P.136 Quantifying potential sources of delay in surgical management of cervical spondylotic myelopathy
Bibliographic record
Abstract
Background: Cervical spondylotic myelopathy is a degenerative condition with a variable clinical course. We aim to quantify the sources of potential delay in management and understand how the timing of these events may affect quality of life measures. Methods: The Canadian Spine Outcomes Research Network Registry was used to identify patients older than 18 years of age and have received cervical decompression surgery from January 1, 2013 to March 1, 2016. The primary outcome was the Short Form-12 Physical Component Score at 12-month follow-up. Four time groups were identified: 1) duration of symptoms, 2) time awaiting surgical consult, 3) time spent monitoring symptoms, and 4) time awaiting surgery. -Multivariate regression was used for analysis. Results: A total of 208 patients were identified. The mean age was 59.5 years. 61.53% of patients had symptoms for >12 months at initial consult. Mean time awaiting surgical consult, monitoring symptoms, and awaiting surgery was 77.2, 60.9, and 46.9 days, respectively. Time awaiting surgery (β=-0.032, p=0.04) was a significant factor for change in Physical Component Score. Conclusions: We found time awaiting surgery to be a significant factor on PSC score at 12-month follow-up. Increased time awaiting surgery may result in negative impacts on quality of life outcomes.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".