Total iron binding capacity is a predictor for muscle loss in maintenance hemodialysis patients

Ikeda-Taniguchi, Misa; Takahashi, Keiko; Shishido, Kanji; Honda, Hirokazu

doi:10.1007/s10157-022-02193-1

Cited by 11 publications

(13 citation statements)

References 27 publications

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“…In one study, patients with heart failure and an absolute iron deficiency often had normal serum levels of ferritin, 55 and in other reports, myocardial (but not serum) levels of ferritin reflected the presence of cardiac iron deficiency in experimental and clinical heart failure 20,62 . Furthermore, inflammation and nutritional status can influence transferrin levels, thus complicating the interpretation of transferrin saturation in heart failure 63–66 …”

Section: Changes In Iron Homeostasis Proteins In Patients With Heart ...mentioning

confidence: 98%

Section: Changes In Iron Homeostasis Proteins In Patients With Heart ...mentioning

confidence: 99%

“…20,62 Furthermore, inflammation and nutritional status can influence transferrin levels, thus complicating the interpretation of transferrin saturation in heart failure. [63][64][65][66] Given the limitations of both hepcidin and ferritin in states of chronic inflammation, the measurement of sTfR has been advocated as an additional diagnostic tool. Serum levels of sTfR are increased in both patients with an absolute or functional iron deficiency, 43,67 since the receptor is upregulated in response to a decrease in cytosolic iron, regardless of cause.…”

Section: Changes In Iron Homeostasis Proteins In Patients With Heart ...mentioning

confidence: 99%

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How can sodium–glucose cotransporter 2 inhibitors stimulate erythrocytosis in patients who are iron‐deficient? Implications for understanding iron homeostasis in heart failure

Packer

2022

European J of Heart Fail

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Many patients with heart failure have an iron‐deficient state, which can limit erythropoiesis in erythroid precursors and ATP production in cardiomyocytes. Yet, treatment with sodium–glucose cotransporter 2 (SGLT2) inhibitors produces consistent increases in haemoglobin and haematocrit, even in patients who are iron‐deficient before treatment, and this effect remains unattenuated throughout treatment even though SGLT2 inhibitors further aggravate biomarkers of iron deficiency. Heart failure is often accompanied by systemic inflammation, which activates hepcidin, thus impairing the duodenal absorption of iron and the release of iron from macrophages and hepatocytes, leading to a decline in circulating iron. Inflammation and oxidative stress also promote the synthesis of ferritin and suppress ferritinophagy, thus impairing the release of intracellular iron stores and leading to the depletion of bioreactive cytosolic Fe2+. By alleviating inflammation and oxidative stress, SGLT2 inhibitors down‐regulate hepcidin, upregulate transferrin receptor protein 1 and reduce ferritin; the net result is to increase the levels of cytosolic Fe2+ available to mitochondria, thus enabling the synthesis of heme (in erythroid precursors) and ATP (in cardiomyocytes). The finding that SGLT2 inhibitors can induce erythrocytosis without iron supplementation suggests that the abnormalities in iron diagnostic tests in patients with mild‐to‐moderate heart failure are likely to be functional, rather than absolute, that is, they are related to inflammation‐mediated trapping of iron by hepcidin and ferritin, which is reversed by treatment with SGLT2 inhibitors. An increase in bioreactive cytosolic Fe2+ is also likely to augment mitochondrial production of ATP in cardiomyocytes, thus retarding the progression of heart failure. These effects on iron metabolism are consistent with (i) proteomics analyses of placebo‐controlled trials, which have shown that biomarkers of iron homeostasis represent the most consistent effect of SGLT2 inhibitors; and (ii) statistical mediation analyses, which have reported striking parallelism of the effect of SGLT2 inhibitors to promote erythrocytosis and reduce heart failure events.

