Medication adherence and clinical outcome in patients with pulmonary arterial hypertension or distal chronic thromboembolic pulmonary hypertension
Bibliographic record
Abstract
INTRODUCTION: In pulmonary arterial hypertension (PAH) and distal chronic thromboembolic pulmonary hypertension (CTEPH), the consistent use of disease-specific therapies is crucial. We aimed to investigate medication adherence to oral disease-specific medication and the impact on clinical outcome among patients with PAH or CTEPH to identify potential patient-related reasons for treatment incompliance. STUDY DESIGN AND METHODS: This prospective study focused on medication adherence using a multimeasure approach, including specialty pharmacy order data to calculate medication possession ratio (MPR) and self-reporting via questionnaire among patients with PAH or CTEPH. Adherence rates of ≥80% were considered adherent. Simplified four-strata risk categories according to the 2022 European Respiratory Society/European Society of Cardiology pulmonary hypertension (PH) guidelines were determined. RESULTS: We included 93 patients (66% women, 75% PAH, 25% CTEPH, 57±17 years), all on PH-targeted oral medication between 2013 and 2023. Overall, a number of 73 patients (78%) were classified as adherent. The mean MPR was 98±19% and the mean value of questionnaire responses was 89±10%. At the end of the observation period, adherent patients improved their risk category, while non-adherent patients did not. Factors associated with adherence were older age (OR=1.03, 95% CI=1.01 to 1.07) and being classified in a higher risk category (OR=2.13; 95% CI=1.11 to 4.64). Patients with adverse drug reactions were 75% more likely to be non-adherent to medication (OR=0.25; 95% CI=0.08 to 0.77). CONCLUSION: In this collective, mean MPR and self-reported adherence were overall high, with 78% of patients classified as adherent. Adherent patients improved clinical outcomes contrary to non-adherent patients. Insufficient adherence and potential contributing factors should be regularly considered, especially in patients without improvement after starting disease-specific therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".