Chiropractic care of Parkinson’s disease and deformity
Bibliographic record
Abstract
Parkinson's disease (PD) is a progressive neurological disease characterized by muscle stiffness, tremor, slowness of movement, and difficulties with posture and walking. Muscle and joint pain are frequent non-motor symptoms of PD. Pain associated with PD is mainly caused by a combination of truncal dystonia, stooped posture, and muscle rigidity. However, PD deformities were rarely discussed in the literature. A 68-year-old Asian female with PD treated with Levodopa for six years complained of progressive neck pain, contractures, and subluxation of both hands in the last two years. A positron emission tomography (PET) scan revealed decreased rostrocaudal gradient uptake in both posterior putamen. After 9 months of multimodal chiropractic rehabilitation, the patient had significant improvement in symptoms, including pain resolution as per the numeric rating scale and physical and mental improvement as per the PD questionnaire. Radiographic measurement showed significantly improved postural alignment and stability. Measurement of joint motion and angles showed an improvement in hand deformity. Although PD is a neurodegenerative disease that is not curable, multimodal rehabilitation may improve neurological and musculoskeletal functions by inducing proprioceptive balance, motor strength, and joint movement. The current study may illustrate multimodal rehabilitation addressing orthopedic deformity associated with symptoms in a PD patient.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".