Transfusion of pooled buffy coat platelet components prepared with photochemical pathogen inactivation treatment: the euroSPRITE trial
Bibliographic record
Abstract
A nucleic acid-targeted photochemical treatment (PCT) using amotosalen HCl (S-59) and ultraviolet A (UVA) light was developed to inactivate viruses, bacteria, protozoa, and leukocytes in platelet components. We conducted a controlled, randomized, double-blinded trial in thrombocytopenic patients requiring repeated platelet transfusions for up to 56 days of support to evaluate the therapeutic efficacy and safety of platelet components prepared with the buffy coat method using this pathogen inactivation process. A total of 103 patients received one or more transfusions of either PCT test (311 transfusions) or conventional reference (256 transfusions) pooled, leukoreduced platelet components stored for up to 5 days before transfusion. More than 50% of the PCT platelet components were stored for 4 to 5 days prior to transfusion. The mean 1-hour corrected count increment for up to the first 8 test and reference transfusions was not statistically significantly different between treatment groups (13,100 +/- 5400 vs 14,900 +/- 6200, P =.11). By longitudinal regression analysis for all transfusions, equal doses of test and reference components did not differ significantly with respect to the 1-hour (95% confidence interval [CI], -3.1 to 6.1 x 10(9)/L, P =.53) and 24-hour (95% CI, -1.3 to 6.5 x 10(9)/L, P =.19) posttransfusion platelet count. Platelet transfusion dose, pretransfusion storage duration, and patient size were significant covariates (P <.001) for posttransfusion platelet counts. Clinical hemostasis, hemorrhagic adverse events, and overall adverse events were not different between the treatment groups. Platelet components prepared with PCT offer the potential to further improve the safety of platelet transfusion using technology compatible with current methods to prepare buffy coat platelet components.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".