Initial combination therapy with macitentan and tadalafil in pulmonary arterial hypertension: a retrospective cohort study
Bibliographic record
Abstract
Abstract Purpose: Initial combination therapy with ambrisentan and tadalafil has been demonstrated superior to either agent alone in pulmonary arterial hypertension (PAH). More recently, the OPTIMA trial showed efficacy of another combination of endothelin receptor antagonist and phosphodiesterase 5-inhibitor, macitentan and tadalafil, as initial therapy for PAH. The objective of this study was to assess the effectiveness, tolerability, and safety of macitentan and tadalafil in a real-world clinical setting.Methods: This single centre, retrospective cohort study identified adult patients newly diagnosed with PAH between January 2014 and December 2017 who were started on macitentan and tadalafil. Patients were retrospectively followed for one year. Effectiveness was evaluated via change from baseline in disease risk profile based on a validated score incorporating World Health Organization functional class, 6-minute walk distance (6MWD), B-type natriuretic peptide (BNP), and hemodynamics on follow-up right heart catheterization. Secondary endpoints included change in 6MWD, BNP, and hemodynamic variables. Drug tolerability and adverse events were assessed.Results: The cohort included 46 patients, 8 of whom (17%) did not tolerate and discontinued either macitentan or tadalafil. Median time to follow-up was 161 days (IQR 72). 42% of patients with an initially moderate or high risk disease profile improved to low risk. Secondary endpoints showed a reduction in the geometric mean of pulmonary vascular resistance of 45% (95% CI 29, 57%) and improvement in 6MWD of 88m (95% CI 27, 148m).Conclusion: In a real-world setting, macitentan and tadalafil as initial combination therapy for PAH was well tolerated and yielded clinical benefit.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".