Transfusion practice in anemic, non-bleeding patients: Cross-sectional survey of physicians working in general internal medicine teaching hospitals in Switzerland
Bibliographic record
Abstract
BACKGROUND: Transfusion practice might significantly influence patient morbidity and mortality. Between European countries, transfusion practice of red blood cells (RBC) greatly differs. Only sparse data are available on transfusion practice of general internal medicine physicians in Switzerland. METHODS: In this cross-sectional survey, physicians working in general medicine teaching hospitals in Switzerland were investigated regarding their self-reported transfusion practice in anemic patients without acute bleeding. The definition of anemia, transfusion triggers, knowledge on RBC transfusion, and implementation of guidelines were assessed. RESULTS: 560 physicians of 71 hospitals (64%) responded to the survey. Anemia was defined at very diverging hemoglobin values (by 38% at a hemoglobin <130 g/L for men and by 57% at <120 g/L in non-pregnant women). 62% and 43% respectively, did not define anemia in men and in women according to the World Health Organization. Fifty percent reported not to transfuse RBC according to international guidelines. Following factors were indicated to influence the decision to transfuse: educational background of the physicians, geographical region of employment, severity of anemia, and presence of known coronary artery disease. 60% indicated that their knowledge on Transfusion-related Acute Lung Injury (TRALI) did not influence transfusion practice. 50% of physicians stated that no local transfusion guidelines exist and 84% supported the development of national recommendations on transfusion in non-acutely bleeding, anemic patients. CONCLUSION: This study highlights the lack of adherence to current transfusion guidelines in Switzerland. Identifying and subsequently correcting this deficit in knowledge translation may have a significant impact on patient care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".