Criteria used to define appropriate red blood cell transfusion in the perioperative setting: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Intraoperative red blood cell (RBC) transfusion strategies vary depending on multiple factors. Several studies have documented significant variability in RBC transfusion practices during surgery. This scoping review aimed to identify and describe existing criteria or clinical decision-making tools used to evaluate intraoperative and immediate post-operative RBC transfusion appropriateness. METHODS: A scoping review was conducted and reported according to Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with extension for scoping reviews. A systematic search of MEDLINE and EMBASE was conducted. Relevant references were also explored. Studies reporting on the development, use, or validation of a clinical tool or set of criteria to adjudicate the appropriateness of intra- or post-operative RBC transfusions were eligible for inclusion. RESULTS: A total of 3,342 de-duplicated articles were identified. 135 underwent full text review, and 28 were included in the analysis. One tool was designed specifically for use during surgery. Adjudication of perioperative RBC transfusion appropriateness was determined using pre-existing published society guidelines in 61% of studies. 29% used a pre-defined set of criteria selected by the study team, and one study used RAND-UCLA to achieve consensus on appropriate transfusion criteria. CONCLUSION: This review identified several tools that were used to adjudicate the appropriateness of intraoperative and immediate postoperative RBC transfusions. Almost all studies adjudicated transfusion appropriateness based on guidelines intended for use outside of perioperative settings. Further research is required to develop RBC transfusion adjudication criteria that specifically integrate the unique factors that influence transfusion in the perioperative setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.081 | 0.237 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.044 | 0.038 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".