Comparison of hemodynamic parameters in treatment-naïve and pre-treated patients with pulmonary arterial hypertension in the randomized phase III PATENT-1 study
Bibliographic record
Abstract
BACKGROUND: Detailed hemodynamic data from the phase III PATENT-1 study of riociguat in patients with pulmonary arterial hypertension (PAH) were investigated. METHODS: Patients with PAH who were treatment naïve or pre-treated with endothelin receptor antagonists or non-intravenous prostanoids were randomly assigned to riociguat up to 2.5 mg 3 times a day or placebo. Hemodynamic parameters were assessed at baseline and week 12. RESULTS: [95% CI -252 to -120; p < 0.0001]) patients and significantly increased cardiac index (LS mean difference +0.7 [95% CI 0.5 to 0.8] and +0.5 [95% CI 0.3 to 0.7], respectively [both p < 0.0001]). Mean pulmonary artery pressure (p = 0.0056 and p = 0.0019 for treatment-naïve and pre-treated patients, respectively), mean arterial pressure (both p < 0.0001), and systemic vascular resistance (both p < 0.0001) were significantly reduced, and there was an increase in mixed venous oxygen saturation (p < 0.0001 and p = 0.0004, respectively). Results were similar in patients pre-treated with endothelin receptor antagonists and patients pre-treated with non-intravenous prostanoids. Improvements in 6-minute walking distance correlated very weakly with improvements in pulmonary vascular resistance (r = -0.21 [95% CI -0.30 to -0.11; p < 0.0001]) and cardiac index (r = 0.16 [95% CI 0.06 to 0.25; p < 0.0016]). CONCLUSIONS: Riociguat significantly improved hemodynamic parameters in pre-treated and treatment-naïve 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".