Risk analysis of transfusion of cryoprecipitate without consideration of <scp>ABO</scp> group
Bibliographic record
Abstract
BACKGROUND: Transfusion medicine standards in Canada state that adult recipients can be transfused with cryoprecipitate of any ABO group, however, not all hospitals follow this guideline. There is a paucity of data on cryoprecipitate anti-A/B levels to reinforce standards. STUDY DESIGN AND METHODS: Manual tube antibody titration was performed on 7 units of group O plasma and the corresponding cryosupernatant plasma and cryoprecipitate. IgG/IgM levels were determined by nephelometry. Additionally, 10 cryoprecipitate each from groups A, B, and O were similarly assessed. From the antibody titer distribution among these samples, the probability of making a pool of cryoprecipitate with a titer ≥1:100 was calculated using bootstrap analysis. RESULTS: Anti-A/B titers in cryoprecipitate were equivalent to those in corresponding plasma; partitioning of anti-A/B activity into cryoprecipitate was not observed. Average IgM concentration was higher in cryoprecipitate than in plasma (P < .01). However, no correlation between IgM levels and anti-A/B titers was established. Among 30 cryoprecipitates from routine blood bank inventory, the median antibody titer and mode were 1:32 and 1:16, respectively. Of the samples tested, 4 of 30 and 9 of 30 had titers above 1:100 and 1:50, respectively. The probability of transfusing an adult dose of cryoprecipitate (pool of 10 cryoprecipitate) with a titer higher than 1:100 was calculated to be less than 1 in 3 million. CONCLUSIONS: This study provides strong evidence to support current Canadian transfusion medicine standards on the safety of transfusion of cryoprecipitate without the need for blood group matching in adult recipients.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".