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. 2023 Jan 22;10(2):38.
doi: 10.3390/jcdd10020038.

Does Gender Influence the Indication of Treatment and Long-Term Prognosis in Severe Aortic Stenosis?

Celia Gil Llopis  1 , Amparo Valls Serral  1 , Ildefonso Roldán Torres  1 , Maria Belén Contreras Tornero  1 , Ana Cuevas Vilaplana  1 , Adrian Sorribes Alonso  1 , Pablo Escribano Escribano  1 , Pau Gimeno Tio  1 , Esther Galiana Talavera  1 , Juan Geraldo Martínez  1 , Paula Gramage Sanchis  1 , Alberto Hidalgo Mateos  1 , Vicente Mora Llabata  1
Affiliations

Does Gender Influence the Indication of Treatment and Long-Term Prognosis in Severe Aortic Stenosis?

Celia Gil Llopis et al. J Cardiovasc Dev Dis. .

Abstract

Introduction: It is a matter of controversy whether the therapeutic strategy for severe aortic stenosis (AS) differs according to gender.

Methods: Retrospective study of patients diagnosed with severe AS (transvalvular mean gradient ≥ 40 mmHg and/or aortic valvular area < 1 cm2) between 2009 and 2019. Our aim was to assess the association of sex on AVR or medical management and outcomes in patients with severe AS.

Results: 452 patients were included. Women (51.1%) were older than men (80 ± 8.4 vs. 75.8 ± 9.9 years; p < 0.001). Aortic valve replacement (AVR) was performed less frequently in women (43.4% vs. 53.2%; p = 0.03), but multivariate analyses showed that sex was not an independent predictor factor for AVR. Age, Charlson index and symptoms were predictive factors (OR 0.81 [0.82-0.89], OR 0.81 [0.71-0.93], OR 22.02 [6.77-71.64]). Survival analysis revealed no significant association of sex within all-cause and cardiovascular mortalities (log-rank p = 0.63 and p = 0.07). Cox proportional hazards analyses showed AVR (HR: 0.1 [0.06-0.15]), Charlson index (HR: 1.13 [1.06-1.21]) and reduced LVEF (HR: 1.9 [1.32-2.73]) to be independent cardiovascular mortality predictors.

Conclusions: Gender is not associated with AVR or long-term prognosis. Cardiovascular mortality was associated with older age, more comorbidity and worse LVEF.

Keywords: aortic valve replacement; aortic valve stenosis; mortality; sex differences; treatment outcome.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Binary logistic regression model used for multivariate analysis of predictors of AVR.
Figure 2
Figure 2
Cox regression used for multivariate analysis of predictors of cardiovascular mortality.
Figure 3
Figure 3
Kaplan–Meier survival curves according to gender.
Figure 4
Figure 4
Kaplan–Meier cardiovascular survival according to type of AVR.
See this image and copyright information in PMC

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