Superior vena cava flow and management of neonates with vein of Galen malformation
Bibliographic record
Abstract
OBJECTIVE: Vein of Galen malformation (VGAM) in neonates presents a complex management challenge. Measurement of superior vena cava (SVC) blood flow may provide insights into the haemodynamics of VGAM and the effects of therapeutic intervention. METHODS: SVC flow was assessed in 15 neonates with VGAM. SVC flow results, Bicêtre scores (clinical assessment), echocardiographic assessment and clinical outcomes are presented. RESULTS: SVC flows (166-581 ml/kg/min) were significantly elevated at presentation (p<0.001; normal range 55-111 ml/kg/min). Endovascular intervention was undertaken in 12 cases, with nine survivors. SVC flows decreased sequentially with each embolisation, with a median SVC flow at discharge of 124 ml/kg/min (IQR 79-155 ml/kg/min). All cases with SVC flow >400 ml/kg/min (n=5) had an adverse outcome (death or profound neurological damage). Cases with SVC flow <400 ml/kg (n=10) required embolisation before discharge at a median age of 6 days. There were no survivors with Bicêtre scores <8 (n=2) but the predictive value of early Bicêtre score was poor. CONCLUSIONS: SVC flow measurements provide insight into the haemodynamic challenges of VGAM and provide additional useful prognostic information.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".