Incidence of hypotension and acute hypotensive transfusion reactions following platelet concentrate transfusions
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Platelet concentrates (PCs) are associated with transfusion reactions involving hypotension, particularly bradykinin-mediated acute hypotensive transfusion reactions. This study aims to determine the incidence of hypotensive events and more specifically acute hypotensive transfusion reaction associated with PC transfusions. We also sought to ascertain whether these reactions are associated with elevated bradykinin levels. MATERIALS AND METHODS: This is a prospective descriptive study of PCs administered at Sainte-Justine Hospital over 28 months. All PCs administered during this period were screened for hypotension through review of all transfusion-associated reaction reports (TARRs) sent to the blood bank. All residual PC bags were returned to the blood bank. TARRs associated with hypotension were reviewed by adjudicators that established the imputability of the PC transfusion to the reaction. Bradykinin levels were sampled in the first 168 PC bags returned to the blood bank. Levels were compared between PCs associated with hypotension and control PCs not associated with hypotension. RESULTS: A total of 3672 PC bags were returned to the blood bank; 25 PCs were associated with hypotension. Adjudicators ascertained that five hypotensive events were imputable to PCs of which one was an acute hypotensive transfusion reaction (incidence: 0·03%). Bradykinin level in the latter PC was 10 pg/ml, whereas levels were 226·2 ± 1252 pg/ml in the 143 control PCs. CONCLUSION: Our results show a low incidence of hypotension after PC transfusion. We identified only one acute hypotensive transfusion reaction. No correlation between bradykinin level and the occurrence of acute hypotensive reactions could be observed given that only one event was identified.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".