Pediatric Mechanical Circulatory Support: Pathophysiology of Pediatric Hemostasis and Available Options
Bibliographic record
Abstract
Pediatric mechanical circulatory support (MCS) is considered a strategy for heart failure management as a bridge to recovery and transplantation or as a destination therapy. The final outcome is significantly impacted by the number of complications that may occur during MCS. Children on ventricular assist devices (VADs) and extracorporeal membrane oxygenation (ECMO) are at high risk for bleeding and thrombotic complications that are managed through anticoagulation. The first detailed guideline in pediatric VADs (Edmonton Anticoagulation and Platelet Inhibition Protocol) was based on conventional antithrombotic drugs, such as unfractionated heparin (UFH) and warfarin. UFH is the first-line anticoagulant in pediatric MCS, although its profile is not considered optimal in pediatric setting. The broad variation in heparin doses among children is associated with frequent occurrence of cerebrovascular accidents, bleeding, and thrombocytopenia. Direct thrombin inhibitors (DTIs) have been utilized as alternative strategies to heparin. Since 2018, bivalirudin has become the chosen anticoagulant in the long-term therapy of patients undergoing MCS implantation, according to the most recent protocols shared in North America. This article provides a review of the non-traditional anticoagulation strategies utilized in pediatric MCS, focusing on pharmacodynamics, indications, doses, and monitoring aspects of bivalirudin. Moreover, it exposes the efforts and the collaborations among different specialized centers, which are committed to an ongoing learning in order to minimize major complications in this special pediatric population. Further prospective trials regarding DTIs in a pediatric MCS setting are necessary and in specific well-designed randomized control trials between UFH and bivalirudin. To conclude, based on the reported literature, the clinical use of the bivalirudin in pediatric MCS seems to be a value added in controlling and maybe reducing thromboembolic complications. Further research is necessary to confirm all the results provided by this literature review.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".