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Section: Changes In Iron Homeostasis Proteins In Patients With Heart ...mentioning

confidence: 98%

Section: Changes In Iron Homeostasis Proteins In Patients With Heart ...mentioning

confidence: 99%

Section: Changes In Iron Homeostasis Proteins In Patients With Heart ...mentioning

confidence: 99%

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How can sodium–glucose cotransporter 2 inhibitors stimulate erythrocytosis in patients who are iron‐deficient? Implications for understanding iron homeostasis in heart failure

Packer

2022

European J of Heart Fail

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“…Likewise, also high-performance athletes due to exercise-induced inflammation and obese people due to the presence of low-grade inflammation are suffering from functional iron deficiency. 275 When suffering from functional iron deficiency, ferritin-levels are normal or elevated ranging from 30-500 μg/L, [276][277][278][279] while transferrin saturation (TSAT) values are below 20% and-dependent on inflammation severity-inflammation markers such as C-reactive protein (CRP; for low-grade inflammation high sensitivity-CRP) or α1-acid glycoprotein (AGP) are elevated. 79 Body iron stores may be adequate in "functional iron deficiency"; however, there are reduced levels of "metabolic active iron" as iron is not accessible.…”

Section: Iron Deficiency-absolute and Functionalmentioning

confidence: 99%

Nutrition in chronic inflammatory conditions: Bypassing the mucosal block for micronutrients

Roth‐Walter,

Berni Canani,

O'Mahony

et al. 2023

Allergy

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Nutritional Immunity is one of the most ancient innate immune responses, during which the body can restrict nutrients availability to pathogens and restricts their uptake by the gut mucosa (mucosal block). Though this can be a beneficial strategy during infection, it also is associated with non‐communicable diseases—where the pathogen is missing; leading to increased morbidity and mortality as micronutritional uptake and distribution in the body is hindered. Here, we discuss the acute immune response in respect to nutrients, the opposing nutritional demands of regulatory and inflammatory cells and particularly focus on some nutrients linked with inflammation such as iron, vitamins A, Bs, C, and other antioxidants. We propose that while the absorption of certain micronutrients is hindered during inflammation, the dietary lymph path remains available. As such, several clinical trials investigated the role of the lymphatic system during protein absorption, following a ketogenic diet and an increased intake of antioxidants, vitamins, and minerals, in reducing inflammation and ameliorating disease.

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“…Moreover, dialysis concentration may affect dialysis efficacy [ 59 ]. A study reported that the dialysis efficacy of patients who died was lower than that of those who survived; lower dialysis efficacy results in lower levels of calcium, creatinine and a lower ultrafiltration volume [ 60 ]. Impaired nutritional status results in lower levels of triglycerides, lower levels of density lipoprotein cholesterol, and a lower body mass index [ 61 , 62 ].…”

Section: Discussionmentioning

confidence: 99%

Application of deep learning to predict the low serum albumin in new hemodialysis patients

Yang

Chen

et al. 2023

Nutr Metab (Lond)

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Background Serum albumin level is a crucial nutritional indicator for patients on dialysis. Approximately one-third of patients on hemodialysis (HD) have protein malnutrition. Therefore, the serum albumin level of patients on HD is strongly correlated with mortality. Methods In study, the data sets were obtained from the longitudinal electronic health records of the largest HD center in Taiwan from July 2011 to December 2015, included 1,567 new patients on HD who met the inclusion criteria. Multivariate logistic regression was performed to evaluate the association of clinical factors with low serum albumin, and the grasshopper optimization algorithm (GOA) was used for feature selection. The quantile g-computation method was used to calculate the weight ratio of each factor. Machine learning and deep learning (DL) methods were used to predict the low serum albumin. The area under the curve (AUC) and accuracy were calculated to determine the model performance. Results Age, gender, hypertension, hemoglobin, iron, ferritin, sodium, potassium, calcium, creatinine, alkaline phosphatase, and triglyceride levels were significantly associated with low serum albumin. The AUC and accuracy of the GOA quantile g-computation weight model combined with the Bi-LSTM method were 98% and 95%, respectively. Conclusion The GOA method was able to rapidly identify the optimal combination of factors associated with serum albumin in patients on HD, and the quantile g-computation with DL methods could determine the most effective GOA quantile g-computation weight prediction model. The serum albumin status of patients on HD can be predicted by the proposed model and accordingly provide patients with better a prognostic care and treatment.

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Total iron binding capacity is a predictor for muscle loss in maintenance hemodialysis patients

Cited by 11 publications

References 27 publications

How can sodium–glucose cotransporter 2 inhibitors stimulate erythrocytosis in patients who are iron‐deficient? Implications for understanding iron homeostasis in heart failure

How can sodium–glucose cotransporter 2 inhibitors stimulate erythrocytosis in patients who are iron‐deficient? Implications for understanding iron homeostasis in heart failure

Nutrition in chronic inflammatory conditions: Bypassing the mucosal block for micronutrients

Application of deep learning to predict the low serum albumin in new hemodialysis patients

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