A Simple Guideline Reduces the Need for Red Blood Cell Transfusions in Swiss Hospitals: A Prospective, Multicentre, Before-and-After Study in Elective Hip and Knee Replacement
Bibliographic record
Abstract
INTRODUCTION: Optimising the use of blood has become a core task of transfusion medicine. Because no general guidelines are available in Switzerland, we analysed the effects of the introduction of a guideline on red blood cell (RBC) transfusion for elective orthopaedic surgery. METHODS: Prospective, multicentre, before-and-after study comparing the use of RBCs in adult elective hip or knee replacement before and after the implementation of a guideline in 10 Swiss hospitals, developed together with all participants. RESULTS: We included 2,134 patients, 1,238 in 7 months before, 896 in 6 months after intervention. 57 (34 or 2.7% before, 23 or 2.6% after) were lost before follow-up visit. The mean number of transfused RBC units decreased from 0.5 to 0.4 per patient (0.1, 95% CI 0.08-0.2; p = 0.014), the proportion of transfused patients from 20.9% to 16.9% (4%, 95% C.I. 0.7-7.4%; p = 0.02), and the pre-transfusion haemoglobin from 82.6 to 78.2 g/l (4.4 g/l, 95% C. I. 2.15-6.62 g/l, p < 0.001). We did not observe any statistically significant changes in in-hospital mortality (0.4% vs. 0%) and morbidity (4.1% vs. 4.0%), median hospital length of stay (9 vs. 9 days), follow-up mortality (0.4% vs. 0.2%) and follow-up morbidity (6.9% vs. 6.0%). CONCLUSIONS: The introduction of a simple transfusion guideline reduces and standardises the use of RBCs by decreasing the haemoglobin transfusion trigger, without negative effects on the patient outcome. Local support, training, and monitoring of the effects are requirements for programmes optimising the use of blood.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".