Predictors of an academic career among fellowship-trained open vascular and endovascular neurosurgeons
Bibliographic record
Abstract
OBJECTIVE: Although previous studies have explored factors that predict an academic career among neurosurgery residents in general, such predictors have yet to be determined within specific neurosurgical subspecialties. The authors report on predictors they identified as correlating with academic placement among fellowship-trained vascular neurosurgeons. METHODS: A database was created that included all physicians who graduated from ACGME (Accreditation Council for Graduate Medical Education)-accredited neurosurgery residency programs between 1960 and 2018 using publicly available online data. Neurosurgeons who completed either open vascular or endovascular fellowships were identified. Subsequent employment of vascular or endovascular neurosurgeons in academic centers was determined. A position was considered academic if the hospital of employment was affiliated with a neurosurgery residency program; all other positions were considered non-academic. Bivariate analyses were conducted using Fisher's exact test or the Mann-Whitney U-test, and multivariate analysis was performed using a logistic regression model. RESULTS: A total of 83 open vascular neurosurgeons and 115 endovascular neurosurgeons were identified. In both cohorts, the majority of neurosurgeons were employed in academic positions after training. In bivariate analysis, only 2 factors were significantly associated with a career in academic neurosurgery for open vascular neurosurgeons: 1) an h-index of ≥ 2 during residency (OR 3.71, p = 0.016), and 2) attending a top 10 residency program based on U.S. News and World Report rankings (OR 4.35, p = 0.030). In bivariate analysis, among endovascular neurosurgeons, having an h-index of ≥ 2 during residency (OR 4.35, p = 0.0085) and attending a residency program affiliated with a top 10 U.S. News and World Report medical school (OR 2.97, p = 0.029) were significantly associated with an academic career. In multivariate analysis, for both open vascular and endovascular neurosurgeons, an h-index of ≥ 2 during residency was independently predictive of an academic career. Attending a residency program affiliated with a top 10 U.S. News and World Report medical school independently predicted an academic career among endovascular neurosurgeons only. CONCLUSIONS: The authors report that an h-index of ≥ 2 during residency predicts pursuit of an academic career among vascular and endovascular neurosurgeons. Additionally, attendance of a residency program affiliated with a top research medical school independently predicts an academic career trajectory among endovascular neurosurgeons. This result may be useful to identify and mentor residents interested in academic vascular neurosurgery.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".