, causing DM development.²² An association between subclinical iron overload assessed using serum markers and the onset of DM has been shown in multiple studies, and a causal relationship was confirmed in studies using iron chelators, iron-deficient diets, and bloodletting: interventions that reduce iron storage improve glycaemic control.^22,51 This is the case with DM complications: treatment with iron chelators improves the clinical manifestations of diabetic nephropathy and vascular dysfunction, whereas iron supplementation therapy contributes to vascular oxidative stress and atherosclerosis progression in patients with end-stage renal diseases.^22,52 Intriguingly, the results of a double-blind, placebo-controlled, randomized trial showed that the therapy with disodium ethylenediaminetetraacetic acid, an iron chelator, in patients with a history of acute myocardial infarction is associated with a significantly reduced composite of mortality, stroke, and coronary events and that statistically greater benefits were indicated in patients with DM.⁵³ Although clinical data showing the effect of iron chelation on skeletal muscle function in DM are limited, dietary iron restriction has been shown to improve skeletal muscle function by reducing oxidative stress in streptozotocin-induced diabetic rats.⁵⁴ Altogether, these untoward effects of iron on DM and its complications might have an impact on the lack of a linear correlation between TSAT and SPPB in HF patients with DM. More importantly, the HF guideline-recommended iron supplemental therapy may cause severe consequences including reduced physical function in HF patients with DM. Subgroup analyses of randomized trials for analysing the effects of iron supplementation using the presence and absence of DM may resolve this issue.

Limitations

This study had several limitations. First, because this study was an observational and cross-sectional study conducted in a single centre, there may have been selection bias. Although differences in baseline characteristics between the DM and non-DM patients were adjusted in the spline dose–response curve analyses, inevitable biases may exist. Second, due to the small number of study subjects, the study's statistical power may be insufficient to detect differences in the TSAT–SPPB relationship among the groups with different aetiologies of HF, for example, HFrEF vs. HFpEF or ischaemic vs. non-ischaemic cardiomyopathy. Third, the effects of diabetic medications on iron status and physical function were not considered in this study. Recent studies have suggested that metformin use is associated with the development of anaemia in patients with type 2 DM.⁵⁵ In contrast, sodium–glucose co-transporter 2 inhibitors were shown to be associated with increased haemoglobin concentration in patients with HF.⁵⁶ However, the effects of these drugs on iron status remain unclear. Fourth, the analyses were not adjusted using erythropoiesis-stimulating agents or hypoxia-inducible factor prolyl hydroxylase enzyme inhibitors, which affect serum iron status. Finally, although SPPB is a reproducible method for assessing physical function, especially in elderly individuals, the study's results should be confirmed by using other measures including a cardiopulmonary function test and a walking distance/speed test.

Conclusions

TSAT as a continuous variable, but not ID, was independently associated with physical function in HF patients, and a significant association was lost in HF patients with DM, which suggests a limited impact of iron supplementation therapy in patients with HF and DM.

Funding

This study was supported by Grants JP18K17677 and 22K11288 (S.K.) from the Japan Society for the Promotion of Science, Tokyo, Japan, and the Hokkaido Heart Association Grant for Research.

Conflict of interest

None declared.

References

Roger VL. Epidemiology. Circ Res 2013;113:646‐659.

Roger VL. Epidemiology of heart failure: A contemporary perspective. Circ Res 2021;128:1421‐1434.

Katano S, Hashimoto A, Ohori K, Watanabe A, Honma R, Yanase R, et al. Nutritional status and energy intake as predictors of functional status after cardiac rehabilitation in elderly inpatients with heart failure—A retrospective cohort study. Circ J 2018;82:1584‐1591. doi:10.1253/circj.CJ‐17‐1202

Katano S, Yano T, Ohori K, Kouzu H, Nagaoka R, Honma S, et al. Barthel index score predicts mortality in elderly heart failure—A goal of comprehensive cardiac rehabilitation. Circ J 2021;86:70‐78. doi:10.1253/circj.CJ‐21‐0584

Coats AJS, Forman DE, Haykowsky M, Kitzman DW, McNeil A, Campbell TS, et al. Physical function and exercise training in older patients with heart failure. Nat Rev Cardiol 2017;14:550‐559. doi:10.1038/nrcardio.2017.70

O'Neill D, Forman DE. The importance of physical function as a clinical outcome: Assessment and enhancement. Clin Cardiol 2020;43:108‐117. doi:10.1002/clc.23311

Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM, et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med Sci Sports Exerc 2011;43:1334‐1359. doi:10.1249/MSS.0b013e318213fefb

