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Record W4200600006 · doi:10.1007/s00134-021-06531-x

Transfusion strategies in bleeding critically ill adults: a clinical practice guideline from the European Society of Intensive Care Medicine

2021· article· en· W4200600006 on OpenAlexaff
Alexander P. J. Vlaar, Joanna C. Dionne, Sanne de Bruin, Marije Wijnberge, Jorinde Raasveld, Frank E.H.P. van Baarle, Massimo Antonelli, Cécile Aubron, Jacques Duranteau, Nicole P. Juffermans, Jens Meier, Gavin J. Murphy, Riccardo Abbasciano, Marcella C.A. Müller, Marcus D. Lancé, Nathan D. Nielsen, Herbert Schöchl, Beverley J. Hunt, Maurizio Cecconi, Simon Oczkowski

Bibliographic record

VenueIntensive Care Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare HamiltonImpact
FundersBritish Heart Foundation
KeywordsGuidelineMedicineAnesthesiologyCritically illIntensive care medicineTranexamic acidIntensive carePopulationTransfusion medicineMEDLINEMedical emergencyBlood transfusionSurgeryBlood lossPathology

Abstract

fetched live from OpenAlex

To develop evidence-based clinical practice recommendations regarding transfusion practices and transfusion in bleeding critically ill adults. A taskforce involving 15 international experts and 2 methodologists used the GRADE approach to guideline development. The taskforce addressed three main topics: transfusion support in massively and non-massively bleeding critically ill patients (transfusion ratios, blood products, and point of care testing) and the use of tranexamic acid. The panel developed and answered structured guideline questions using population, intervention, comparison, and outcomes (PICO) format. The taskforce generated 26 clinical practice recommendations (2 strong recommendations, 13 conditional recommendations, 11 no recommendation), and identified 10 PICOs with insufficient evidence to make a recommendation. This clinical practice guideline provides evidence-based recommendations for the management of massively and non-massively bleeding critically ill adult patients and identifies areas where further research is needed.

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)0.037
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.366
Teacher spread0.327 · 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 designQualitative
Domainnot available
GenreCommentary

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

Citations131
Published2021
Admission routes1
Has abstractyes

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