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Record W2549745315 · doi:10.1111/voxs.12327

Understanding iron depletion and overload in blood donors

2016· article· en· W2549745315 on OpenAlexafffund
Sheila F. O’Brien, Mindy Goldman

Bibliographic record

VenueISBT Science Series · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsCanadian Blood ServicesUniversity of Ottawa
FundersCanadian Blood Services
KeywordsIron statusIron deficiencyBlood donorDonationBlood donationsMedicineIron supplementationFerritinHemoglobinPhysiologyAnemiaIron supplementSurgeryInternal medicineImmunology

Abstract

fetched live from OpenAlex

Normal iron stores in healthy men are about 1000 mg, whereas in healthy females only about 300 mg. A whole‐blood donation depletes the donor of approximately 225–250 mg of iron. For females, this means that often her iron stores are completely depleted after only one donation. Dietary absorption of iron can be up to 3·5–4 mg/day when iron stores are low, less when iron stores are higher. It can take 5 months or more for haemoglobin (Hb) to return to 80% of the drop in Hb following a whole‐blood donation, and longer to recoup iron stores; hence, to donate frequently, many donors may require iron supplements. Low iron stores are usually related to diet and blood donation, but can also be a sign of underlying pathology. Hb is routinely measured to determine donor eligibility. However, because iron stores will be largely depleted before Hb concentrations drop, it is a late‐stage indicator of iron deficiency. Serum ferritin is correlated with total body iron, thus is a convenient marker of iron status. Recent studies have shown that iron depletion is common among blood donors. Some people, especially young females, have low iron stores on their first donation. However, low iron stores are correlated with higher frequency of blood donation in both females and males. In countries largely reliant on regular donors, a high proportion of donors may be iron deficient. Low iron stores are sometimes associated with fatigue, pica and restless leg syndrome. There may be other health consequences, but large prospective blood donor studies are required. To address low iron stores in blood donors, there are a range of potential strategies to choose from. These include providing donor education about iron, reducing donation frequency, providing iron supplements and/or testing donor ferritin levels and notifying them of abnormal results. The threshold Hb for male donors can be raised. Ideally, deferral for low Hb should be long enough to recoup body iron stores, and iron supplements have been shown to be beneficial. Hemochromatosis, a condition of excess iron stores, is usually a genetic disorder. If left untreated, iron overload is associated with end‐organ damage to the heart and liver. Treatment usually involves phlebotomy, thus donating blood can be beneficial. Donors who have iron overload may be unaware of their condition, and iron supplements could be detrimental. Many blood services are performing studies and revising policies to better address iron status and safety of blood donation. Due to country‐specific factors such as the nutritional/health status of the population, variable reliance on repeat donation and operational issues, no one policy will suit all centres.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.006
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.240
Teacher spread0.198 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2016
Admission routes2
Has abstractyes

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