Assessment of Impact of Long-Cassette Standing X-Rays on Surgical Planning for Cervical Pathology
Bibliographic record
Abstract
BACKGROUND: Understanding the role of regional segments of the spine in maintaining global balance has garnered significant attention recently. Long-cassette radiographs (LCR) are necessary to evaluate global spinopelvic alignment. However, it is unclear how LCRs impact operative decision-making for cervical spine pathology. OBJECTIVE: To evaluate whether the addition of LCRs results in changes to respondents' operative plans compared to standard imaging of the involved cervical spine in an international survey of spine surgeons. METHODS: Fifteen cases (5 control cases with normal and 10 test cases with abnormal global alignment) of cervical pathology were presented online with a vignette and cervical imaging. Surgeons were asked to select a surgical plan from 6 options, ranging from the least (1 point) to most (6 points) extensive. Cases were then reordered and presented again with LCRs and the same surgical plan question. RESULTS: One hundred fifty-seven surgeons completed the survey, of which 79% were spine fellowship trained. The mean response scores for surgical plan increased from 3.28 to 4.0 (P = .003) for test cases with the addition of LCRs. However, no significant changes (P = .10) were identified for the control cases. In 4 of the test cases with significant mid thoracic kyphosis, 29% of participants opted for the more extensive surgical options of extension to the mid and lower thoracic spine when they were provided with cervical imaging only, which significantly increased to 58.3% upon addition of LCRs. CONCLUSION: In planning for cervical spine surgery, surgeons should maintain a low threshold for obtaining LCRs to assess global spinopelvic alignment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".