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Record W7073711975

Optimizing endothelin receptor antagonist use in the management of pulmonary arterial hypertension

2008· article· en· W7073711975 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed Central · 2008
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsnot available
Fundersnot available
KeywordsEndothelin receptorEndothelin receptor antagonistReceptor antagonistClinical trialPulmonary hypertensionAmbrisentanRandomized controlled trialAntagonist
DOInot available

Abstract

fetched live from OpenAlex

Endothelin receptor antagonism has emerged as an important therapeutic approach in pulmonary arterial hypertension (PAH). Bench to bedside scientific research has shown that endothelin-1 (ET-1) is overexpressed in several forms of pulmonary vascular disease and may play an important pathogenetic role in the development and progression of PAH. Oral endothelin receptor antagonists (ERAs) improved exercise capacity, functional status, pulmonary hemodymanics, and delayed the time to clinical worsening in several randomized placebo-controlled trials. Two ERAs are currently approved by the US Food and Drug Administration: bosentan, a dual ERA for patients with class III and IV PAH, and ambrisentan, a selective ERA for patients with class II and III PAH. Sitaxsentan, another selective ERA, has been approved in Europe, Canada, and Australia. The objective of this review is to evaluate the available evidence describing the pharmacology, efficacy, safety, and tolerability, and patient-focused perspectives regarding the different types of endothelin receptor antagonists. Ongoing and forthcoming randomized trials are also highlighted including the approach of combining this class of drugs with other drugs that target different cellular pathways believed to be etiologically important in PAH.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.180
Teacher spread0.158 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2008
Admission routes1
Has abstractyes

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