Riociguat: a soluble guanylate cyclase stimulator for the treatment of pulmonary hypertension
Bibliographic record
Abstract
Despite advances in treatments and improved survival, patients with pulmonary hypertension still experience poor exercise and functional capacity, which has a significant detrimental impact on their quality of life. The nitric oxide (NO)-soluble guanylate cyclase (sGC)-cyclic guanosine 3',5'-monophosphate (cGMP) pathway has been shown to play an important role in cardiovascular physiology, especially in vasodilation and pulmonary vascular tone. The oral sGC stimulator riociguat has a dual mode of action on the NO-sGC-cGMP pathway: direct stimulation of sGC independent of NO and indirect simulation via sensitization of sGC to endogenous NO. Riociguat is now licensed in >50 countries worldwide, including in Europe, the USA, Canada, and Japan. Approval for the treatment of pulmonary arterial hypertension (PAH) was based on Phase III data from the PATENT studies, in which riociguat significantly improved exercise capacity, pulmonary vascular resistance, a range of secondary end points, and hemodynamic parameters in patients with symptomatic PAH. In the Phase III CHEST studies, riociguat consistently improved exercise capacity in patients with inoperable chronic thromboembolic pulmonary hypertension (CTEPH) or persistent/recurrent CTEPH after pulmonary endarterectomy and is now the only drug to be approved for this indication. Riociguat was well tolerated in long-term studies of PAH and CTEPH. This review describes the role of the NO-sGC-cGMP pathway in the pathophysiology of pulmonary hypertension, and reviews the clinical efficacy and safety of riociguat in patients with PAH and inoperable or persistent/recurrent CTEPH. Based on its demonstrated efficacy and established safety profile, riociguat is a promising treatment option for patients with PAH and CTEPH.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".