Efficacy of Electroconvulsive Therapy for the Treatment of Movement Disorders: A Literature Review
Bibliographic record
Abstract
Electroconvulsive therapy (ECT) is a safe and effective treatment modality for various psychiatric disorders. However, evidence suggests a putative role of ECT in treating movement disorders that are refractory to less invasive modalities. ECT is primarily used in treatment-resistant psychiatric disorders. However, growing evidence exists for its use in movement disorders with and without psychiatric comorbidity. The primary objective of this systematic review was to examine the efficacy of ECT as a primary treatment modality for movement disorders. Relevant, peer-reviewed publications were retrieved from PubMed, SCOPUS, CINAHL, and PsycINFO. Keywords related to ECT and movement disorders were used as search phrases to identify relevant articles. A total of 90 articles that met the inclusion criteria were included in this review. Core findings were subsequently appraised on the role of ECT in treating movement disorders. Inclusion and exclusion criteria were developed to guide the search and selection process. Sources that met the inclusion criteria were those published between 2001 and January 2023. Additionally, peer-reviewed journals published in the English language covering the role of ECT in movement disorders were deemed appropriate for inclusion. Sources published before 2001, written in a non-English language, and not from peer-reviewed journals were excluded from this systematic review. The exclusion criteria also entailed eliminating duplicates from the review list. Most reviewed sources revealed that ECT improved outcomes in symptoms associated with various movement symptoms. However, ECT does not have a long-lasting impact on neuroacanthocytosis symptoms. Additionally, ECT is negatively associated with aggression and agitation, two of the most critical movement symptoms of Alzheimer's disease. Evidence affirms the efficacy of ECT in providing symptomatic relief for movement disorders aside from psychiatric comorbidities. This positive association highlights the need for randomized controlled studies to identify movement disorder sub-populations that may respond to ECT.
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".