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Record W4211060114 · doi:10.1213/ane.0000000000005873

A Global Definition of Patient Blood Management

2022· article· en· W4211060114 on OpenAlexaffabout

Bibliographic record

VenueAnesthesia & Analgesia · 2022
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsOntario Stroke NetworkHospital for Sick ChildrenUniversité de Montréal
Fundersnot available
KeywordsBlood managementMultidisciplinary approachBlood transfusionMultidisciplinary teamPatient safetyMEDLINEWork (physics)

Abstract

fetched live from OpenAlex

While patient blood management (PBM) initiatives are increasingly adopted across the globe as part of standard of care, there is need for a clear and widely accepted definition of PBM. To address this, an expert group representing PBM organizations from the International Foundation for Patient Blood Management (IFPBM), the Network for the Advancement of Patient Blood Management, Haemostasis and Thrombosis (NATA), the Society for the Advancement of Patient Blood Management (SABM), the Western Australia Patient Blood Management (WAPBM) Group, and OnTrac (Ontario Nurse Transfusion Coordinators) convened and developed this definition: "Patient blood management is a patient-centered, systematic, evidence-based approach to improve patient outcomes by managing and preserving a patient's own blood, while promoting patient safety and empowerment." The definition emphasizes the critical role of informed choice. PBM involves the timely, multidisciplinary application of evidence-based medical and surgical concepts aimed at (1) screening for, diagnosing, and appropriately treating anemia; (2) minimizing surgical, procedural, and iatrogenic blood losses and managing coagulopathic bleeding throughout the care; and (3) supporting the patient while appropriate treatment is initiated. We believe that having a common definition for PBM will assist all those involved including PBM organizations, hospital administrators, individual clinicians, and policy makers to focus on the appropriate issues when discussing and implementing PBM. The proposed definition is expected to continue to evolve, making this endeavor a work in progress.

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)0.018
metaresearch head score (Gemma)0.017
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: Methods · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0040.017
Scholarly communication0.0110.011
Open science0.0030.010
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0050.002

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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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
GenreMethods

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

Citations193
Published2022
Admission routes2
Has abstractyes

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