Patient‐tailored platelet transfusion practices for children supported by extracorporeal membrane oxygenation
Bibliographic record
Abstract
Abstract Background and Objectives Extracorporeal membrane oxygenation (ECMO) serves as cardiopulmonary therapy in critically ill patients with respiratory/heart failure and often necessitates multiple blood product transfusions. The administration of platelet transfusions during ECMO is triggered by the presence or risk of significant bleeding. Most paediatric ECMO programmes follow guidelines that recommend a platelet transfusion threshold of 80–100 × 109/L. To reduce exposure to platelets, we developed a practice to dynamically lower the threshold to ~20 × 109/L. We describe our experience with patient‐tailored platelet thresholds and related bleeding outcomes. Materials and Methods We retrospectively evaluated our platelet transfusion policy, bleeding complications and patient outcome in 229 ECMO‐supported paediatric patients in our unit. Results We found that more than 97.4% of patients had a platelet count <100 × 109/L at some point during their ECMO course. Platelets were transfused only on 28.5% of ECMO days; and 19.2% of patients never required a platelet transfusion. The median lowest platelet count in children who had bleeding events was 25 × 109/L as compared to 33 × 109/L in children who did not bleed (p < 0.001). Our patients received fewer platelet transfusions and did not require more red blood cell transfusions, nor did they experience more haemorrhagic complications. Conclusion We have shown that a restrictive, ‘patient‐tailored’ rather than ‘goal‐directed’ platelet transfusion policy is feasible and safe, which can greatly reduce the use of platelet products. Although there was a difference in the lowest platelet counts in children who bled versus those who did not, the median counts were much lower than current recommendations.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".