Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 506

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Iron Deficiency and Erythropoiesis: New Diagnostic Approaches

Brugnara, Carlo·2003·Clinical Chemistry

Abstract

Iron deficiency anemia is one of the most common diseases worldwide. In the majority of cases, the presence of hypochromic microcytic anemia and biochemical evidence for depletion of body iron stores makes the diagnosis relatively straightforward. However, in several clinical conditions, classic biochemical indices such as serum iron, transferrin saturation, and ferritin may not be informative or may not change rapidly enough to reflect transient iron-deficient states (functional iron deficiency), such as the ones that develop during recombinant human erythropoietin (r-HuEPO) therapy. The identification and treatment of iron deficiency in settings such as r-HuEPO therapy, anemia of chronic disease, and iron deficiency of early childhood may be improved by the use of red cell and reticulocyte cellular indices, which reflect in almost real time the development of iron deficiency and the response to iron therapy. In the anemia of chronic disease, measurements of plasma cytokines and iron metabolism regulators such as hepcidin (when available) may be helpful in the characterization of the pathophysiologic basis of this condition. The ratio of serum transferrin receptor (sTfR) to serum ferritin (R/F ratio) has been shown to have excellent performance in estimating body iron stores, but it cannot be used widely because of the lack of standardization for sTfR assays. The combination of hematologic markers such as reticulocyte hemoglobin content, which decreases with iron deficiency, and R/F ratio may allow for a more precise classification of anemias.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1373/49.10.1573

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 506

Metadata

Authors
Brugnara, C.
Venue
Clinical Chemistry
Published
2003-10-01
Volume
49
Issue
10
Pages
1573-1578
ISSN
  • 0009-9147 (ISSN-L)
  • 1530-8561
OpenAlex
W2102434796
Cited by
506
References
10
FWCI
7.25
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.