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Record W2178195663 · doi:10.1002/jca.21438

Citrate anticoagulation: Are blood donors donating bone?

2015· review· en· W2178195663 on OpenAlexfundno aff
Walter Bialkowski, Roberta Bruhn, Gustaf Edgren, Paula E. Papanek

Bibliographic record

VenueJournal of Clinical Apheresis · 2015
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsnot available
FundersInstitute of Infection and ImmunityNational Heart, Lung, and Blood Institute
KeywordsApheresisMedicinePlateletpheresisDonationBlood donorIntensive care medicineVolunteerSurgeryImmunologyPlatelet

Abstract

fetched live from OpenAlex

An estimated 2.4 million volunteer apheresis blood donation procedures were performed in the United States in 2010, and increases in the proportion of transfused blood products derived from apheresis blood collections have been consistently reported. Anticoagulation is required during apheresis and is achieved with citrate. Donor exposure to citrate causes an acute physiological response to maintain serum mineral homeostasis. Some data are available on the sequelae of this acute response in the days and weeks following exposure, raising questions about bone mineral density in regular apheresis donors. New research is emerging that addresses the potential long-term health outcomes of repeated citrate exposure. This article reviews the acute physiological response to citrate anticoagulation in volunteer blood donors, presents contrasting perspectives on the potential effects of citrate exposure on bone density, and identifies key knowledge gaps in our understanding of long-term health outcomes in apheresis donors. J. Clin. Apheresis 31:459-463, 2016. © 2015 Wiley Periodicals, Inc.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.209
GPT teacher head0.421
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2015
Admission routes1
Has abstractyes

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