The impact of discontinuation of 7‐day storage of apheresis platelets (PASSPORT) on recipient safety: an illustration of the need for proper risk assessments
Bibliographic record
Abstract
BACKGROUND: Seven-day stored apheresis platelets (APs) were withdrawn from the US market after detection of two culture-positive units from 2571 tested at outdate in the PASSPORT surveillance study. The impact of this discontinuation on recipient safety was explored using mathematical modeling. STUDY DESIGN AND METHODS: Risk models for septic transfusion reactions (STRs) and transfusion-related acute lung injury (TRALI) were developed. Key assumptions were 400,000 annual APs transfused, equivalent STR risk for platelets (PLTs) stored for 5 days or more and zero for PLTs stored for less than 5 days, whole blood-derived PLTs (WBplts) administered in 5-unit pools, a 4.6-fold higher risk of false-negatives with surrogate versus culture-based bacterial testing, an AP TRALI risk between 1 per 1000 and 1 per 10,000, and a delay in TRALI risk reduction implementation in some centers by 6 to 12 months due to limited PLT availability. RESULTS: STR risk could increase, decrease, or remain the same depending on the percentage of inventory replaced by surrogate-tested WBplts versus culture-tested apheresis or whole blood PLTs. A delay in TRALI risk reduction implementation is likely to result in a comparable or greater risk during the delayed implementation period than the safety achieved with regard to STRs, even in the most favorable case scenario. CONCLUSION: A comprehensive risk assessment should have been conducted before the decision to discontinue PASSPORT. Risk assessments using accepted methods (and actual data when available) should precede any major blood safety decisions.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".