Changes in blood center red blood cell distributions in the era of patient blood management: the trends for collection (TFC) study
Bibliographic record
Abstract
BACKGROUND: As patient blood management becomes more widespread, fewer red blood cell (RBC) units have been transfused. This multinational study evaluated changes in blood center RBC distributions. STUDY DESIGN AND METHODS: Data on number and ABO and D groups of RBC distributions were obtained from several large American blood centers and national or provincial blood services (NPBS) from fiscal year (FY) 2010 through FY2014. Due to relatively larger numbers of distributions and differences in ABO and D groups between the Japanese Red Cross and the other NPBS, Japanese data were not included in distributions calculations. RESULTS: Data from seven American blood centers and eight NPBS were obtained. Overall, at both the American and the seven NPBS that were analyzed, there were declines in the number of RBC distributions between FY2010 and FY2014, 16.9 and 8.0%, respectively. The number of O- RBC distributions decreased by 9.0% at American blood centers but the proportion of RBC distributions that were O- increased by 9.3% during this time. The NPBS had 1.6% increase in O- RBC distributions and 10.5% increase in the proportion of O- distributions. The proportion of O+ distributions increased slightly over time at American centers (2.9%) while decreasing slightly (1.1%) at NPBS despite reductions in the absolute numbers of O+ distributions. Overall there was 2.6% decrease in the proportion of B+ and AB+ RBCs distributed and 13.6% absolute reduction in the number of these units distributed. CONCLUSION: Although overall RBC distributions have decreased over time, the proportion of O units has increased substantially.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".