Navigated percutaneous screw fixation of the pelvis with O-arm 2: two years’ experience
Bibliographic record
Abstract
<p><strong>Aim <br /></strong>To evaluate the case series of the patients operated with percutaneous fixation by the navigation system based on 3D fluoroscopic images, to assess the precision of a surgical implant and functional outcome of patients.<br /><strong>Methods <br /></strong>A retrospective study of pelvic ring fractures in a 2-year period included those treated with the use of the O-Arm 2 in combination with the Stealth Station 8. Pelvic fractures were classified according to the Tile and the Young-Burgess classification. All patients were examined before surgery, with X-rays and CT scans, and three days after surgery with additional CT scan. The positioning of the screws was evaluated according to the Smith score, the outcome with the SF-36.<br /><strong>Results</strong> <br />Among 24 patients 18 were with B and six with C type fracture according to Tile, while eight were with APC, 10 LC, and<br />six with VS type according to Young-Burgess classification. All patients were treated in the supine position, except two. A total of 41 iliosacral or transsacral screws and five anterior pelvic ring screws were implanted. The medium surgical time per screw was 41 minutes. There was a perfect correspondence of screw scores value from post-operative CT and intraoperative fluoroscopy. The mean screw score value was 0.92. There were no cases of poor positioning. The median follow-up was 17.5 months. The patients were satisfied with their health condition on SF-36.<br /><strong>Conclusion </strong><br />The use of the O-arm guarantees great precision in the positioning of the screws and reduced surgical times with excellent<br />clinical results in patients.</p>
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".