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When to transfuse: Red blood cell and platelet transfusion thresholds in clinical practice

2019· article· en· W2983057363 on OpenAlexafffund
Chantalle Menard, Matthew D. Seftel, A Ponnampalam, Ryan Zarychanski

Bibliographic record

VenueSouth African Medical Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of British ColumbiaUniversity of ManitobaResearch Institute in Oncology and HematologyCancerCare Manitoba
FundersCanadian Institutes of Health ResearchMax Rady College of Medicine, University of Manitoba
KeywordsMedicineIntensive care medicineBlood componentBlood transfusionRed Blood Cell TransfusionPlatelet transfusionPlateletBlood managementClinical PracticeClinical trialWhole bloodSurgeryInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Blood component transfusion is a frequently prescribed intervention in healthcare that depends on the availability of a limited and expensive resource. The transfusion of blood products may be life-saving, but it is not without risk. Society guidelines and clinical trials guide transfusion decisions regarding transfusion thresholds, as well as the appropriateness of prophylactic v. therapeutic transfusion strategies. This review provides a practical and evidence-informed approach to the transfusion of red blood cells and platelets in commonly encountered clinical settings.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.292
Teacher spread0.277 · 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.

Study designNot applicable
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

Citations1
Published2019
Admission routes2
Has abstractyes

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