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Record W4368360153 · doi:10.2217/nmt-2022-0039

5-HT <sub>1A</sub> Agonists for levodopa-induced Dyskinesia in Parkinson’s Disease

2023· review· en· W4368360153 on OpenAlexaff
Jawad Al‐Kassmy, Christine Sun, Philippe Huot

Bibliographic record

VenueNeurodegenerative Disease Management · 2023
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsDyskinesiaLevodopaMedicineParkinson's diseaseDiseaseAdverse effectClinical trialPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Levodopa is the most effective agent for treating the symptoms of Parkinson’s disease (PD). However, levodopa-induced dyskinesia remains a significant complication that manifests after few years of treatment, for which therapeutic options remain limited. Several agonists of the serotonin type 1A (5-HT1A) receptor with varying levels of efficacy and interaction at other sites, have been tested in the clinic. Clinical trials testing 5-HT1A agonists have yielded inconsistent results in alleviating dyskinesia, especially that the antidyskinetic benefit observed was often accompanied by an adverse effect on motor function. In this article, we summarize and analyze the various clinical trials performed with 5-HT1A agonists in PD patients with dyskinesia and offer perspectives on the future of this class of agents in PD.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.080
GPT teacher head0.343
Teacher spread0.263 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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