Apheresis platelets are more frequently associated with adverse reactions than pooled platelets both in recipients and in donors: a study from <scp>F</scp>rench hemovigilance data
Bibliographic record
Abstract
BACKGROUND: Controversy exists regarding the safety of the different types of platelet (PLT) concentrates. This study was aimed at comparing the rate of adverse reactions associated with apheresis PLT concentrates (APCs) and pooled PLT concentrates (PPCs) both in donors and in recipients. STUDY DESIGN AND METHODS: From the French national hemovigilance system, types and numbers of recipient adverse reactions were compared over a period from 2009 to 2011. Donor adverse reactions were available for 2010 and 2011. This study involved 23 of 26 French regions. Main outcomes were the rates of adverse reaction in recipients and serious adverse reaction in donors. RESULTS: There were 790,854 PLT transfusions during the study period (477,747 [60%] with APCs, 313,107 [40%] with PPCs). APCs were associated with more adverse reactions (6244 vs. 2469 per 1,000,000, p < 0.001) and more severe and life-threatening reactions (respectively, 241 vs. 131 per 1,000,000, p < 0.001; and 182 vs. 121 per 1,000,000, p = 0.04). Mortality rates due to an adverse transfusion reaction were similar (15 vs. 6 per 1,000,000, p = 0.5). In donors, the number of whole blood (WB) donations was 4,722,685 whereas 266,095 apheresis procedures were performed. Serious adverse reactions were more frequent for apheresis procedures than for WB donations (5445 vs. 803 per 1,000,000, p < 0.001). CONCLUSION: Our findings suggest that apheresis PLTs may be more hazardous than pooled PLTs both in recipients and in donors. This study calls for randomized trials to confirm or refute these results.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".