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Record W2055840896 · doi:10.5581/1516-8484.20120086

Blood donation, blood supply, iron deficiency and anemia - It is time to shift attention back to donor health

2012· article· en· W2055840896 on OpenAlexaboutno aff
Rodolfo Delfini Cançado, Dante Mário Langhi

Bibliographic record

VenueRevista Brasileira de Hematologia e Hemoterapia · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsnot available
Fundersnot available
KeywordsBlood donorMedicineAnemiaBlood donationsIron deficiencyDonationBlood supplyIntensive care medicinePediatricsSurgeryImmunologyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

Since the 1980s blood collectors worldwide have focused on two central themes: blood product safety and an adequate blood supply. From the standpoint of safety, specifically the reduction of transfusion-transmitted diseases, the achievements over the past quarter century are remarkable. With respect to the adequacy of the blood supply, the past decade has witnessed major gains in some countries of Europe, Canada and the US and less than had been expected in others, including Brazil, where the challenge of having a more stable blood supply, in which supply and demand are in better balance remains an important issue(1). On the other hand, the aforementioned achievement has come at a price: iron depletion of the repeat blood donor. Blood centers have long recognized that it is more effective and less expensive to collect blood from existing donors than to recruit new donors. While first-time donors, particularly the young and minorities, have been more successfully recruited, 70% of US and 40-70% (depending on the region) of Brazilian donors are repeat donors(1,2). The only known significant disadvantage of blood donation is the potential risk of iron deficiency (ID). Iron is a vitally important element in the human metabolism. It plays a central role in erythropoiesis and is also involved in many other intracellular processes in all the tissues of the body. The potentiality of the individual donor to give blood without developing ID and iron deficiency anemia (IDA) varies widely, probably due to differences in nutritional iron intake, the differences in prevalences of ID in each study population, menstrual iron loss in females, the frequency of blood donation and the use of supplemental iron(2). The frequency of ID is high in blood donors (1.8% to 8.4% in males and 4.5% to 34.8% in females), and more dependent on the frequency of donations than on the cumulated number of donations(2,4). In addition to this, ID is a significant problem and its prevalence is increasing in many countries around the world. The prevalence has been reported to be 9-40% in women, depending on age and menstrual status and 2-5% in men(1,2). Because menstruating females begin their blood donation careers from a lower starting point, subsequent donations pose a risk for greater clinical harm. Females have much higher rates of both ID and IDA.The clinical implications of ID and IDA are not insignificant, including fatigue, reduced work performance and intellectual capacity, reduced endurance, restless leg syndrome, pica, and cognitive and immune function changes. The degree of symptomatology is proportionate to the severity of the anemia(1,2). Moreover, low hemoglobin (Hb) accounts for 4-10% of total deferrals, with the vast majority occurring in women. Therefore it seems reasonable to secure adequate iron reserves in the donor population in order to maintain an appropriate donation potentiality and to avoid possible hematological and non-hematological complications related to ID(1,2). The question that arises is whether this practice is in the best interest of donor health. In this issue of Revista Brasileira de Hematologia e Hemoterapia, Silva et al., representing the Hemocentro Regional de Uberaba, Minas Gerais, Brazil, have brought this issue to light(5). Given the findings in this and other studies, what measures can blood collectors pursue to address iron depletion? There is no single answer, but several approaches should be considered: 1) modifying the donor Hb requirements and measurement of Hb, 2) changing the interdonation interval, 3) testing for serum ferritin, and 4) iron supplementation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.262
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2012
Admission routes1
Has abstractyes

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