Rehabilitation program for traumatic chronic cervical pain associated with unsteadiness: a single case study
Bibliographic record
Abstract
BACKGROUND: Neck problems are often recurring or chronic. After pain, unsteadiness and balance problems are among the most frequent symptoms reported by chronic neck pain (CNP) patients. Altered sensorimotor control of the cervical spine and sensorimotor integration problems affecting postural control have been observed in CNP patients. Very few data are available regarding the post-intervention effects of rehabilitation programs on postural control in CNP. CASE PRESENTATION: This is a case study of a traumatic CNP patient (a 45-year old female) with postural unsteadiness who participated in an 8-week rehabilitation program combining therapeutic exercises with spinal manipulative therapy. Pre-intervention data revealed that the postural control system was challenged when postural control sensory inputs were altered, particularly during the head-extended-backward condition. Post-intervention centre of pressure measurements indicated a drastic reduction in postural sway during trials with changes in neck orientation. CONCLUSION: This case report indicates that an 8-week rehabilitation program combining therapeutic exercises with spinal manipulative therapy may have had an effect on improvement of postural control in a trauma CNP patient with unsteadiness. These results warrant further studies to investigate the relationships between pain amelioration, sensorimotor control of the cervical spine, muscle fitness and postural steadiness.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".