Lutz AH, Delligatti A, Allsup K, Afilalo J, Forman DE. Cardiac rehabilitation is associated with improved physical function in frail older adults with cardiovascular disease. J Cardiopulm Rehabil Prev 2020;40:310‐318. doi:10.1097/HCR.0000000000000537

Kamiya K, Sato Y, Takahashi T, Tsuchihashi‐Makaya M, Kotooka N, Ikegame T, et al. Multidisciplinary cardiac rehabilitation and long‐term prognosis in patients with heart failure. Circ Heart Fail 2020;13: [eLocator: e006798]. doi:10.1161/CIRCHEARTFAILURE.119.006798

Jankowska EA, von Haehling S, Anker SD, Macdougall IC, Ponikowski P. Iron deficiency and heart failure: Diagnostic dilemmas and therapeutic perspectives. Eur Heart J 2013;34:816‐829. doi:10.1093/eurheartj/ehs224

Dziegala M, Josiak K, Kasztura M, Kobak K, von Haehling S, Banasiak W, et al. Iron deficiency as energetic insult to skeletal muscle in chronic diseases. J Cachexia Sarcopenia Muscle 2018;9:802‐815. doi:10.1002/jcsm.12314

Sawicki KT, De Jesus A, Ardehali H. Iron metabolism in cardiovascular disease: Physiology, mechanisms, and therapeutic targets. Circ Res 2023;132:379‐396. doi:10.1161/CIRCRESAHA.122.321667

Koleini N, Shapiro JS, Geier J, Ardehali H. Ironing out mechanisms of iron homeostasis and disorders of iron deficiency. J Clin Invest 2021;131: [eLocator: e148671]. doi:10.1172/JCI148671

Hoes MF, Grote Beverborg N, Kijlstra JD, Kuipers J, Swinkels DW, Giepmans BNG, et al. Iron deficiency impairs contractility of human cardiomyocytes through decreased mitochondrial function. Eur J Heart Fail 2018;20:910‐919. doi:10.1002/ejhf.1154

Jankowska EA, Rozentryt P, Witkowska A, Nowak J, Hartmann O, Ponikowska B, et al. Iron deficiency predicts impaired exercise capacity in patients with systolic chronic heart failure. J Card Fail 2011;17:899‐906. doi:10.1016/j.cardfail.2011.08.003

Rizzo C, Carbonara R, Ruggieri R, Passantino A, Scrutinio D. Iron deficiency: A new target for patients with heart failure. Front Cardiovasc Med 2021;8: [eLocator: 709872]. doi:10.3389/fcvm.2021.709872

Enjuanes C, Klip IT, Bruguera J, Cladellas M, Ponikowski P, Banasiak W, et al. Iron deficiency and health‐related quality of life in chronic heart failure: Results from a multicenter European study. Int J Cardiol 2014;174:268‐275. doi:10.1016/j.ijcard.2014.03.169

Comín‐Colet J, Enjuanes C, González G, Torrens A, Cladellas M, Meroño O, et al. Iron deficiency is a key determinant of health‐related quality of life in patients with chronic heart failure regardless of anaemia status. Eur J Heart Fail 2013;15:1164‐1172. doi:10.1093/eurjhf/hft083

Barandiarán Aizpurua A, Sanders‐van Wijk S, Brunner‐La Rocca HP, Henkens MTHM, Weerts J, Spanjers MHA, et al. Iron deficiency impacts prognosis but less exercise capacity in heart failure with preserved ejection fraction. ESC Heart Fail 2021;8:1304‐1313. doi:10.1002/ehf2.13204

Alcaide‐Aldeano A, Garay A, Alcoberro L, Jiménez‐Marrero S, Yun S, Tajes M, et al. Iron deficiency: Impact on functional capacity and quality of life in heart failure with preserved ejection fraction. J Clin Med 2020;9:1199. doi:10.3390/jcm9041199

Ikeda Y, Funamoto M, Tsuchiya K. The role of iron in obesity and diabetes. J Med Invest 2022;69:1‐7. doi:10.2152/jmi.69.1

Swaminathan S, Fonseca VA, Alam MG, Shah SV. The role of iron in diabetes and its complications. Diabetes Care 2007;30:1926‐1933. doi:10.2337/dc06‐2625

Liu J, Li Q, Yang Y, Ma L. Iron metabolism and type 2 diabetes mellitus: A meta‐analysis and systematic review. J Diabetes Investig 2020;11:946‐955. doi:10.1111/jdi.13216

Ingle L, Reddy P, Clark AL, Cleland JG. Diabetes lowers six‐minute walk test performance in heart failure. J Am Coll Cardiol 2006;47:1909‐1910. doi:10.1016/j.jacc.2006.02.005

Dianati‐Maleki N, Butler J. Diabetes mellitus in patients with heart failure: Bad for all, worse for some. JACC Heart Fail 2017;5:25‐27.

