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Record W3098195547 · doi:10.1093/ehjcr/ytaa320

Contemporary use of Selexipag in pulmonary arterial hypertension associated with congenital heart disease: a case series

2020· article· en· W3098195547 on OpenAlexaff
Sarah Blissett, David Blusztein, Vaikom S. Mahadevan

Bibliographic record

VenueEuropean Heart Journal - Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineProstacyclinCardiologyInternal medicineContext (archaeology)Pulmonary hypertension

Abstract

fetched live from OpenAlex

BACKGROUND: There are significant risks of parenteral prostacyclin use in patients with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD), which may limit their use. Selexipag is an oral, selective prostacyclin analogue that has been shown to reduce disease progression and improve exercise capacity in patients with PAH-CHD. Administering Selexipag in patients with PAH-CHD could potentially overcome some of the risks of parenteral therapy while improving clinical outcomes. CASE SUMMARY: We report five cases highlighting the clinical uses of Selexipag in patients with PAH-CHD. In the first two cases, Selexipag was initiated as part of a Treat-to-close strategy. In the third case, initiation of Selexipag improved symptoms and objective exercise capacity in a patient with Eisenmenger syndrome. In the fourth and fifth cases, rapid cross-titration protocols were used to transition from parenteral prostacyclins to Selexipag. In the fourth case, Selexipag was initiated in the context of significant side effects limiting parenteral prostacyclin use. In the fifth case, Selexipag was used to down-titrate from parenteral prostacyclins following closure of a sinus venosus atrial septal defect and redirection of anomalous pulmonary veins. DISCUSSION: Selexipag is a promising oral therapy for patients with at various stages of the spectrum of PAH-CHD to improve symptoms, exercise capacity and, in some cases, haemodynamics. Our cases also highlight practical aspects of Selexipag use including targeting the individualized maximally tolerated dose for each patient, managing side effects and managing dose interruptions.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.105
GPT teacher head0.294
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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