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Record W4392859178 · doi:10.1016/j.shj.2024.100282

Invasive Assessment of Right Ventricular to Pulmonary Artery Coupling Improves 1-year Mortality Prediction After Transcatheter Aortic Valve Replacement and Anticipates the Persistence of Extra-Aortic Valve Cardiac Damage

2024· article· en· W4392859178 on OpenAlexaff
Mark Lachmann, Amelie Hesse, Teresa Trenkwalder, Erion Xhepa, Tobias Rheude, Moritz von Scheidt, Héctor Alfonso Alvarez Covarrubias, Elena Rippen, Oksana Hramiak, Costanza Pellegrini, Tibor Schuster, Shinsuke Yuasa, Heribert Schunkert, Adnan Kastrati, Christian Kupatt, Karl‐Ludwig Laugwitz, Michael Joner

Bibliographic record

VenueStructural Heart · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMcGill University
FundersDeutsche Gesellschaft für Kardiologie-Herz und Kreislaufforschung.Technische Universität MünchenElse Kröner-Fresenius-Stiftung
KeywordsCardiologyInternal medicineMedicinePulmonary arteryAortic valve

Abstract

fetched live from OpenAlex

Background The interplay between the right ventricle and the pulmonary artery, known as right ventricular to pulmonary artery (RV-PA) coupling, is crucial for assessing right ventricular systolic function against the afterload from the pulmonary circulation. Pulmonary artery pressure levels are ideally measured by right heart catheterization. Yet, echocardiography represents the most utilized method for evaluating pulmonary artery pressure levels, albeit with limitations in accuracy. This study therefore aims to evaluate the prognostic significance of right ventricular to pulmonary artery (RV-PA) coupling expressed as tricuspid annular plane systolic excursion (TAPSE) related to systolic pulmonary artery pressure (sPAP) levels measured by right heart catheterization (TAPSE/sPAP invasive ) or estimated by transthoracic echocardiography (TAPSE/sPAP echocardiography ) in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement (TAVR). Methods Using data from a bicentric registry, this study compares TAPSE/sPAP invasive vs. TAPSE/sPAP echocardiography in predicting 1-year all-cause mortality after TAVR. Results Among 333 patients with complete echocardiography and right heart catheterization data obtained before TAVR, their mean age was 79.8 ± 6.74 years, 39.6% were female, and general 1-year survival was 89.8%. sPAP invasive and sPAP echocardiography showed only moderate correlation (Pearson correlation coefficient R : 0.53, p value: <0.0001). TAPSE/sPAP invasive was superior to TAPSE/sPAP echocardiography in predicting 1-year all-cause mortality after TAVR (area under the curve: 0.662 vs. 0.569, p value: 0.025). Patients with reduced TAPSE/sPAP invasive levels (< 0.365 mm/mmHg) evidenced significantly lower 1-year survival rates than patients with preserved TAPSE/sPAP invasive levels (81.8 vs. 93.6%, p value: 0.001; hazard ratio for 1-year mortality: 3.09 [95% confidence interval: 1.55-6.17]). Echocardiographic follow-up data revealed that patients with reduced RV-PA coupling suffer from persistent right ventricular dysfunction (TAPSE: 16.6 ± 4.05 mm vs. 21.6 ± 4.81 mm in patients with preserved RV-PA coupling) and severe tricuspid regurgitation (diagnosed in 19.7 vs. 6.58% in patients with preserved RV-PA coupling). Conclusions RV-PA coupling expressed as TAPSE/sPAP invasive can refine stratification of severe aortic stenosis patients into low-risk and high-risk cohorts for mortality after TAVR. Moreover, it can help to anticipate persistent extra-aortic valve cardiac damage, which will demand further treatment.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.015
GPT teacher head0.320
Teacher spread0.304 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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