Puthoff ML. Outcome measures in cardiopulmonary physical therapy: Short physical performance battery. Cardiopulm Phys Ther J 2008;19:17‐22.

Pritchard JM, Kennedy CC, Karampatos S, Ioannidis G, Misiaszek B, Marr S, et al. Measuring frailty in clinical practice: A comparison of physical frailty assessment methods in a geriatric out‐patient clinic. BMC Geriatr 2017;17:264. doi:10.1186/s12877‐017‐0623‐0

Welch SA, Ward RE, Beauchamp MK, Leveille SG, Travison T, Bean JF. The short physical performance battery (SPPB): A quick and useful tool for fall risk stratification among older primary care patients. J Am Med Dir Assoc 2021;22:1646‐1651. doi:10.1016/j.jamda.2020.09.038

Nogueira Á, Álvarez G, Russo F, San‐José B, Sánchez‐Tomero JA, Barril G. Is SPPB useful as a screening method of functional capacity in patients with advanced chronic kidney disease? Nefrologia (Engl Ed) 2019;39:489‐496. doi:10.1016/j.nefro.2019.01.003

Pavasini R, Guralnik J, Brown JC, di Bari M, Cesari M, Landi F, et al. Short physical performance battery and all‐cause mortality: Systematic review and meta‐analysis. BMC Med 2016;14:215. doi:10.1186/s12916‐016‐0763‐7

Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129‐2200.

Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, et al. 2022 AHA/ACC/HFSA guideline for the management of heart failure: Executive summary: A report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol 2022;79:1757‐1780. doi:10.1016/j.jacc.2021.12.011

Ishigo T, Katano S, Yano T, Kouzu H, Ohori K, Nakata H, et al. Overestimation of glomerular filtration rate by creatinine‐based equation in heart failure patients is predicted by a novel scoring system. Geriatr Gerontol Int 2020;20:752‐758. doi:10.1111/ggi.13959

Ohori K, Yano T, Katano S, Kouzu H, Inoue T, Takamura Y, et al. Independent link between peripheral artery disease and muscle wasting in patients with heart failure. ESC Heart Fail 2020;7:3252‐3256. doi:10.1002/ehf2.12951

Ohori K, Yano T, Katano S, Kouzu H, Honma S, Shimomura K, et al. High percent body fat mass predicts lower risk of cardiac events in patients with heart failure: An explanation of the obesity paradox. BMC Geriatr 2021;21:16. doi:10.1186/s12877‐020‐01950‐9

Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 2020;21:300‐307.e2. doi:10.1016/j.jamda.2019.12.012

Katano S, Yano T, Kouzu H, Ohori K, Shimomura K, Honma S, et al. Energy intake during hospital stay predicts all‐cause mortality after discharge independently of nutritional status in elderly heart failure patients. Clin Res Cardiol 2021;110:1202‐1220. doi:10.1007/s00392‐020‐01774‐y

Kouzu H, Katano S, Yano T, Ohori K, Nagaoka R, Inoue T, et al. Plasma amino acid profiling improves predictive accuracy of adverse events in patients with heart failure. ESC Heart Fail 2021;8:5045‐5056.

Yano T, Katano S, Kouzu H, Nagaoka R, Inoue T, Takamura Y, et al. Distinct determinants of muscle wasting in nonobese heart failure patients with and without type 2 diabetes mellitus. J Diabetes 2021;13:7‐18. doi:10.1111/1753‐0407.13090

Martens P. The effect of iron deficiency on cardiac function and structure in heart failure with reduced ejection fraction. Card Fail Rev 2022;8: [eLocator: e06]. doi:10.15420/cfr.2021.26

Grote Beverborg N, Klip IT, Meijers WC, Voors AA, Vegter EL, van der Wal HH, et al. Definition of iron deficiency based on the gold standard of bone marrow iron staining in heart failure patients. Circ Heart Fail 2018;11: [eLocator: e004519]. doi:10.1161/CIRCHEARTFAILURE.117.004519

