A consensus redefinition of transfusion‐related acute lung injury
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Transfusion-related acute lung injury (TRALI) is a serious complication of blood transfusion and is among the leading causes of transfusion-related morbidity and mortality in most developed countries. In the past decade, the pathophysiology of this potentially life-threatening syndrome has been increasingly elucidated, large cohort studies have identified associated patient conditions and transfusion risk factors, and preventive strategies have been successfully implemented. These new insights provide a rationale for updating the 2004 consensus definition of TRALI. STUDY DESIGN AND METHODS: An international expert panel used the Delphi methodology to develop a redefinition of TRALI by modifying and updating the 2004 definition. Additionally, the panel reviewed issues related to TRALI nomenclature, patient conditions associated with acute respiratory distress syndrome (ARDS) and TRALI, TRALI pathophysiology, and standardization of reporting of TRALI cases. RESULTS: In the redefinition, the term "possible TRALI" has been dropped. The terminology of TRALI Type I (without an ARDS risk factor) and TRALI Type II (with an ARDS risk factor or with mild existing ARDS) is proposed. Cases with an ARDS risk factor that meet ARDS diagnostic criteria and where respiratory deterioration over the 12 hours before transfusion implicates the risk factor as causative should be classified as ARDS. TRALI remains a clinical diagnosis and does not require detection of cognate white blood cell antibodies. CONCLUSIONS: Clinicians should report all cases of posttransfusion pulmonary edema to the transfusion service so that further investigation can allow for classification of such cases as TRALI (Type I or Type II), ARDS, transfusion-associated circulatory overload (TACO), or TRALI or TACO cannot distinguish or an alternate diagnosis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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 it