Low antithrombin levels in neonates and infants undergoing congenital heart surgery result in more red blood cell and plasma transfusion on cardiopulmonary bypass
Bibliographic record
Abstract
BACKGROUND: Neonates have lower levels of antithrombin (AT) due to immature liver synthetic function. AT deficiency may lead to inadequate anticoagulation with heparin during cardiac surgery resulting in consumption of coagulation factors and increased blood transfusion. The goal of this study is to examine the effect of AT level on the transfusion requirements of neonates and infants undergoing open heart surgery. STUDY DESIGN AND METHODS: This is a prospective, observational study at a tertiary pediatric referral center. Neonates and infants up to 6 months of age undergoing congenital heart surgery with cardiopulmonary bypass (CPB) were enrolled. Demographic, intraoperative, transfusion, and complications data were collected. Preoperative AT level was measured after induction of anesthesia. Prior to separation from CPB, a second blood sample was drawn and AT, thrombin antithrombin complex (TAT), D-dimer, and anti-Xa levels were measured. Linear and logistic regression were performed for data analysis. RESULTS: Preoperative low AT level was significantly associated with increased transfusion of red blood cells (RBCs) and fresh frozen plasma (FFP) during CPB, but not after separation from CPB. The incidence of thrombosis and re-operation were not associated with preoperative AT levels. There was no association between TAT, D-dimer, and anti-Xa levels at the end of CPB and preoperative AT levels. CONCLUSION: Low preoperative AT level is associated with increased transfusion of RBC and FFP on CPB in neonates and infants undergoing congenital heart surgery. Low preoperative AT level did not result in coagulation activation after CPB and after surgery.
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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 | 0.003 |
| 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 | 0.001 |
| 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".