Part 1: Pushing the boundaries of neurointerventional surgery: A historical review of the work of Dr Gerard Debrun
Bibliographic record
Abstract
French-American neurointerventionalist and pioneer, Dr Gerard Debrun, laid the groundwork for treatments which have become irreplaceable in neurointerventional surgery today. This article aims to outline the career of Dr Debrun while highlighting his accomplishments and contributions to the field of neurointerventional surgery. We selected relevant articles from PubMed authored or co-authored by Dr Debrun between 1941 and 2023. All included articles discuss the accomplishments and contributions of Dr Debrun. Dr Debrun began his career in France by investigating neurointerventional techniques, most notably the intravascular Detachable Balloon Catheter (DBC). His work was recognized by renowned neurosurgeon Dr Charles Drake, who recruited him to London, Ontario. Dr Debrun created the foundation for homemade manufacturing of DBCs, building on one of the largest series for use of DBCs in cerebrovascular disease. Dr Debrun spent time as faculty at Massachusetts General Hospital (MGH) and Johns Hopkins Hospital, before arriving at the University of Illinois Chicago (UIC) where he remained until his retirement. Dr Debrun's subsequent contributions included the calibrated-leak balloon catheter, pioneering of glue embolization, setting the foundation for preoperative AVM embolizations, and as an early adopter of the Guglielmi detachable coil (GDC), including mastering the balloon remodeling technique for wide neck aneurysms. Dr Debrun established the first integrated neurointerventional surgery program at UIC, establishing a well sought-after fellowship program. Dr Debrun lectured extensively and was a prolific writer on neurointerventional surgery throughout this career. His contributions established the foundation for several techniques which have since become standard practice in present-day neurointerventional surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".