Axial Postural Abnormalities in Parkinsonism: Gaps in Predictors, Pathophysiology, and Management
Bibliographic record
Abstract
Axial postural abnormalities are common and disabling motor complications of Parkinson's disease (PD) and parkinsonism. They consist of abnormal trunk or neck postures in the upright position, often interfering with daily life activities.1-5 A high number of patients with PD may develop one or more axial postural abnormalities, which may begin as minor forms, almost universal in persons with parkinsonism (eg, minor flexed posture of the trunk and lower limbs), and progress to severe forms such as camptocormia, antecollis, or Pisa syndrome in over 20% of patients,1 although the definitions of severe axial postural abnormalities were purely based on subjective/expert opinion. Drug-induced parkinsonism or progressive supranuclear palsy may also present axial postural abnormalities, and in multiple system atrophy these symptoms are more frequent than in PD and occur earlier in the disease course.2, 6 Because axial postural abnormalities are associated with an increased risk of falling, pain, and diminished quality of life, their proper prevention and management is warranted.2, 4, 5, 7, 8 However, to date, recommendations for multidisciplinary management and prevention remain an unmet need.3 Diagnosis is typically based on a simple clinical examination, whereas treatments (eg, pharmacological, physical therapy, and surgical treatments) have been evaluated only in small single-center studies that failed to show consistent, long-lasting improvement.2, 5, 8-10 The absence of reliable protocols for the assessment, treatment, and prevention of axial postural abnormalities in parkinsonism is probably due to the largely obscure pathophysiology and uncertainty about prognostic factors needed to estimate beneficial responses to therapy (eg, duration of axial postural abnormalities).2, 5, 8, 11-13 The aim of this viewpoint is to critically analyze the literature on axial postural abnormalities, identify the current issues and gaps, and formulate proposals for current clinical management and future research exploration.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".