The treatment of dystonic tremor: a systematic review
Bibliographic record
Abstract
Tremor is one of the clinical manifestations of dystonia; however, there are no specific therapeutic trials evaluating the efficacy of treatments for dystonic tremor (DT), tremor associated with dystonia or primary writing tremor (PWT). We systematically reviewed the literature available up to July 2013 on the treatment of these tremors and retrieved the data of 487 patients published in 43 papers detailing the effects of given interventions on tremor severity. Treatment outcome was highly variable, depending on the specific type of intervention and tremor distribution. No specifically designed studies were available for the treatment of tremor associated with dystonia. As for the other tremors, drug efficacy was generally disappointing and a moderate effect was only found with anticholinergics, tetrabenazine, clonazepam, β-blockers and primidone; levodopa was only efficacious on tremor due to dopa-responsive dystonia. The largest amount of data was available for botulinum toxin injections, which provided a marked improvement, particularly for the management of axial tremors (head or vocal cords). In refractory DTs, deep brain stimulation of several targets was attempted. Deep brain stimulation of globus pallidus internus, thalamus or subthalamic area led to a marked improvement of dystonic axial or appendicular tremors in most cases refractory to other treatments. Few other non-invasive treatments, for example, orthotic device in PWT, have been used with anecdotal success. In conclusion, considering the lack of good-quality studies, future randomised controlled trials are needed. In absence of evidence-based guidelines, we propose an algorithm for the treatment of DT based on currently available data.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".