Systematic reviews of guidelines and studies for single versus multiple unit transfusion strategies
Bibliographic record
Abstract
BACKGROUND: Recent recommendations indicate that one red blood cell (RBC) unit should be transfused at a time, with reassessment after each transfusion, which may be extrapolated from literature supporting restrictive transfusion triggers rather than specific evidence. Therefore, two systematic reviews were performed to identify the following: 1) RBC transfusion guidelines and review articles to determine if single- or multiple-unit transfusion strategies are recommended and 2) studies comparing strategies for evidence of benefit. STUDY DESIGN AND METHODS: MEDLINE, EMBASE, CINAHL, Web of Science, National Guideline Clearinghouse, and Trip Database were searched (inception to June 2017). For the first review, the proportion of articles with single/multiple-unit recommendations was assessed and stratified by article type. For the second review, the primary outcome was RBC use. Secondary outcomes included proportion of transfusion episodes using a single-unit strategy, length of stay, and mortality. RESULTS: The first review identified 145 articles for analysis, with 51 transfusion guidelines. Only 14 guidelines (27%) made a recommendation, with most (93%) recommending single-unit transfusions. The second review identified seven cohort studies comparing preimplementation and postimplementation of a policy encouraging single-unit transfusion strategies. Meta-analysis could not be performed for outcomes given inconsistencies in reporting. RBC use decreased by approximately 10 to 41% across studies. CONCLUSION: Transfusion guidelines lack recommendations to transfuse to a single-unit strategy. Mostly retrospective cohort studies (six of seven) are inconsistent in outcome reporting but suggest improved RBC use. Further high-quality studies could identify the benefits of a single-unit transfusion strategy, determine the applicability to different clinical settings, and inform future practice guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".