Cankurtaran M, Yavuz BB, Halil M, Ulger Z, Haznedaroğlu IC, Arıoğul S. Increased ferritin levels could reflect ongoing aging‐associated inflammation and may obscure underlying iron deficiency in the geriatric population. Eur Geriat Med 2012;3:277‐280. doi:10.1016/j.eurger.2012.06.005

Grote Beverborg N, van der Wal HH, Klip IT, Anker SD, Cleland J, Dickstein K, et al. Differences in clinical profile and outcomes of low iron storage vs defective iron utilization in patients with heart failure: Results from the DEFINE‐HF and BIOSTAT‐CHF studies. JAMA Cardiol 2019;4:696‐701. doi:10.1001/jamacardio.2019.1739

Masini G, Graham FJ, Pellicori P, Cleland JGF, Cuthbert JJ, Kazmi S, et al. Criteria for iron deficiency in patients with heart failure. J Am Coll Cardiol 2022;79:341‐351. doi:10.1016/j.jacc.2021.11.039

Garnham JO, Roberts LD, Espino‐Gonzalez E, Whitehead A, Swoboda PP, Koshy A, et al. Chronic heart failure with diabetes mellitus is characterized by a severe skeletal muscle pathology. J Cachexia Sarcopenia Muscle 2020;11:394‐404. doi:10.1002/jcsm.12515

Pilar Vaquero M, Martínez‐Suárez M, García‐Quismondo Á, Del Cañizo FJ, Sánchez‐Muniz FJ. Diabesity negatively affects transferrin saturation and iron status. The DICARIVA study. Diabetes Res Clin Pract 2021;172: [eLocator: 108653]. doi:10.1016/j.diabres.2021.108653

Cheung CL, Cheung TT, Lam KS, Cheung BM. High ferritin and low transferrin saturation are associated with pre‐diabetes among a national representative sample of U.S. adults. Clin Nutr 2013;32:1055‐1060. doi:10.1016/j.clnu.2012.11.024

Podmore C, Meidtner K, Schulze MB, Scott RA, Ramond A, Butterworth AS, et al. Association of multiple biomarkers of iron metabolism and type 2 diabetes: The EPIC‐InterAct study. Diabetes Care 2016;39:572‐581. doi:10.2337/dc15‐0257

Wang H, Li H, Jiang X, Shi W, Shen Z, Li M. Hepcidin is directly regulated by insulin and plays an important role in iron overload in streptozotocin‐induced diabetic rats. Diabetes 2014;63:1506‐1518. doi:10.2337/db13‐1195

Wang CY, Babitt JL. Hepcidin regulation in the anemia of inflammation. Curr Opin Hematol 2016;23:189‐197. doi:10.1097/MOH.0000000000000236

Cooksey RC, Jones D, Gabrielsen S, Huang J, Simcox JA, Luo B, et al. Dietary iron restriction or iron chelation protects from diabetes and loss of β‐cell function in the obese (ob/ob lep^−/−) mouse. Am J Physiol Endocrinol Metab 2010;298:E1236‐E1243. doi:10.1152/ajpendo.00022.2010

Matsumoto M, Sasaki N, Tsujino T, Akahori H, Naito Y, Masuyama T. Iron restriction prevents diabetic nephropathy in Otsuka Long‐Evans Tokushima fatty rat. Ren Fail 2013;35:1156‐1162. doi:10.3109/0886022X.2013.819729

Lamas GA, Goertz C, Boineau R, Mark DB, Rozema T, Nahin RL, et al. Effect of disodium EDTA chelation regimen on cardiovascular events in patients with previous myocardial infarction: The TACT randomized trial. JAMA 2013;309:1241‐1250. doi:10.1001/jama.2013.2107

Vargas‐Vargas MA, Saavedra‐Molina A, Gómez‐Barroso M, Peña‐Montes D, Cortés‐Rojo C, Miguel H, et al. Dietary iron restriction improves muscle function, dyslipidemia, and decreased muscle oxidative stress in streptozotocin‐induced diabetic rats. Antioxidants (Basel) 2022;11:731. doi:10.3390/antiox11040731

Donnelly LA, Dennis JM, Coleman RL, Sattar N, Hattersley AT, Holman RR, et al. Risk of anemia with metformin use in type 2 diabetes: A MASTERMIND study. Diabetes Care 2020;43:2493‐2499. doi:10.2337/dc20‐1104

Packer M. How can sodium‐glucose cotransporter 2 inhibitors stimulate erythrocytosis in patients who are iron‐deficient? Implications for understanding iron homeostasis in heart failure. Eur J Heart Fail 2022;24:2287‐2296. doi:10.1002/ejhf.2731