Training and Evaluating Spinal Surgeons
Bibliographic record
Abstract
STUDY DESIGN: Cohort study. OBJECTIVE: The purpose of this study was to develop and validate a series of novel assessment measures for use during a lumbar pedicle cannulation task. SUMMARY OF BACKGROUND DATA: There is increasing pressure being placed on the surgical community to develop appropriate assessment measures of technical skills as an indicator of surgical competence. To date, little research has been performed in this area in spinal surgery. METHODS: Twelve novice and 7 expert spine surgeons cannulated a complete set of lumbar pedicles on a synthetic model. Electromagnetic markers were traced to record their dominant hand and arm movements while the forces applied to the model were measured using a small force plate. The amount of wrist motion, mean forces, peak forces, and task time were evaluated. Following task completion, angles of pedicle cannulation and the number and location of all breaches in the models were recorded. RESULTS: Novice surgeons used less mean force (91 N vs. 115 N, P = 0.001) but required more time to perform each cannulation task (12.4 seconds vs. 8.2 seconds, P < 0.001). Cannulation by novices demonstrated a greater mean number of frank (far lateral) pedicle breaches (1.5 vs. 0 per individual, P = 0.002), but no differences in the angles of cannulation were seen (P = 0.988). CONCLUSION: Four variables, 3 involving process measures and 1 an outcome measure, can be used to distinguish between novice and expert spine surgeons using a simple lumbar spine pedicle cannulation task, providing evidence of their construct validity. Knowledge of these differences may be useful in objective evaluation of surgical competence and providing precise feedback during the training of this skill, thereby enhancing learning.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".