Preoperative expectations of patients with degenerative cervical myelopathy: an observational study from the Canadian Spine Outcomes and Research Network
Bibliographic record
Abstract
BACKGROUND: Despite an abundance of literature on degenerative cervical myelopathy (DCM), little is known about preoperative expectations of these patients. PURPOSE: The primary objective was to describe patient preoperative expectations. Secondary objectives included identifying patient characteristics associated with high preoperative expectations and to determine if expectations varied depending on myelopathy severity. STUDY DESIGN: This was a retrospective study of a prospective multicenter, observational cohort of patients with DCM. PATIENT SAMPLE: Patients who consented to undergo surgical treatment between January 2019 and September 2022 were included. OUTCOMES MEASURES: An 11-domain expectation questionnaire was completed preoperatively whereby patients quantified the expected change in each domain. METHODS: The most important expected change was captured. A standardized expectation score was calculated as the sum of each expectation divided by the maximal possible score. The high expectation group was defined by patients who had an expectation score above the 75th percentile. Predictors of patients with high expectations were determined using multivariable logistic regression models. RESULTS: There were 262 patients included. The most important patient expectation was preventing neurological worsening (40.8%) followed by improving balance when standing or walking (14.5%), improving independence in everyday activities (10.3%), and relieving arm tingling, burning and numbness (10%). Patients with mild myelopathy were more likely to select no worsening as the most important expected change compared to patients with severe myelopathy (p<.01). Predictors of high patient expectations were: having fewer comorbidities (OR -0.30 for every added comorbidity, 95% CI -0.59 to -0.10, p=.01), a shorter duration of symptoms (OR 0.92, 95% CI 0.35-1.19, p=.02), no contribution from "failure of other treatments" on the decision to undergo surgery (OR 1.49, 95% CI 0.56-2.71, p=.02) and more severe neck pain (OR 0.19 for 1 point increase, 95% CI 0.05-0.37, p=.01). CONCLUSIONS: Most patients undergoing surgery for DCM expect prevention of neurological decline, better functional status, and improvement in their myelopathic symptoms. Stopping neurological deterioration is the most important expected outcomes by patients.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".