MétaCan
Menu
Back to cohort
Record W4225320873 · doi:10.1161/circresaha.121.319971

The Latest in Animal Models of Pulmonary Hypertension and Right Ventricular Failure

2022· review· en· W4225320873 on OpenAlexaff
Olivier Boucherat, Vineet Agrawal, Allan Lawrie, Sébastien Bonnet

Bibliographic record

VenueCirculation Research · 2022
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsInstitute of Infection and ImmunityUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersNational Heart, Lung, and Blood InstituteBritish Heart FoundationU.S. Department of Veterans Affairs
KeywordsPulmonary hypertensionRight ventricular failureCardiologyHeart failureInternal medicineMedicineAnimal modelRight ventricular hypertrophy

Abstract

fetched live from OpenAlex

Pulmonary hypertension (PH) describes heterogeneous population of patients with a mean pulmonary arterial pressure >20 mm Hg. Rarely, PH presents as a primary disorder but is more commonly part of a complex phenotype associated with comorbidities. Regardless of the cause, PH reduces life expectancy and impacts quality of life. The current clinical classification divides PH into 1 of 5 diagnostic groups to assign treatment. There are currently no pharmacological cures for any form of PH. Animal models are essential to help decipher the molecular mechanisms underlying the disease, to assign genotype-phenotype relationships to help identify new therapeutic targets, and for clinical translation to assess the mechanism of action and putative efficacy of new therapies. However, limitations inherent of all animal models of disease limit the ability of any single model to fully recapitulate complex human disease. Within the PH community, we are often critical of animal models due to the perceived low success upon clinical translation of new drugs. In this review, we describe the characteristics, advantages, and disadvantages of existing animal models developed to gain insight into the molecular and pathological mechanisms and test new therapeutics, focusing on adult forms of PH from groups 1 to 3. We also discuss areas of improvement for animal models with approaches combining several hits to better reflect the clinical situation and elevate their translational value.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.180
GPT teacher head0.396
Teacher spread0.215 · 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 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

Citations176
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCirculation ResearchSame topicPulmonary Hypertension Research and TreatmentsFrench-language works237,207