Surgeon Reported Outcome Measure for Spine Trauma
Bibliographic record
Abstract
STUDY DESIGN: International web-based survey. OBJECTIVE: To identify clinical and radiological parameters that spine surgeons consider most relevant when evaluating clinical and functional outcomes of subaxial cervical spine trauma patients. SUMMARY OF BACKGROUND DATA: Although an outcome instrument that reflects the patients' perspective is imperative, there is also a need for a surgeon reported outcome measure to reflect the clinicians' perspective adequately. METHODS: A cross-sectional online survey was conducted among a selected number of spine surgeons from all five AOSpine International world regions. They were asked to indicate the relevance of a compilation of 21 parameters, both for the short term (3 mo-2 yr) and long term (≥2 yr), on a five-point scale. The responses were analyzed using descriptive statistics, frequency analysis, and Kruskal-Wallis test. RESULTS: Of the 279 AOSpine International and International Spinal Cord Society members who received the survey, 108 (38.7%) participated in the study. Ten parameters were identified as relevant both for short term and long term by at least 70% of the participants. Neurological status, implant failure within 3 months, and patient satisfaction were most relevant. Bony fusion was the only parameter for the long term, whereas five parameters were identified for the short term. The remaining six parameters were not deemed relevant. Minor differences were observed when analyzing the responses according to each world region, or spine surgeons' degree of experience. CONCLUSION: The perspective of an international sample of highly experienced spine surgeons was explored on the most relevant parameters to evaluate and predict outcomes of subaxial cervical spine trauma patients. These results form the basis for the development of a disease-specific surgeon reported outcome measure, which will be a helpful tool in research and clinical practice. LEVEL OF EVIDENCE: 4.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".