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Record W4411983574 · doi:10.1093/ejcts/ezaf099

Gender-based outcomes following surgical aortic valve replacement: a multicentre propensity score matching analysis

2025· article· en· W4411983574 on OpenAlexaff
Ruggero De Paulis, Farhad Bakhtiary, Ali Ahmad, Martin Andreas, R Autschbach, Peter Benedikt, Konrad Binder, Nikolaos Bonaros, Michael A. Borger, Thierry Bourguignon, Sergio Cánovas, Enrico Coscioni, François Dagenais, Philippe Demers, Oliver Dewald, Nicolas Doll, Richard Feyrer, Hans-Joachim Geißler, Martin Grabenwöger, Jürg Grünenfelder, Sami Kueri, Ka Yan Lam, Thierry Langanay, Günther Laufer, Wouter van Leeuwen, Seymur Karimli, Andreas Liebold, Giovanni Mariscalco, Parwis Massoudy, Arash Mehdiani, Renzo Pessotto, Francesco Pollari, Jochen Pöling, Gianluca Polvani, Jean‐Christian Roussel, Saad Salamate, Matthias Siepe, Pierluigi Stefàno, Justus Strauch, Alexis Théron, Andreas Vötsch, Alberto Weber, Olaf Wendler, Matthias Thielmann, Matthias Eden, Beate Botta, Peter Bramlage, Bart Meuris, Andreas Zierer

Bibliographic record

VenueEuropean Journal of Cardio-Thoracic Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité de MontréalMontreal Heart InstituteUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersEdwards Lifesciences
KeywordsMedicinePropensity score matchingInternal medicineAortic valve replacementProspective cohort studyCardiologyBody mass indexSurgeryStenosis

Abstract

fetched live from OpenAlex

OBJECTIVES: This study investigated the gnder-based difference in three-year clinical outcomes, left ventricular (LV) regression, and quality-of-life (QoL) following surgical aortic valve replacement (SAVR) by propensity score matching (PSM). METHODS: A prospective multicentre study on combined data from two prospective registries, INDURE and IMPACT, resulted in 993 patients (735 males and 258 females). PSM yielded 689 patients: 442 males and 247 females undergoing first-time SAVR using Edwards INSPIRIS RESILIA. RESULTS: In the PSM cohort, females had lower body mass index (median 27.9 vs 28.6 kg/m2; P = 0.004), higher European System for Cardiac Operative Risk Evaluation (EuroSCORE) II (2.4 ± 3.0 % vs 1.8 ± 1.9 %; P < 0.001), Society of Thoracic Surgeons (STS) score (1.8 ± 1.7 % vs 1.3 ± 2.0 %; P < 0.001) and were most often in New York Heart Association class III/IV (45.7 % vs 37.6 %; P < 0.021), angina CCS class III/IV (6.1 % vs 2.9 %; P < 0.001) than males. Post-SAVR clinical outcomes up to three years were similar between both genders. Significant differences existed for LV regression after surgery between genders at up to three years (P < 0.001) with better haemodynamic performance. Hypertension slowed the LV mass regression, mildly affecting LV restoration in females for up to three years. In both genders, New York Heart Association status was restored within one year (P < 0.001) and maintained for up to three years (P < 0.001). At three years, QoL significantly improved. CONCLUSIONS: Despite females presenting with a significantly higher surgical risk profile, three-year outcomes following SAVR were comparable between genders with significant improvement in functional status. However, the degree of QoL improvement differed between genders. CLINICAL TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT04053088/-NCT03666741.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.048
GPT teacher head0.351
Teacher spread0.303 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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