Analysis of Influencing Factors for Chronic Neck Pain with Cognitive Impairment
Bibliographic record
Abstract
Background: Cervical spondylosis is a common chronic degenerative musculoskeletal disorder. It is based on the degeneration of the cervical intervertebral discs and secondary pathological changes, affecting the surrounding soft tissues, nerve roots, vertebral arteries, sympathetic nerves, and spinal cord. This condition gives rise to a series of clinical symptoms and signs. Pain represents one of the most crucial manifestations. Notably, when pain symptoms endure for over three months, this may give rise to chronic neck pain (CNP). The progression of this chronic neck pain may increase the risk of cognitive impairment (CI). However, to date, predictive markers for chronic neck pain with cognitive impairment (CNP-CI) remain lacking. Previous investigations have demonstrated that routine blood parameters possess predictive utility for Alzheimer's disease. However, the association between these parameters and chronic neck pain with CNP - CI remains elusive. This study was designed to explore the correlations among routine blood indices and to provide evidence regarding the differences between two groups of patients with chronic neck pain, namely those with and without cognitive impairment. Additionally, this study aims to lay the groundwork for longitudinal experimental investigations into effective intervention strategies for patients with chronic neck pain who develop cognitive impairment. Methods: This cross-sectional study was conducted in West China Hospital, Sichuan University. Montreal Cognitive Assessment (MoCA) was conducted to divide patients into the CNP-CI or CNP-nCI group. Statistical analysis was performed to examine the differences between chronic neck pain patients with cognitive impairment and those without cognitive impairment. All statistical tests were conducted at a significant level of α=0.05 for two-sided testing. Results: The prevalence of chronic neck pain with cognitive impairment in this study demonstrates age-related disparities, with a higher prevalence observed among older individuals (P=0.007). A statistically significant difference in serum calcium was observed between individuals with chronic neck pain and cognitive impairment (P=0.046). Conclusion: The age and serum calcium may serve as influential factors in the development of chronic neck pain with cognitive impairment. This finding can aid healthcare professionals in implementing early intervention and treatment for individuals experiencing this condition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".