Abstract 18481: Genetic Polymorphisms Associated with Response to Intraoperative Heparin Anticoagulation and Thrombosis Risk in Pediatric Patients Undergoing Cardiac Surgery
Bibliographic record
Abstract
Introduction: Thrombosis is an important and widespread post-operative complication of pediatric cardiac surgery. Prophylaxis intraoperative anticoagulation in this context is obtained by using heparin which requires a bond with antithrombin to achieve anticoagulant effect. We sought to identify SNPs associated with blood antithrombin levels, response to heparin and post-operative thrombosis risk in pediatric patients undergoing cardiac surgery with cardiopulmonary bypass (CPB). Methods: A total of 625 cardiac operations with CPB in 383 patients were reviewed. Ninety-six SNPs on 53 genes in the coagulation/fibrinolysis pathways were assayed using the the Illumina GoldenGate custom SNP panel. Genotyping was successful for >99% of SNPs. Regression models adjusted for repeated measures and bootstrap resampling (1,000 samples) were used to offset multiple comparisons bias; SNPs with very low minor allele frequencies were excluded. Results: Average preoperative antithrombin activity was 89±18% (normal 100%, adjusted for age and oxygen saturation) and average response to heparin was 1.0±0.3U/ml/100U/kg (blood heparin concentration achieved per 100U/kg of heparin). Post-operative thrombosis was observed after 86 operations (14%) (within 30 days of surgery, risk-adjusted according to a previously published model of post-operative thrombosis risk). SNPs associated with higher antithrombin levels, lower heparin response and higher postoperative thrombosis are listed in the Table. Conclusions: Polymorphisms in genes in the coagulation and fibrinolytic systems activity were associated with antithrombin levels, response to heparin and risk of post-operative thrombosis. The association of individual SNPs at the laboratory and clinical levels suggest a mechanism for upstream alteration in the coagulation system that is correlated with undesirable clinical outcome and could be the target for genetically tailored clinical interventions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".