The impact of elective spine surgery in Canada for degenerative conditions on patient reported health-related quality of life outcomes
Bibliographic record
Abstract
The impact of spine surgery on Health-Related Quality-of-Life (HRQoL) outcomes across common spinal degenerative diagnoses is not well characterised. A prospective observational study of patients enrolled in the Canadian Spine Outcomes and Research Network (CSORN) registry was performed. Baseline and 1-year post-operative Short Form-12 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores were collated and compared to normative values from the Canadian General Population (CGP). The percentage of patients achieving the PCS Minimum Clinically Important Difference (MCID) was quantified. 5049 patients were included in the analysis. The mean pre-operative SF-12 PCS was 29.5 and MCS was 44.1. This improved to a mean PCS of 40.5 (p < 0.001) and MCS of 49.3 (p < 0.0001) at 1-year post-operatively. The mean pre-operative PCS was over 2 standard deviations (SD) lower than the normative mean of the CGP; this improved to being close to 1-SD from the normative CGP mean at 1-year post-operatively. Findings were similar across age- and sex-stratified subgroups. Across all conditions, 70-75% of patients achieved the PCS MCID. Fewer patients with cervical myelopathy achieved the PCS MCID (59%). In a surgical cohort, patients with degenerative spinal conditions demonstrate a profound reduction in PCS compared to their peers in the CGP. Spinal surgery was impactful in improving physical function HRQoL outcomes in the majority, but not typically to average population norms.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".