Comparative Results Between Conventional and Computer-Assisted Pedicle Screw Installation in the Thoracic, Lumbar, and Sacral Spine
Bibliographic record
Abstract
STUDY DESIGN: A comparative study on the position of pedicle screws in patients treated surgically with and without computer assistance. OBJECTIVES: To evaluate the accuracy of computer-assisted pedicle screw installation, and to evaluate its clinical benefit as compared with conventional pedicle screw installation techniques. SUMMARY OF BACKGROUND DATA: In vitro and clinical studies have documented a significant rate of misplaced screws in the thoracolumbar area. Neurologic complications are recognized problems caused by screw misplacement. METHODS: Patients treated surgically with computer assistance were compared with a historical control group of patients treated surgically with conventional techniques in the same hospital and by the same surgical team. All screw positions were measured with a postoperative magnetic resonance tomography, and cortical effractions were categorized in 2-mm increments. Patients' charts also were reviewed to assess individual neurologic outcomes. RESULTS: The control cohort was composed of 100 patients, with 544 screws from T5 to S1. The computer-assisted cohort was composed of 50 patients, with 294 screws from T2 to S1. In the control cohort, 461 of 544 screws (85%) were found completely within their pedicles as compared with 278 of 294 screws (95%) correctly placed in the computer-assisted group (P < 0.0001). All 16 screws incorrectly placed with computer assistance were found 0.1 mm to 2 mm from the pedicle cortex. In the control cohort, 68 screws were found 0.1 mm to 2 mm, 10 screws 2.1 mm to 4 mm, and 5 screws more than 4 mm from the pedicle cortex. Seven patients in the control cohort were surgically retreated because of postoperative neurologic deficits, whereas no patients in the computer-assisted group were surgically retreated. CONCLUSIONS: Computer assistance can decrease the incidence of incorrectly positioned pedicle screws.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".