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Record W2171854124 · doi:10.1586/ers.12.83

The emergence of new therapeutic targets in pulmonary arterial hypertension: from now to the near future

2013· review· en· W2171854124 on OpenAlexaff
Simon Malenfant, Guillaume Margaillan, Jérémy Loehr, Sébastien Bonnet, Steeve Provencher

Bibliographic record

VenueExpert Review of Respiratory Medicine · 2013
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineVascular resistanceIntensive care medicinePulmonary hypertensionCardiologyDiseasePathophysiologyHemodynamicsPulmonary vasculatureTherapeutic approachInternal medicine

Abstract

fetched live from OpenAlex

Pulmonary arterial hypertension (PAH) is a vascular remodeling disease that pathologically increases pulmonary vascular resistance. Ultimately, this leads to right ventricular failure and premature death. Current therapeutic strategies are mainly designed to induce relaxation of the pulmonary arteries, but are not directly aimed to improve vascular remodeling that characterize PAH. Although these treatments modestly improve patient symptoms, pulmonary hemodynamics and survival, none of them are curative and approximately 15% of patients die within 1 year of medical follow-up despite treatment. Within the last 5 years, tremendous advances in our understanding of the PAH pathophysiology have arisen. These advances have a high potential for the development of better patient care by providing novel therapeutic targets. The goal of this report is to review the current PAH treatments, as well as novel therapies that will pave the future in this devastating disease.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.003

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 head0.087
GPT teacher head0.391
Teacher spread0.304 · 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

Citations15
Published2013
Admission routes1
Has abstractyes

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