Is There Any Relationship between Scoliosis, Cervical Pain and Postural Imbalance in Parkinson’s Disease? A Cross-Sectional, Pilot Study
Bibliographic record
Abstract
Background: Parkinsons’s disease is characterized by progressive worsening of gait, posture and balance with disability in daily life activities and to improvement in chronic musculoskeletal pain, often in neck pain associated with worsening of balance. The aim of the study is to investigate the correlation between scoliosis, balance and cervical pain in Parkinson’s disease. Methods: Cross-sectional, pilot study. A total of 16 Parkinson’s patients were enrolled in the study. The Pain Visual analogue scale and the short form McGill pain questionnaire measured neck cervical pain; static balance, Tinetti, Berg Balance and Short Physical Performance Battery scales(SPPB) were used to evaluate dynamic balance. Whole-spine standard X-ray assess spinal scoliosis with Cobb angles measurement .An observational statistical analysis was performed with the patients subdivided into a non-scoliosis (NS) group and a true scoliosis (TS) group based on whether they presented a Cobb’s angle below or ≥10°. Results: Frequency of neck pain in the NS group was 37% compared to 50% in the TS group. A non-statistically significant difference was found in terms of static, dynamic balance and cervical pain scores between NS and TS groups. Conclusions: Scoliosis, cervical pain and postural imbalance are significant yet often overlooked complaints in PD.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".