MétaCan
Menu
Back to cohort
Record W1966028568 · doi:10.2174/157488908783421500

The Evolution of Pharmacological Treatment for Parkinsons Disease

2008· review· en· W1966028568 on OpenAlexaff
Quincy J. Almeida, H. Christopher Hyson

Bibliographic record

VenueRecent Patents on CNS Drug Discovery · 2008
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsLevodopaNeuroprotectionDopamineMedicinePharmacologyParkinson's diseaseMonoamine oxidaseNeurodegenerationDiseaseDrugNeurosciencePsychologyInternal medicineChemistry

Abstract

fetched live from OpenAlex

Since the introduction of levodopa therapy in the 60's, there has yet to be a more efficacious drug identified for the symptomatic treatment of Parkinson's disease (PD). Perhaps more importantly, there has been little to no success finding agents that have proven effective in protecting against neurodegeneration. In fact, recent development efforts have been primarily directed at stabilizing the side effects (wearing off, drug-induced dyskinesias, motor fluctuations) that accompany prolonged levodopa therapy, such as catechol O-methyltransferase inhibiton to combat the side effects of levodopa therapy. This review also examines alternative strategies to levodopa therapy, including potential adjuncts therapies, recent patents and future directions to be evaluated for neuroprotection. While dopamine agonists are inferior to levodopa in controlling motor symptoms, potential benefits and drawbacks with this class of drugs are presented. Potential neuroprotective agents such as monoamine oxidase-B inhibitors are also examined for their therapeutic benefit as well as their potential to slow disease progression. Neuroprotection will continue to be an important area of research in CNS drug development.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
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 head0.085
GPT teacher head0.359
Teacher spread0.274 · 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 teacher head, not a consensus.

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

Citations10
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueRecent Patents on CNS Drug DiscoverySame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207