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Record W4412047533 · doi:10.1080/17582024.2025.2528557

Recent and on-going trials for the treatment of levodopa-induced dyskinesia: a review of the clinical trial databases

2025· review· en· W4412047533 on OpenAlex
Jawad Al‐Kassmy, Mohammed Alsalmi, Woojin Kang, Michael Palayew, Philippe Huot

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeurodegenerative Disease Management · 2025
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMcGill University Health CentreMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsDyskinesiaClinical trialLevodopaMedicineDatabaseComputer scienceParkinson's diseaseDiseaseInternal medicine

Abstract

fetched live from OpenAlex

L-3,4-dihydroxyphenylalanine (Levodopa)-induced dyskinesia remains a condition for which there are few therapeutic options available. Fortunately, the past 5 years have seen the completion of several clinical trials, some of which yielded positive and encouraging results. Here, we performed a review of the clinical trials that were completed or for which outcomes were disclosed within the past 5 years. Promising results were obtained in Phase II trials with the serotonin type 1A (5-HT1A) agonist befiradol, the dopamine D3 receptor antagonist mesdopetam and the phosphodiesterase inhibitor CPL500036. In contrast, the metabotropic glutamate 4 (mGlu4) receptor negative allosteric modulator foliglurax and JM-010 (a combination of the 5-HT1A partial agonist buspirone and the and the 5-HT type 1B and 1D [5-HT1B/1D] agonist zolmitriptan) did not meet their endpoints in Phase II studies. Lastly, robot-assisted Repetitive Transcranial Magnetic Stimulation (rTMS) of the pre-supplementary motor area may be a promising non-pharmacological approach to alleviate dyskinesia.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.373
GPT teacher head0.487
Teacher spread0.114 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it