Dystonia: A Leading Neurological Movement Disorder
Bibliographic record
Abstract
Dystonia is the third leading movement disorder arising mainly from the damage of basal ganglia or other parts of the brain that control movements. The objective of this review is to represent the detailed profile of dystonia. A computerized literature review was conducted in authentic scientific databases including PubMed, Google Scholar, Scopus, Science Direct and National Institutes of Health (NIH) etc. Terms searched included dystonia, risk factors, etiologies, clinical features, classification, pathology, guidelines, treatment strategies, primary and secondary dystonia. Initially, 97 articles and 9 books were extracted but finally, 64 articles and 7 books were used. After analysis, we found that causes of dystonia could be acquired or inherited and dystonia can be classified based on age at onset, etiology, and distribution of the affected body parts. The risk factors of this heterogeneous disorder could be trauma, thyroid disorder, hypertension, life habits, occupation, use of drugs and genetics. A significant number of articles were found which signify the ability of brainstem and cerebellar pathology to trigger the symptoms of dystonia. Since antipsychotic drugs are the most commonly prescribed among the people with intellectual disability (ID), therefore they possess a greater risk to experience antipsychotic drugs-induced movement side effects including acute dystonia, parkinsonism, tardive dyskinesia, and akathisia. Depending on various manifestations and causes, there are several treatment options including oral medications, intramuscular injection of botulinum toxin, neurosurgical procedures and occupational therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".