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Enregistrement W2765602292 · doi:10.1093/ehjci/jex258

Outcome of aortic valve replacement in aortic stenosis: the number of valve cusps matters

2017· letter· en· W2765602292 sur OpenAlexafffund
Philippe Pîbarot, Marie‐Annick Clavel

Notice bibliographique

RevueEuropean Heart Journal - Cardiovascular Imaging · 2017
Typeletter
Langueen
DomaineMedicine
ThématiqueCardiac Valve Diseases and Treatments
Établissements canadiensUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésStenosisCardiologyInternal medicineAortic valve replacementAortic valveMedicineAortic valve stenosisValve replacement

Résumé

récupéré en direct d'OpenAlex

Although the prevalence of bicuspid aortic valve (BAV) is only 0.5–1% in children, it accounts for about half of aortic valve replacements (AVRs) for aortic valve stenosis (AS). These findings illustrate that valve remodelling occurs more frequently and more rapidly on bicuspid than on tricuspid aortic valves (TAVs). During their lifetime, most subjects with a BAV develop aortic valve dysfunction, mostly AS, whereas only 1% remains with a normal valve function.1 In both subjects with a BAV and those with a TAV, age is a powerful risk factor for AS, and the prevalence of this disease in the population is 3% and 10%, in the subjects >65 and 80 years of age, respectively.2 Individuals with a BAV, however, develop AS one or two decades earlier than those with a TAV and their lifetime risk of AVR is around 50% (Table 1). In this issue of the journal, Huntley et al.3 present an elegant study in which they compared age-matched cohorts of 198 BAV stenosis and 198 TAV stenosis patients. The authors found that, at a given age, patients with TAV stenosis have higher prevalence of cardiovascular risk factors, greater degree of cardiac impairment and worse survival after AVR compared to those with BAV stenosis (Table 1). Similarities and differences between BAV and TAV stenosis AS, aortic valve stenosis; AVR, aortic valve replacement; BAV, bicuspid aortic valve; Lp(a), lipoprotein(a); TAV, tricuspid aortic valve. Similarities and differences between BAV and TAV stenosis AS, aortic valve stenosis; AVR, aortic valve replacement; BAV, bicuspid aortic valve; Lp(a), lipoprotein(a); TAV, tricuspid aortic valve. The mutations that have been identified in families with BAV are in the NOTCH1 and GATA5 genes2,4 (Table 1). The NOTCH1 mutations are associated with both BAV phenotype and derepression of aortic valve calcium deposition. Hence, these mutations not only predispose to the development of a BAV but they also promote valve mineralization later in life, therefore exacerbating the risk of developing AS. In subjects with TAV, studies using a candidate gene approach have identified several genes (Table 1). However, these associations still need to be confirmed in larger samples. Recent large studies using a Mendelian randomization design have identified the single-nucleotide polymorphism (rs10455872) at the LPA gene locus as the only genome-wide significant single-nucleotide polymorphism associated with the presence of aortic valve calcification and clinical AS.5 The clinical risk factors associated with AS are similar to those associated with atherosclerosis and include older age, male sex, smoking, hypertension, hypercholesterolaemia, obesity, metabolic syndrome, diabetes, and elevated lipoprotein(a) [Lp(a)] (Table 1).2 There is, however, no evidence that these cardiovascular risk factors would have more pronounced effect on the initiation or progression of AS in TAV vs. BAV subjects. By matching the BAV and TAV cohorts, Hunter et al.3 adjusted for the most powerful risk factor of AS, i.e. age. The cohorts were also well matched with respect to sex, which has been shown to have an important effect on the pathobiology and outcome of AS.2,6 The prevalence of cardiovascular risk factors such as obesity, diabetes, hypertension, and hypercholesterolaemia as well as that of atherosclerotic diseases such as coronary artery disease and peripheral vascular disease were much higher in the TAV stenosis cohort than in the BAV stenosis cohort, despite similar age and sex distribution in both cohorts.3 The most striking difference between the two cohorts was for diabetes, which prevalence was 2.4 higher in TAV (46 vs. 19%). Obesity, metabolic syndrome, and diabetes are among the risk factors that exhibit the strongest association with AS incidence, progression, and outcomes.7,8 Furthermore, these cardiometabolic risk factors are also associated with higher risk of structural valve deterioration following AVR with a bioprosthesis.9 Hypertension has also been reported to have an important effect on the pathophysiology and outcomes of AS both prior and after AVR.10,11 The marked over-representation of cardiovascular risk factors in the TAV cohort vs. the BAV cohort after age matching3 provides support to the concept that, in middle-age TAV subjects, the progression rate, and clinical outcome of calcific AS are, in large part, driven by cardiometabolic risk factors (Table 1). In BAV patients, the aforementioned genetic factors as well as mechanical factors related to the BAV configuration (i.e. increased mechanical stress on valve leaflets and turbulent transvalvular flow) likely have a predominant contribution to the pathogenesis of AS and these factors may occult—or compete with—the effects of cardiovascular risk factors on the course of aortic valve disease (Table 1). In their study, Hunter et al.3 did not report the prevalence of metabolic syndrome and Lp(a). One would expect that plasma levels of Lp(a), a potential causal factor of calcific AS, would be higher in the TAV cohort than in the BAV cohort. The differences in the baseline risk profile between the TAV and BAV stenosis cohorts largely explain the worse cardiac function and lower survival rates observed in the TAV cohort (Table 1).3 Interestingly, the 5-year survival rate (79%) in the BAV cohort was comparable to the expected survival in the general population (86%), whereas in the TAV cohort, survival was substantially lower (61%). In the multivariable analysis, the Charlson comorbidity index but not the aortic valve phenotype was associated with increased risk of mortality after AVR. This is consistent with the fact that differences in outcomes between TAV and BAV are, in large part, related to differences in baseline risk profile and comorbidities (Table 1). Compared with subjects with TAV, those with BAV have larger aortic annulus and thus lower prevalence of small prosthetic valves and ensuing prosthesis–patient mismatch following AVR. In this study,3 prosthesis–patient mismatch was indeed more frequent in TAV than in BAV patients (37 vs. 25%; P = 0.019) and was strongly and independently associated with increased risk of mortality. This finding may also contribute to explain the worse survival observed in TAV vs. BAV patients. This also further emphasizes the importance of avoiding prosthesis–patient mismatch in patients with severe AS undergoing AVR. If you are born with a normal TAV, you likely need to have cardiovascular risk factors such as metabolic syndrome, diabetes, hypertension, dyslipidaemia, or high Lp(a), to develop AS at a young or middle age. On the other hand, if you are born with a BAV, you have a high likelihood to develop AS at relatively young age, even in the absence of any of these risk factors. As expected, BAV patients more frequently have concomitant aortopathy, which does not appear to alter their prognosis after AVR. On the other hand, these patients have larger aortic annulus and thus lower risk of prosthesis–patient mismatch following AVR, compared to TAV patients. This difference further contributes to the better survival of BAV vs. TAV patients after AVR. Future interventional studies should focus on aggressive cardiovascular risk factor management to improve outcomes after AVR, particularly in the subset of patients with a TAV. P.P. holds the Canada Research Chair in Valvular Heart disease and his research program is funded by a Foundation grant (FDN-143225) from Canadian Institutes of Health Research (Ottawa, Ontario, Canada). M.-A.C. received a research scholarship from Fonds de Recherche en Santé du Québec. Conflict of interest: None declared.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0060,004
Charge utile insuffisante (le modèle a refusé de juger)0,0020,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,339
Écart entre enseignants0,308 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2017
Routes d'admission2
Résumé présentoui

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