Preparing <scp>small‐dose</scp> red cell concentrates (<scp>RCCs</scp>) for neonatal and pediatric transfusions: Impact of <scp>RCC</scp> volume, storage, and irradiation
Bibliographic record
Abstract
BACKGROUND: Preparing small-dose red cell concentrates (RCCs) is a common practice for pediatric and neonatal transfusions. However, there is a lack of quality monitoring data to indicate that both the preparation and storage of small-dose RCCs does not alter in vitro red cell quality. The present study seeks to provide data to support this practice. MATERIALS AND METHODS: To evaluate quality of stored small aliquots, six ABO/Rh matched leukoreduced citrate phosphate-dextrose/saline-adenine-glucose-mannitol (LR CPD/SAGM) RCCs were pooled and split into 30 ml aliquots, 80 ml aliquots, and a standard 290 ml unit, with testing performed for up to 43 days post-collection. To evaluate the impact of irradiation on small-dose RCC preparation, a total of 48 independent LR CPD/SAGM RCCs were used (non-irradiated: n = 24; irradiated: n = 24). Aliquoting with/without irradiation was performed within 7 days of collection and baseline testing was performed within 24 h of aliquot production. RESULTS: Limited variability in hemolysis, mean cell volume, and extracellular potassium concentrations were seen between the different aliquot sizes throughout the 43-day storage period. Aliquot production did not accentuate damage based on any of these tested parameters in both the non-irradiated and irradiated subsets. A significant increase was seen in the potassium concentrations in the irradiated parent and aliquot samples relative to their non-irradiated counterparts. CONCLUSIONS: Non-irradiated small-aliquot dose RCCs meet in vitro quality criteria required for safe transfusion throughout the 42-day storage period. The same can be said for aliquots derived from irradiated units and tested within 24 h of aliquot production.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".