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Record W4416060547 · doi:10.1093/eurheartj/ehaf784.040

Impact of symptoms and left ventricular systolic function in patients with moderate mixed aortic valve disease

2025· article· en· W4416060547 on OpenAlexaff
María Pilar López Santi, Jérémy Bernard, Andréanne Powers, Khalid A. Abdoun, Dorien Laenens, Ai‐Ping Chua, Bart J.J. Velders, Paolo Springhetti, Mohammed Amanullah, See Hooi Ewe, K H Yiu, Philippe Pîbarot, Marie‐Annick Clavel, J. J. Bax, Nina Ajmone Marsan

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsEjection fractionRegurgitation (circulation)StenosisClinical endpointAortic valve replacementAortic valve stenosisDiabetes mellitusAortic valve

Abstract

fetched live from OpenAlex

Abstract Background There is limited data on mortality in patients with truly moderate mixed aortic valve disease (MAVD), defined as the combination of moderate aortic stenosis (AS) and moderate aortic regurgitation (AR). Consequently, current guidelines do not provide specific recommendations for aortic valve replacement (AVR) in this population. Objectives This study aims to compare survival between patients with moderate MAVD and those with isolated severe AS or severe AR. Patients were further stratified based on the presence of symptoms or left ventricular ejection fraction (LVEF) <50%, as current criteria for AVR in severe AS or AR. Methods A total of 1926 patients were included from four tertiary centers: 527 with moderate MAVD, 413 with severe AR, and 986 with severe AS. The primary endpoint was all-cause mortality. Results Patients with moderate MAVD were older (68 ± 18 vs. 58 ± 22 years, p<0.001) and more often female (57% vs. 25%, p<0.001) than those with severe AR. They had higher rates of CAD (36% vs. 11%, p<0.001), hypertension (61% vs. 44%, p<0.001), diabetes (23% vs. 7%, p<0.001), and AF (24% vs. 14%, p<0.001), but lower BAV prevalence (11% vs. 43%, p<0.001). Their LV dimensions were smaller (LVEDD 51 ± 8 vs. 59 ± 9 mm, p<0.001), with more concentric remodeling (RWT: 0.44 ± 0.12 vs. 0.37 ± 0.08, p<0.001). Compared to severe AS, patients with moderate MAVD were younger (68 ± 18 vs. 77 ± 13 years, p<0.001), more frequently male (57% vs. 44%, p<0.001), had less CAD (36% vs. 47%, p<0.001), more BAV (11% vs. 8%, p<0.001), and larger LVEDD (51 ± 8 vs. 47 ± 8 mm, p<0.001), but similar LV remodeling (p<0.001) and less RV dysfunction (TAPSE <18 mm: 16% vs. 27%, p<0.001). No significant differences were found in HF symptoms (NYHA II-IV, p=0.267), LV systolic dysfunction (LVEF <50%, p=0.064), or LA enlargement (LAVI >34 ml/m², p=0.208). Over a median follow-up of 7.2 (IQR, 3.4-11.3) years, 748 patients died. After adjusting for relevant clinical and echocardiographic variables (among which NYHA class, LVEF <50%, and AVR as time-dependent covariate) patients with moderate MAVD showed a 10-year survival similar to severe AS but worse than severe AR (62%, 55%, and 79% respectively, p<0.001) (Figure 1). Symptomatic moderate MAVD patients showed adjusted mortality comparable to symptomatic severe AS, while asymptomatic moderate MAVD patients had adjusted mortality similar to severe AR (both symptomatic and asymptomatic) (Figure 2A). Patients with moderate MAVD and LVEF<50% had adjusted mortality comparable to severe AS with LVEF<50%, while those with LVEF≥50% showed mortality rates similar to severe AR (regardless of LV dysfunction) (Figure 2B). Conclusions In moderate MAVD, the presence of symptoms or LVEF<50% is associated with reduced long-term survival, comparable to isolated severe AS under similar conditions. Therefore, patients with moderate MAVD should benefit from AVR in the presence of symptoms or LV dysfunction.

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 score0.002
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.289
Teacher spread0.281 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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