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Basic and clinical pharmacology of new motility promoting agents

2005· review· en· W1990407890 on OpenAlexaff
James J. Galligan, Stephen Vanner

Bibliographic record

VenueNeurogastroenterology & Motility · 2005
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsGastric emptyingMedicineTegaserodGastroparesisIrritable bowel syndromePharmacologyDrugMetoclopramideInternal medicineStomachVomiting

Abstract

fetched live from OpenAlex

Recent research has provided new information about drugs that could be used to treat functional motility disorders. Promotility drugs accelerate gastric emptying or colonic transit and these properties may contribute to their efficacy in treating symptoms associated with gastroparesis, functional dyspepsia or constipation. 5-Hydroxytryptamine4 receptors are targets for drugs (tegaserod, renzapride) that treat symptoms in constipated irritable bowel syndrome patients and in gastroparesis. Drugs acting at motilin (erythromycin) and cholecystokinin-1 (dexloxiglumide) receptors accelerate gastric emptying. Dexloxiglumide might be useful in the treatment of functional dyspepsia particularly that associated with lipid intake. Alvimopan is a mu-opioid receptor antagonist that does not cross the blood brain barrier. Alvimopan is effective in treating postsurgical ileus and perhaps opiate-induced bowel dysfunction. Successes and failures of recent efforts to develop promotility agents revealed opportunities and challenges for developing new promotility drugs. The pharmacological properties of partial agonists might be exploited to develop effective promotility drugs. However, opposing actions of promotility agents on motility (increased contraction vs decreased accommodation) limit the clinical efficacy of drugs with these opposing actions. Selection of appropriate patient populations for evaluation of new drugs is also critical.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.677
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
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 head0.119
GPT teacher head0.434
Teacher spread0.314 · 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 designObservational
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

Citations131
Published2005
Admission routes1
Has abstractyes

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