Enhanced Visualization of the Cervical Vertebra during Intraoperative Fluoroscopy Using a Shoulder Traction Device
Bibliographic record
Abstract
STUDY DESIGN: A retrospective, matched cohort study of a prospective database. PURPOSE: To evaluate the efficacy and safety of the Cervision system (Spinologics, Montreal, Canada), a new shoulder traction device that improves the fluoroscopic visualization of the lower cervical spine using caudal traction of the shoulders out of the radiographic field. OVERVIEW OF LITERATURE: Operating at a wrong level is a common error that may be committed by nearly 50% of surgeons during their career. Intraoperative fluoroscopy of the cervical vertebrae is an extremely important step in cervical spine surgery. Optimal lateral cervical radiography of the C1-T1 vertebrae is not always possible due to overlap of the shoulders. METHODS: In this study, a group of patients (n=33, device group) underwent surgery with the new device used to apply caudal traction to both shoulders, and another group of patients (n=33, matched control group) had surgery with the tape traction. Data about the lowest vertebra visible on lateral fluoroscopic view, installation time, skin irritation under the traction area, and postoperative brachial palsy were recorded, and these parameters were analyzed using the t-test. RESULTS: The mean numbers of visible cervical vertebra were 6.3±0.41 in the device group and 5.6±0.32 in the matched control group (p <0.01, unpaired t-test). The mean installation times were 83.9±5.15 minutes in the device group and 73.7±6.32 minutes in the matched control group (p <0.02). Seven patients from the matched control group presented with skin irritation. However, none of the patients from the device group had the condition (p =0.005, Pearson chi-square test). Postoperative brachial palsy was not observed in both groups. CONCLUSIONS: The Cervision system is more effective and superior to tape traction in pulling the shoulders down to improve the visualization of the cervical vertebra on lateral fluoroscopic view during cervical spine surgery.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".