Temporal and Anatomic Risk Profile of Brain Injury With Neonatal Repair of Congenital Heart Defects
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Brain injury is common in newborns with congenital heart disease (CHD) requiring neonatal surgery. The purpose of this study is to define the risk factors for preoperative and postoperative brain injuries and their association with functional cardiac anatomic groups. METHODS: Sixty-two neonates with CHD were studied with preoperative MRI, and 53 received postoperative scans. Clinical and therapeutic characteristics were compared in newborns with and without newly acquired brain injuries. A subset of 16 consecutive patients was monitored with intraoperative cerebral near-infrared spectroscopy. RESULTS: Brain injury was observed in 56% of patients. Preoperative brain injury, seen in 39%, was most commonly stroke and was associated with balloon atrial septostomy (P=0.002). Postoperative brain injury, seen in 35%, was most commonly white matter injury and was particularly common in neonates with single-ventricle physiology and aortic arch obstruction (P=0.001). Risk factors associated with acquired postoperative brain injury included cardiopulmonary bypass (CPB) with regional cerebral perfusion (P=0.01) and lower intraoperative cerebral hemoglobin oxygen saturation during the myocardial ischemic period of CPB (P=0.008). In a multivariable model, new postoperative white matter injury was specifically associated with low mean blood pressure during the first postoperative day (P=0.04). CONCLUSIONS: Specific modifiable risk factors can be identified for preoperative and postoperative white matter injury and stroke associated with neonatal surgery for CHD. The high incidence of postoperative injury observed despite new methodologies of CPB indicates the need for ongoing evaluation to optimize neurological outcome.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".