Training Distal Locking Screw Insertion Skills to Novice Trainees
Bibliographic record
Abstract
OBJECTIVES: To compare the effect fluoroscopy or electromagnetic (EM) guidance has on the learning of locking screw insertion in tibial nails in surgical novices. METHODS: A randomized, prospective, controlled trial was conducted involving 18 surgical trainees with no prior experience inserting locking screws in intramedullary nails. After a training session using fluoroscopy, participants underwent a pretest using fluoroscopic guidance. Participants were then randomized into either the fluoroscopy or EM group and were further trained using their respective technique. Post, retention, and transfer tests were conducted. Outcomes included task completion, drill attempts, screw changes, and radiation time. RESULTS: Intragroup comparisons revealed that the EM group used significantly less drill attempts during the post and retention tests compared with the pretest (P = 0.016 and P = 0.016, respectively). Intergroup comparisons revealed that the EM group was (1) more likely to complete the task during the retention test (P = 0.043) and (2) had significantly less radiation time during the post and retention tests (P = 0.002 and P = 0.003, respectively). Radiation time in the EM group during the transfer test increased to a level equal to what the fluoroscopy group used during the post and retention tests (P = 0.71 and P = 0.92, respectively). No other significant between-group differences occurred. CONCLUSIONS: EM guidance may be safely used to assist in the training of surgical novices in the skill of distal locking screw insertion. Not only does this technology significantly improve the ability to complete the task and decrease radiation use but also it does so without compromising skill acquisition. LEVEL OF EVIDENCE: Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".