Longterm Survival Among Patients with Scleroderma-associated Pulmonary Arterial Hypertension Treated with Intravenous Epoprostenol
Bibliographic record
Abstract
OBJECTIVE: Pulmonary arterial hypertension (PAH) remains challenging to treat, especially in association with scleroderma. We examined survival rates among patients with PAH in association with scleroderma who received epoprostenol (Flolan) through continuous intravenous (i.v.) infusion in an uncontrolled open-label 3-year extension study following an initial randomized, controlled 12-week study. METHODS: One hundred two patients diagnosed with PAH in association with scleroderma who received epoprostenol were included in the analyses. This included 51 PAH patients from a subject population of 56 who received epoprostenol in the randomized controlled study, and 46 patients from an initial population of 55 subjects on conventional therapy in the randomized controlled study, who received epoprostenol in the extension study. All patients in this extension study received open-label epoprostenol. Adverse events, survival, and dosing information were collected throughout the study. RESULTS: The probabilities of survival during the first and second years for all subjects who received epoprostenol during the initial randomized controlled study or during the extension study were 0.71 and 0.52, respectively. This measure remained constant at 0.48 during the third and fourth years. CONCLUSION: This study reports longterm survival rates for patients with scleroderma-associated PAH treated with i.v. epoprostenol. Although comparisons to historical data should be made with caution, this study reports a better survival outcome than natural history data on patients with scleroderma-associated 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".