Computer-Assisted Guidewire Insertion for Hip Fracture Fixation
Bibliographic record
Abstract
OBJECTIVE: : This study was designed to test in a laboratory setting a novel computer-assisted fluoroscopic technique and a conventional fluoroscopic technique for open reduction and internal fixation (ORIF) of hip fractures. Our hypothesis is that a novel computer-assisted fluoroscopic technique will achieve acceptable guidewire placement in one pass, with decreased fluoroscopic time and with accuracy and precision better than conventional technique. DESIGN: Prospective, randomized trials. SETTING: Laboratory. PARTICIPANTS: Thirty, Sawbone, femur phantoms. INTERVENTION: Dynamic hip screw guidewires were inserted into 15 femur phantoms under fluoroscopic guidance by using computer-assisted fluoroscopic ORIF technique, and 15 femurs were inserted by using a conventional fluoroscopic-assisted ORIF technique. MAIN OUTCOME MEASUREMENTS: Ideal guidewire placement was defined as the center of the femoral head, 5 mm from the apical bone edge on anteroposterior and lateral views. Accuracy was measured as distance to ideal placement, and the number of passes and fluoroscopic time were noted for each trial. RESULTS: The computer-assisted technique achieved an average guidewire placement that was as accurate as the conventional technique in fewer passes, 1.1 +/- 0.2 (mean +/- standard deviation) compared with 2.4 +/- 1.1 (P < 0.0001), respectively, and with fewer fluoroscopic images, 2 +/- 0 compared with 13.5 +/- 3 (P < 0.0002), respectively. Guidewire placement in both groups was within the tip-apex distance defined by Baumgaertner et al. CONCLUSIONS: The computer-assisted technique was significantly more accurate and precise than conventional technique. It also required fewer drill tracks through the femur and exposed the patient and the surgical team to significantly less ionizing radiation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".