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Record W4211224198 · doi:10.1016/j.healun.2022.02.002

Oral anticoagulants (NOAC and VKA) in chronic thromboembolic pulmonary hypertension

2022· article· en· W4211224198 on OpenAlexaff
Marc Humbert, Gérald Simonneau, David Pittrow, Marion Delcroix, Joanna Pepke‐Żaba, David Langleben, Lisa Mielniczuk, Pilar Escribano Subías, Repke J. Snijder, Joan Albert Barberà, Jens Klotsche, Christian Meier, Marius M. Hoeper

Bibliographic record

VenueThe Journal of Heart and Lung Transplantation · 2022
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of OttawaWilfrid Laurier UniversityMcGill UniversityJewish General Hospital
FundersBayer
KeywordsMedicineChronic thromboembolic pulmonary hypertensionVitamin K antagonistInternal medicineAdverse effectRiociguatCohortProspective cohort studyPulmonary embolismAtrial fibrillationWarfarin

Abstract

fetched live from OpenAlex

EXPERT was an international, multicenter, prospective, uncontrolled, non-interventional cohort study in patients with pulmonary hypertension treated with riociguat. Patients were followed for 1-4 years, and the primary outcomes were adverse events (AEs) and serious AEs (SAEs), including embolic/thrombotic and hemorrhagic events. Here we report data on patients with chronic thromboembolic pulmonary hypertension (CTEPH) receiving a vitamin K antagonist (VKA; n = 683) or a non-vitamin K antagonist oral anticoagulant (NOAC; n = 198) at baseline. AEs and SAEs were reported in 438 patients (64.1%) and 257 patients (37.6%), respectively, in the VKA group, and in 135 patients (68.2%) and 74 patients (37.4%) in the NOAC group. Exposure-adjusted hemorrhagic event rates were similar in the two groups, while exposure-adjusted embolic and/or thrombotic event rates were higher in the NOAC group, although the numbers of events were small. Further studies are required to determine the long-term effects of anticoagulation strategies in CTEPH.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.300
Teacher spread0.273 · 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 designObservational
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

Citations66
Published2022
Admission routes1
Has abstractyes

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