Satisfaction in surgically treated patients with degenerative cervical myelopathy: an observational study from the Canadian Spine Outcomes and Research Network
Bibliographic record
Abstract
BACKGROUND CONTEXT: Healthcare reimbursement is evolving towards a value-based model, entwined and emphasizing patient satisfaction. Factors associated with satisfaction after degenerative cervical myelopathy (DCM) surgery have not been previously established. PURPOSE: Our primary objective was to ascertain satisfaction rates and satisfaction predictors at 3 and 12 months following surgical treatment for DCM. DESIGN: This is a prospective cohort study within Canadian Spine Outcomes and Research Network (CSORN). PATIENT SAMPLE: Patients in the study were surgically treated for DCM patients who completed 3-month and 12-month follow-ups within CSORN between 2015 and 2021. OUTCOME MEASURES: Data analyzed included patient demographic, surgical variables, patient-reported outcomes (NDI, NRS-NP, NRS-AP, SF-12-MCS, SF-12-PCS, ED-5Q, PHQ-8), MJOA and self-reported satisfaction on a Likert scale. METHODS: Multivariable regression analysis was conducted to identify significant factors associated with satisfaction, address multicollinearity and ensure predictive accuracy. This process was conducted separately for the 3-month and 12-month follow-ups. RESULTS: Six hundred and sixty-three patients were included, with an average age of 60, and an even distribution across MJOA scores (mild, moderate, severe). At 3-month and 12-month follow-up, satisfaction rates were 86% and 82%, respectively. At 12 months, logistic regression showed the odds of being satisfied varied by +24%, -3%, -10%, -14%, +3%, and +12% for each 1-point change between baseline and 12 months in MJOA, NDI, NRS-NP, NRS-AP, SF-12-MCS, SF-12-PCS. Satisfaction increased 11-fold for each 0.1-point increased in ED-5Q from baseline to 12 months. At baseline, for every 1-point increase in SF-12-MCS, the odds of being satisfied increased by 7%. At 3 months, all PROs (except for NRS-AP change and baseline SF-12-MCS) predicted satisfaction. All logistic regression analyses demonstrated excellent predictive accuracy, with the highest 12-month AUC of 0.86 (95%CI=0.81-0.90). No patient demographic or surgical factors influenced satisfaction. CONCLUSIONS: Improvement in Patient Reported Outcomes and MJOA are strongly associated with patient satisfaction after surgery for DCM. The only baseline PRO associated with 12-months satisfaction was SF-12-MCS. No modifiable patient baseline characteristic or surgical variables were associated with satisfaction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.001 | 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".