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Record W4315436310 · doi:10.1111/trf.17242

Patient perspectives on intraoperative blood transfusion: A qualitative interview study with perioperative patients

2023· article· en· W4315436310 on OpenAlexaff
Tori Lenet, Stephanie Skanes, Joseph Tropiano, Michael Verret, Daniel I. McIsaac, Alan Tinmouth, Julie Hallet, Stuart G. Nicholls, Dean Fergusson, Guillaume Martel

Bibliographic record

VenueTransfusion · 2023
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreHealth Sciences CentreCanadian Blood ServicesOttawa HospitalUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePerioperativeBlood transfusionPsychological interventionThematic analysisInformed consentBlood managementQualitative researchHealth careElective surgeryIntensive care medicineSurgeryNursingAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: While red blood cell (RBC) transfusions are frequently administered during surgery, little is known about patient perspectives regarding intraoperative transfusion. The aim of this study was to understand patient perspectives about intraoperative RBC transfusion and explore their willingness to engage in transfusion prevention strategies. STUDY DESIGN AND METHODS: This descriptive qualitative study used semi-structured patient interviews before and after surgery. Purposive sampling was used to select adult patients with varying perioperative courses, including having perioperative transfusion or postoperative anemia. Inductive and deductive thematic analyses were conducted to identify themes. RESULTS: Twenty patients (nine preoperative and 11 postoperative patients) were interviewed. The following themes were identified: Risk-benefit perception of transfusion, transfusion acceptance, trust, patient involvement in transfusion decisions, acceptance of transfusion prevention interventions, and communication. Patients perceived transfusions as low-risk compared to the surgery itself. Factors influencing transfusion acceptance included trust in the healthcare system and the perception of the treatability of transfusion-related complications. Some patients preferred to defer transfusion decision making to the perioperative team, citing trust in professional judgment and building a positive relationship with their surgeon. Others wished for their preferences to be incorporated into transfusion decisions. Some desired detailed blood consent conversations and most were willing to participate in strategies to reduce intraoperative transfusion. CONCLUSION: In our sample, patients consider intraoperative transfusions as low-risk high-reward interventions and trust the healthcare system and perioperative team to guide intraoperative transfusion decision making. However, preoperative transfusion consent discussions were recalled as being superficial and lacking nuance. Targeted strategies are required to improve blood consent discussions to better integrate patient preferences.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.311
Teacher spread0.284 · 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
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

Citations4
Published2023
Admission routes1
Has abstractyes

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