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Contemporary Treatment Strategies in Pulmonary Hypertension: A Clinician's Guide

2025· review· en· W4415374221 on OpenAlexaff
Brandon Budhram, Samuel Chung, Marc Humbert, Evelyn M. Horn

Bibliographic record

VenueAnnual Review of Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPulmonary hypertensionMEDLINEPulmonary diseaseRespiratory diseasePulmonary medicine

Abstract

fetched live from OpenAlex

Pulmonary hypertension (PH) is a complex condition characterized by pulmonary vasculopathy and progressive right ventricular dysfunction. Recent advances have reshaped PH management, including refined risk stratification, improved patient phenotyping, and the discovery of novel therapeutics. In alignment with the recommendations of the Seventh World Symposium on Pulmonary Hypertension, we summarize updated treatment strategies and emerging therapies, such as sotatercept, while acknowledging research gaps and areas of clinical equipoise. This practical, evidence-based review explores treatment across all groups of PH to inform clinical decision-making, improve long-term patient outcomes, and address both current and future challenges in PH management.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.003
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.001
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0140.010

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 head0.110
GPT teacher head0.446
Teacher spread0.336 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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