Correlation of improvements in hemodynamics and exercise capacity in patients with PAH: Results from the phase III PATENT-1 study
Bibliographic record
Abstract
Background Current PAH treatment guidelines recommend that patients (pts) should be evaluated by hemodynamic, clinical, and functional assessments. PATENT-1 investigated riociguat, a novel sGC stimulator, for the treatment of PAH. Aims To determine the effect of riociguat on hemodynamic parameters in pts with PAH, and how this correlates with exercise capacity. Methods In this randomized, double-blind study, pts received placebo (pbo), an individual titration of riociguat (up to 2.5 mg tid), or a capped titration of riociguat (up to 1.5 mg tid). Results 126 pts received pbo, 254 an individually titrated dose of riociguat, and 63 a capped titration of riociguat. At Wk 12, pbo-corrected differences in the riociguat individual dose titration arm were: a reduction in PVR of 226 dyn·s·cm -5 (95% CI −281 to −170; p<0.001); a reduction in mean pulmonary arterial pressure of 4 mmHg (95% CI −6 to −2; p<0.001); a reduction in right atrial pressure of 1 mmHg (95% CI −2 to 0; p=0.07); and an increase in cardiac index of 0.6 L/min/m 2 (95% CI 0.4 to 0.7; p<0.001). Riociguat significantly improved 6-min walking distance (6MWD), with a pbo-corrected increase of 36 m (95% CI 20 to 52; p<0.001). Improvement in 6MWD showed a significant but weak correlation with improvement in PVR (r=−0.21; p<0.001) and cardiac index (r=0.16; p=0.002). Conclusions Improvements in exercise capacity and hemodynamics underline the efficacy of riociguat in the investigated PAH cohort. The significant but small correlation between change in 6MWD and change in hemodynamics shows that assessment of several parameters is necessary to evaluate the overall treatment effect in the individual PAH patient.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".