ABSTRACT 237
Bibliographic record
Abstract
Background and aims: Red blood cell (RBC) transfusion is known to cause various respiratory complications. When respiratory dysfunction (RD) appears after a transfusion is administered, it is considered to be a transfusion-associated respiratory dysfunction (TARD). Aims: 1) to determine the incidence of TARD in a pediatric intensive care unit (PICU), 2) to compare the results obtained with two different definitions (diagnostic criteria) for RD. Methods: This is a prospective cohort study of all consecutive admissions to the PICU of Sainte-Justine Hospital over a one-year period. TARD was diagnosed when RD appeared or significantly worsened after the 1st RBC transfusion administered in PICU. Two independent adjudicators used the diagnostic criteria of Goldstein et al (Pediatr Crit Care Med 2005) and Proulx et al (Chest 1996) to diagnose RD. Agreement was measured using concordance percentage and kappa score. IRB approval was obtained for this study. Results: Among the 842 consecutive admissions to the PICU, 136 children received a transfusion. Among these, 58 (43%) patients presented a TARD according to Goldstein’s criteria, while 53 (39%) TARD were diagnosed according to Proulx’s criteria. Concordance between adjudicators for each item varied from 63% to 100%; kappa scores ranged from 0.63 to 1.00. Conclusions: TARD is frequent in PICU (39% to 43% depending on the definition used). While both definitions by Goldstein et al and Proulx et al gave similar results, the definition by Goldstein et al. was more sensitive.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.689 | 0.569 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".