The mechanisms of platelet dysfunction during extracorporeal membrane oxygenation in critically ill neonates
Bibliographic record
Abstract
OBJECTIVE: Although bleeding associated with thrombocytopenia often complicates extracorporeal membrane oxygenation (ECMO), the mechanisms of platelet dysfunction during ECMO remain poorly understood. We investigated the role of matrix metalloproteinase (MMP)-2, which recently has been shown to mediate a novel pathway of platelet aggregation, in the platelet dysfunction induced by ECMO. DESIGN: Prospective longitudinal case study. SETTING: Level III neonatal intensive care unit. PATIENTS: Ten neonates treated with ECMO. INTERVENTION: ECMO procedure. MEASUREMENTS: Platelet counts and collagen-induced platelet aggregation ex vivo; plasma markers of platelet (soluble P-selectin) and endothelial (soluble E-selectin and total nitrite/nitrate) activation; plasma MMP-2 and MMP-9 activities; and concentrations of tissue inhibitors of MMPs. MAIN RESULTS: During ECMO, time-dependent platelet activation, as evidenced by thrombocytopenia, decreased platelet aggregation, and increased plasma soluble P-selectin concentrations were found in the absence of endothelial activation, as shown by normal plasma concentrations of soluble E-selectin and nitric oxide metabolites (nitrite/nitrate). There was a time-dependent increase in plasma MMP-2 but not MMP-9 activity; tissue inhibitors of MMPs were not detected. Plasma soluble P-selectin concentrations significantly correlated with simultaneous plasma MMP-2 (r2 = .37, p < .0001) but not with MMP-9 activities. Platelet dysfunction persisted despite repeated platelet transfusions to maintain platelet counts >100 x 10(9)/L. CONCLUSIONS: ECMO resulted in the activation of platelets but not endothelial cells. During ECMO, platelet dysfunction persisted despite platelet transfusions. MMP-2 may play a role in the development of platelet dysfunction caused by ECMO.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".