599 Gender-based differences in TAVI outcomes: report from a large contemporary real-world population of self-expandable valves
Notice bibliographique
Résumé
Abstract Aims Small sub-study data derived from randomized clinical trials suggest a gender-based disparity in TAVI outcomes. However, large real-world contemporary data is missing. The aim of this study is to compare the risk factors, procedural characteristics and clinical outcomes of male and female patients who underwent transcatheter aortic valve implantation (TAVI) using two next-generation self-expandable bioprostheses (ACURATE neo and Evolut R/Pro valves). Methods We performed a first unmatched comparison and a propensity score-matched analysis (PSM) to assess the outcomes derived by the sex difference beyond the impact of pre-procedural risk factors in a large, contemporary, real-world, multicentre, international, retrospective registry of 3862 consecutive patients. The primary endpoint was a composite of all-cause death or any stroke (disabling and non-disabling) at 1 year. Results Sixty-four per cent (2162/3353 patients) of the study cohort was female and was older (mean age 82.3 years vs. 81.1 years for men (P<0.001)) had a higher BMI (27.7±5.7 for women vs. 27.2±4.5 for men), and lower prevalence of dyslipidaemia (50.2% vs. 54.7, P=0.037), diabetes (26.8% vs. 33.7, P<0.001), smoking (10.0% vs. 24.3%, P<0.001), COPD (17.4% vs. 21.9%, P=0.002), pacemaker/ICD (9.6% vs. 14.0%, P<0.001), previous cardiac surgery (8.6% vs. 18.8%, P<0.001), previous PCI (23.0% vs. 36.8%, P<0.001). Mean STS score for women was higher 5.2±3.9% vs. 4.5±3.4% (P<0.001). Women had higher mean valve gradients (45.4±17.1 vs. 42.7±14.7 mmHg; P<0.001), smaller valve areas (mean 0.7 cm2 vs. 0.9 cm2, P=0.037) and smaller annular perimeters (56.8±23.0 vs. 62.0±23.8, P<0.001). The primary endpoint was resulted in a rate of 7.9% vs. 6.9% (P=0.337) in the unmatched population and 9.4% vs. 6.0% (P=0.014) after the PSM, respectively for women and for men. Independently, there was no difference in mortality (5.9% vs. 5.6%; P=0.786) and stroke (2.5% vs. 1.8%; P=0.243) rates between women and men in the un-matched groups. Rates of cardiac tamponade (1.5% vs. 0.4%, P=0.008), major vascular complications (7.7% vs. 4.1%, P<0.001), life-threatening bleeding (2.8% vs. 1.4%, P=0.016), major bleeding (5.1% vs. 2.9%, P=0.004), need of transfusion (8.9% vs. 4.6%, P<0.001) and acute kidney injury (8.5% vs. 5.7%, P=0.009), were all significantly higher in women. After PSM, mortality was similar between the two groups (11.3% for women vs. 9.5% for men, P=0.264) but strokes were more prevalent in women (2.8% vs. 1.2%, P<0.024). Furthermore, in the matched population, major vascular complications (6.8% vs. 4.1%, P=0.024), need of transfusion (9.1% vs. 4.6%, P<0.001) and acute kidney injury (8.7% vs. 5.6%, P=0.009) remained significantly different between women and men, respectively. Conclusions In this large real-world contemporary TAVI registry, female gender was associated with higher rates of stroke, vascular complications, major bleeding, and acute kidney injury. Further studies are required to explore the underlying pathophysiological mechanisms for these observations.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».