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Record W6944848836 · doi:10.20381/ruor-28752

Intraoperative Blood Transfusions: Identifying Stakeholder Interests

2023· other· en· W6944848836 on OpenAlexaboutno aff

Bibliographic record

VenueuO Research (University of Ottawa) · 2023
Typeother
Languageen
FieldArts and Humanities
TopicMedieval European History and Architecture
Canadian institutionsnot available
Fundersnot available
KeywordsBlood productBlood transfusionStakeholderClinical PracticeVariation (astronomy)MEDLINESystematic reviewPatient carePsychological intervention

Abstract

fetched live from OpenAlex

Close to one million red blood cell (RBC) units are transfused annually in Canadian hospitals, with surgical inpatients accounting for up to 44% of transfusions. There is evidence of significant variation in transfusion practice in the operating room (i.e., intraoperative). Although variation is expected based on disease severity and patient preference, inappropriate clinical care due to either under- or over-transfusion likely also contributes to significant variation. Indeed, estimates of unwarranted intraoperative RBC transfusions in the literature range from 19% to 49%, owing partly to a lack of evidence-based consensus on RBC transfusion practice in the OR. Our two systematic reviews have highlighted this gap, demonstrating a lack of evidence from trials or actionable clinical practice guidelines to inform decisions in the OR. Perhaps more importantly, avoidance of blood product exposure is an important patient-prioritized outcome that has yet to be studied empirically in the OR. As such, the observed variation in transfusion practice suggests that transfusion decision-making during surgery represents a clear and important knowledge and evidence gap. Transfusion decision-making in the OR is a complex and dynamic process that we cannot begin to improve without first understanding it. It is influenced by 1) physiologic parameters such as acute blood loss, the effects of general anesthesia, and surgical manipulation. Decision-making is also likely heavily influenced by 2) behavioural factors in the OR (heuristics, team dynamics, institutional culture), for which very little empirical work has been conducted. Finally, the importance of 3) patient input in influencing transfusion decisions is inadequately studied, given the documented disconnect between patient priorities and outcomes used in the medical literature and by clinicians. In this context, the aim of my thesis was to develop an empirical understanding of transfusion decision-making in the OR based on stakeholder perceptions and priorities, informed by an integrated patient engagement process. With this work, I address an important knowledge gap in intraoperative blood transfusion, thereby contributing to efforts to reduce variation in blood transfusion practice in surgery. It is my hope that this work will be influential in informing actionable perioperative tools to optimize blood management including providing both evidence and knowledge gaps for future research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0400.001

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 head0.210
GPT teacher head0.299
Teacher spread0.089 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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