Evaluation of the performance of Trima Accel® v5.2 for the collection of concentrated high‐dose platelet products and concurrent plasma from high platelet count donors, in germany
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: This study was undertaken to test the ability of Trima Accel® version 5.2 to simultaneously collect concentrated high-dose leukoreduced platelet products and double doses of plasma. MATERIALS AND METHODS: Random volunteers (18-65 years of age) with preprocedure platelet counts above 270 × 10(3) /μl were recruited among the blood center's apheresis donors. All complied with the center's donor selection criteria. RESULTS: One hundred fourteen (114) collections were performed. Depending on which definition of single platelet dose is used (2.0 × 10(11) as prevalent standard in most European countries, and 3.0 × 10(11) as prevalent standard in the United States and Canada) in 107/114 (single dose = 2.0 × 10(11) ) and 39/114 (single dose = 3.0 × 10(11) ) instances, a triple platelet product was obtained. In 87 cases (76%), a double plasmaproduct (>430 ml) was collected, and in seven cases (6%), a single plasma product (>220 ml) was collected. In 20 procedures, only platelets without concurrent plasma were collected (18%). Overall procedure time was 87 ± 13 min and average platelet yield per procedure was 8.5 ± 1.4 × 10(11) (final storage concentration, 1,279 ± 153 × 10(3) /μl). The median residual leukocyte content per transfusion dose was 0.13 × 10(6) (0.02-0.98 × 10(6) ) for a single dose of 2.0 × 10(11) and 0.14 × 10(6) (0.02-0.98 × 10(6) ) for a single dose of 3.0 × 10(11) . CONCLUSIONS: Trima Accel® version 5.2 allows for collection of concentrated high yield platelet products. It offers high productivity and reliably achieves the configured yield targets. Leukoreduction performance complied with both US and EU legal requirements. Collection as hyperconcentrates furthermore allowed for concurrent collection of double dose plasma in the majority of the procedures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".