Results of an Expert Consensus Survey on the Treatment of Pulmonary Arterial Hypertension With Oral Prostacyclin Pathway Agents
Bibliographic record
Abstract
BACKGROUND: Treatment of pulmonary arterial hypertension (PAH) has evolved substantially over the past two decades and varies according to etiology, functional class (FC), hemodynamic parameters, and other clinical factors. Current guidelines do not provide definitive recommendations regarding the use of oral prostacyclin pathway agents (PPAs) in PAH. To provide guidance on the use of these agents, an expert panel was convened to develop consensus statements for the initiation of oral PPAs in adults with PAH. METHODS: A systematic literature search was conducted using MEDLINE. The established RAND/University of California Los Angeles appropriateness method, which incorporates the Delphi method and the nominal group technique, was used to create consensus statements. Idiopathic, heritable, repaired congenital heart defect, and drug- or toxin-induced PAH (IPAH+) was considered as one etiologic grouping. The process was focused on the use of oral treprostinil or selexipag in patients with IPAH+ or connective tissue disease-associated PAH and FC II or III symptoms receiving background dual endothelin receptor antagonist/phosphodiesterase type 5 inhibitor therapy. RESULTS: The panel developed 14 consensus statements regarding the appropriate use of oral PPAs in the target population. The panel identified 13 clinical scenarios in which selexipag may be considered as a treatment option. CONCLUSIONS: The paucity of clinical evidence overall, and particularly from randomized trials in this setting, creates a gap in knowledge. These consensus statements are intended to aid physicians in navigating treatment options and using oral PPAs in the most appropriate manner in patients with PAH.
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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 | 0.226 | 0.395 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".