Should We Reconsider Recommendations for Red Blood Cell Transfusion?
Bibliographic record
Abstract
Very few randomized controlled trials on the benefits of red blood cell (RBC) transfusions in humans have been published. Consequently, most clinical practice guidelines are based on expert opinion, animal studies and the limited human trials available. In the absence of definitive outcome studies, numerous theoretical arguments have been put forward either to support or to condone the classic transfusion threshold of 10 g/dL. However, the limited data available from randomized controlled trials suggest that a restrictive transfusion strategy (transfusion threshold between 7 and 8 g/dL) is associated with decreased transfusion requirements, that overall morbidity (including cardiac morbidity) and mortality, hemodynamic, pulmonary and oxygen transport variables are not different between restrictive and liberal transfusion strategies and, finally, that a restrictive transfusion strategy is not associated with increased adverse outcomes. In fact, a restrictive strategy may be associated with decreased adverse outcomes in younger and less sick critical care patients. Since transfusions are administered to correct inadequate oxygen delivery, whether global or regional, reliable monitors of tissue oxygenation will be required to study the benefits (or lack thereof) of RBC transfusions. The quest for a universal transfusion trigger, the holy grail of transfusion medicine, must be abandoned. All RBC transfusions must be tailored to the patient's needs, at the moment the need arises. In conclusion, most published recommendations are appropriate but their conclusions are limited, as they are commensurate with existing knowledge. Reliable monitors to guide transfusion therapy and well conducted trials to determine optimal transfusion strategies are required.
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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 | 0.056 | 0.252 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.010 | 0.003 |
| Research integrity | 0.026 | 0.031 |
| Insufficient payload (model declined to judge) | 0.013 | 0.012 |
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".