Is red distribution width a valid tool to predict impaired iron transport in heart failure?

heart failure iron deficiency iron metablism disorder iron metabolism red cell distribution width (RDW)

Journal

Frontiers in cardiovascular medicine
ISSN: 2297-055X
Titre abrégé: Front Cardiovasc Med
Pays: Switzerland
ID NLM: 101653388

Informations de publication

Date de publication:
2023
Historique:
received: 28 12 2022
accepted: 08 03 2023
medline: 28 4 2023
pubmed: 28 4 2023
entrez: 28 4 2023
Statut: epublish

Résumé

Impaired iron transport (IIT) is a form of iron deficiency (ID) defined as transferrin saturation (TSAT) < 20% irrespective of serum ferritin levels. It is frequently observed in heart failure (HF) where it negatively affects prognosis irrespective of anaemia. In this retrospective study we searched for a surrogate biomarker of IIT. We tested the predictive power of red distribution width (RDW), mean corpuscular volume (MCV) and mean corpuscular haemoglobin concentration (MCHC) to detect IIT in 797 non-anaemic HF patients. At ROC analysis, RDW provided the best AUC (0.6928). An RDW cut-off value of 14.2% identified patients with IIT, with positive and negative predictive values of 48 and 80%, respectively. Comparison between the true and false negative groups showed that estimated glomerular filtration rate (eGFR) was significantly higher ( RDW may be seen as a reliable marker to exclude IIT in non-anaemic HF patients with eGFR ≥60 ml/min/1.73 m

Sections du résumé

Background UNASSIGNED
Impaired iron transport (IIT) is a form of iron deficiency (ID) defined as transferrin saturation (TSAT) < 20% irrespective of serum ferritin levels. It is frequently observed in heart failure (HF) where it negatively affects prognosis irrespective of anaemia.
Objectives UNASSIGNED
In this retrospective study we searched for a surrogate biomarker of IIT.
Methods UNASSIGNED
We tested the predictive power of red distribution width (RDW), mean corpuscular volume (MCV) and mean corpuscular haemoglobin concentration (MCHC) to detect IIT in 797 non-anaemic HF patients.
Results UNASSIGNED
At ROC analysis, RDW provided the best AUC (0.6928). An RDW cut-off value of 14.2% identified patients with IIT, with positive and negative predictive values of 48 and 80%, respectively. Comparison between the true and false negative groups showed that estimated glomerular filtration rate (eGFR) was significantly higher (
Conclusion UNASSIGNED
RDW may be seen as a reliable marker to exclude IIT in non-anaemic HF patients with eGFR ≥60 ml/min/1.73 m

Identifiants

pubmed: 37113703
doi: 10.3389/fcvm.2023.1133233
pmc: PMC10126241
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1133233

Informations de copyright

© 2023 Campodonico, Carulli, Doni, Russo, Junod, Gaudenzi Asinelli, Bonomi, De Martino, Vignati, Pezzuto and Agostoni.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor MM declared a shared affiliation with the authors JC, AB, FDM, CV, BP, PA at the time of review.

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Auteurs

Jeness Campodonico (J)

Centro Cardiologico Monzino, IRCCS, Milano, Italy.
Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Ermes Carulli (E)

Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Francesco Doni (F)

Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Gerardo Lo Russo (GL)

Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Daniele Junod (D)

Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Margherita Gaudenzi Asinelli (M)

Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Alice Bonomi (A)

Centro Cardiologico Monzino, IRCCS, Milano, Italy.

Fabiana De Martino (F)

Centro Cardiologico Monzino, IRCCS, Milano, Italy.

Carlo Vignati (C)

Centro Cardiologico Monzino, IRCCS, Milano, Italy.

Beatrice Pezzuto (B)

Centro Cardiologico Monzino, IRCCS, Milano, Italy.

Piergiuseppe Agostoni (P)

Centro Cardiologico Monzino, IRCCS, Milano, Italy.
Department of Clinical Science and Community Health, Cardiovascular Section, University of Milan, Milan, Italy.

Classifications MeSH