Management of Severe Craniofacial Vascular Malformation Operated Under Bypass
Bibliographic record
Abstract
BACKGROUND: Cardiopulmonary bypass (CBP) and circulatory arrest as an assist in the surgical excision of a severe facial vascular malformation were first described by Mulliken et al in 1979. Later on, its use had expanded for resection of intracranial vascular malformations. However, to date, there have not been any published series of these procedures being used in the resection of craniofacial vascular malformations. We sought to review the first 10 surgical procedures performed at McGill University Health Centre for large vascular malformations resection using hypothermic CBP with or without circulatory arrest. METHODS: All consecutive patients at the McGill University Health Centre who had a craniofacial vascular malformation resected with the aid of CBP were reviewed. A comparison of the classic midline sternotomy with cardiac arrest to percutaneous femoral bypass with hypothermic "low flow" was performed. Charts were reviewed for the operative intervention including bypass parameters and short- and long-term complications of the procedure. RESULTS: Cardiopulmonary bypass was used in 9 patients for 10 surgical procedures for the resection of a variety of craniofacial vascular malformations from 1987 to 2001. All lesions had sclerotherapy and embolization of the feeding vessels 72 to 96 hours preoperatively. The average age of our patients was 21 ± 13.4 years (2-37 years). Procedures were conducted via either an open bypass or a closed femoral approach. There were no mortalities. There were 2 major cardiac intraoperative complications and 1 major postoperative complication, which were managed with no sequelae. The average length of postoperative hospital stay was 10 days. All patients went on to full recovery. The blood transfusions varied from 10 U to 0 U for our last patient. CONCLUSIONS: The assistance and adjunct of CBP are a useful procedure in the resection of very large vascular malformations, in selected cases. There were no major long-term complications in this series. With the evolution of our approach, the use of complete circulatory arrest was not required in the majority of cases, and an adequate resection was usually possible with the low-flow state alone as we developed this technique with more experience through the process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".