[Transfusion-related acute lung injury (TRALI) in the Netherlands in 2002-2005].
Bibliographic record
Abstract
OBJECTIVE: To determine the number of reported cases of transfusion-related acute lung injury (TRALI) in the Netherlands in 2002-2005 and to determine how many cases were associated with incompatibility between leukocyte-reactive antibodies in the donor plasma and leukocytes or antigens in the recipient. DESIGN: Retrospective national case review. METHOD: Cases of TRALI reported in 2002-2005 were assessed according to the national clinical definition of TRALI, and the relationship between TRALI and transfusion was assessed. Additional clinical details were requested from the treating hospital as necessary. The results of leukocyte serological tests from donors and recipients were linked to clinical cases. For cases with positive leukocyte serological tests, the relevant blood components and the sex of the donor were recorded. RESULTS: Of the 46 cases reported, 6 had insufficient information. 8 cases did not meet the definition or had another more likely diagnosis. There was a trend toward an increase in the number of reports: 12 cases were reported in 2005, corresponding with 1:60,000 blood components. Of the 40 evaluable cases, 32 (80%) met the definition of TRALI and were deemed to be definitely (n = 16), probably (n = 5) or possibly (n = 11) related to transfusion. Severity ranged from moderate to life-threatening, and there was one TRALI-related death. Leukocyte serology was fully investigated in 18 cases: 13 (72%) had leukocyte incompatibility and in 5 cases exclusively fresh frozen plasma from a female donor was implicated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".