A Roadmap for Therapeutic Discovery in Pulmonary Hypertension Associated with Left Heart Failure. A Scientific Statement of the Heart Failure Association (HFA) of the ESC and the ESC Working Group on Pulmonary Circulation & Right Ventricular Function
Bibliographic record
Abstract
Pulmonary hypertension (PH) associated with left heart failure (LHF) (PH-LHF) is one of the most common causes of PH. It directly contributes to symptoms and reduced functional capacity and negatively affects right heart function, ultimately leading to a poor prognosis. There are no specific treatments for PH-LHF, despite the high number of drugs tested so far. This scientific document addresses the main knowledge gaps in PH-LHF with emphasis on pathophysiology and clinical trials. Key identified issues include better understanding of the role of pulmonary venous versus arteriolar remodelling, multidimensional phenotyping to recognize patient subgroups positioned to respond to different therapies, and conduct of rigorous pre-clinical studies combining small and large animal models. Advancements in these areas are expected to better inform the design of clinical trials and extend treatment options beyond those effective in pulmonary arterial hypertension. Enrichment strategies, endpoint assessments, and thorough haemodynamic studies, both at rest and during exercise, are proposed to play primary roles to optimize early-stage development of candidate therapies for PH-LHF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".