Blood, tissue and imaging biomarkers in calcific aortic valve stenosis
Notice bibliographique
Résumé
PURPOSE OF REVIEW: Calcific aortic valve stenosis is the most prevalent valvular heart disease in the high-income countries. To this date, no medical therapy has been proven to prevent or to stop the progression of aortic valve stenosis. The physiopathology of aortic valve stenosis is highly complex and involves several signalling pathways, as well as genetic related factors, which delay the elaboration of effective pharmacotherapies. Moreover, it is difficult to predict accurately the progression of the valve stenosis and finding the optimal timing for aortic valve replacement remains challenging. Therefore, the present review makes an inventory of the most recent and promising circulating and imaging biomarkers related to the underlying mechanisms involved in the physiopathology of aortic valve stenosis, as well as the biomarkers associated with the left ventricular (LV) remodelling and subsequent dysfunction in patients with aortic valve stenosis. RECENT FINDINGS: Over the last decade, several blood, tissue and imaging biomarkers have been investigated in aortic valve stenosis patients. At the aortic valve level, these biomarkers are mostly associated and/or involved with processes such as lipid infiltration and oxidation, chronic inflammation and fibrocalcific remodelling of the valve. Moreover, recent findings suggest that aging and sex hormones might interact with these multiple processes. Several studies demonstrated the usefulness of circulating biomarkers such as lipoprotein(a), brain natriuretic peptides and high-sensitivity cardiac troponin, which are very close to clinical routine. Furthermore, noninvasive imaging biomarkers including positron emission tomography and cardiac magnetic resonance, which provide a detailed view of the disease activity within the aortic valve and its repercussion on the left ventricle, may help to improve the understanding of aortic valve stenosis physiopathology and enhance the risk stratification. Other biomarkers such as von Willebrand factor and microRNAs are promising but further studies are needed to prove their additive value in aortic valve stenosis. SUMMARY: Most of the biomarkers are used in research and thus, are still being investigated. However, some biomarkers including plasma level of lipoprotein(a), F-sodium fluoride, brain natriuretic peptides and high-sensitivity cardiac troponin can be or are very close to be used for the clinical management of patients with aortic valve stenosis. Moreover, a multibiomarker approach might provide a more global view of the disease activity and improve the management strategies of these patients.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».