Prevalence of Neck Pain in Patients with Degenerative Cervical Myelopathy and Short-Term Response After Operative Treatment: A Cohort Study of 664 Patients From 26 Global Sites
Bibliographic record
Abstract
Study Design Ambispective cohort study. Objectives 1) To define the prevalence of neck pain in patients with degenerative cervical myelopathy (DCM). 2) To identify associated factors of preoperative neck pain in patients with DCM. 3) To assess the neck pain response to surgical intervention. Methods 757 patients with DCM were enrolled at 26 global sites from 2005 to 2011. A total of 664 patients had complete neck pain scores preoperatively (Neck Disability Index, NDI). The prevalence and severity of neck pain preoperatively and at the 6-months follow-up was summarized. Functional assessments of individuals with and without pain were compared. Associations of preoperative neck pain and related factors were evaluated. Results Preoperatively, 79.2% of patients reported neck pain while 20.8% had no neck pain. Of individuals with neck pain, 20.2% rated their pain as very mild, 27.9% as moderate, 19.6% as fairly severe, 9.6% as very severe and 1.9% as the worst imaginable. Functional status (mJOA), number of stenotic levels, age, and duration of symptoms did not significantly differ in patients with and without pain. Factors associated with the presence of neck pain were female gender, BMI ≥27 kg/m 2 , rheumatologic and gastrointestinal comorbidities, and age <57 years. Neck pain improved significantly from the preoperative examination to the 6-months postoperative follow-up ( P < .0001). Conclusion Here, we demonstrate a high prevalence of neck pain in patients with DCM as well as a link between gender, body weight, comorbidity and age. We highlight a significant reduction in neck pain 6 months after surgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".