Pulmonary Arterial Hypertension-Related Morbidity Is Prognostic for Mortality
Bibliographic record
Abstract
BACKGROUND: Registry data suggest that disease progression in pulmonary arterial hypertension (PAH) is indicative of poor prognosis. However, the prognostic relevance of PAH-related morbidity has not been formally evaluated in randomized controlled trials. OBJECTIVES: The purpose of these analyses was to assess the impact of morbidity events on the risk of subsequent mortality using the landmark method and data from the SERAPHIN and GRIPHON studies. METHODS: For each study, the risk of all-cause death up to the end of the study was assessed from the landmark time point (months 3, 6, and 12) according to whether a patient had experienced a primary endpoint morbidity event before the landmark. Each analysis was conducted using data from all patients who were available for survival follow-up at the landmark. RESULTS: In the SERAPHIN study, on the basis of the 3-month landmark time point, patients who experienced a morbidity event before month 3 had an increased risk of death compared with patients who did not (hazard ratio [HR]: 3.39; 95% confidence interval [CI]: 1.94 to 5.92). In the GRIPHON study, on the basis of the 3-month landmark time point, there was also an increased risk with a HR of 4.48; (95% CI: 2.98 to 6.73). Analyses based on 6-month and 12-month landmarks also showed increased risk in patients who experienced morbidity events, albeit with a reduced HR. CONCLUSIONS: These results demonstrate the prognostic relevance of PAH-related morbidity as defined in the SERAPHIN and GRIPHON studies, highlighting the importance of preventing disease progression in patients with PAH and supporting the clinical relevance of SERAPHIN and GRIPHON morbidity events. (Study of Macitentan [ACT-064992] on Morbidity and Mortality in Patients With Symptomatic Pulmonary Arterial Hypertension [SERAPHIN]; NCT00660179; Selexipag [ACT-293987] in Pulmonary Arterial Hypertension [GRIPHON]; NCT01106014).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".