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Enregistrement W2410708572 · doi:10.1093/ehjci/jew110

Quantification of paravalvular regurgitation after transcatheter aortic valve implantation: improved accuracy means better standardization

2016· editorial· en· W2410708572 sur OpenAlexaff
Patrizio Lancellotti, Nicolò Piazza, Thomas Modine

Notice bibliographique

RevueEuropean Heart Journal - Cardiovascular Imaging · 2016
Typeeditorial
Langueen
DomaineMedicine
ThématiqueCardiac Valve Diseases and Treatments
Établissements canadiensMcGill University Health Centre
Organismes subventionnairesnon disponible
Mots-clésRegurgitation (circulation)CardiologyInternal medicineMedicineStandardizationComputer science

Résumé

récupéré en direct d'OpenAlex

If you think of standardization as the best that you know today, but which is to be improved tomorrow; you get somewhere Aortic stenosis (AS) is the most common valvular heart disease in western countries. Because of the ageing population, AS is being an increasing health problem with sizeable economic impact.1 AS is a gradually progressive disease, characterized by a long asymptomatic phase, lasting several decades, followed by a shorter symptomatic phase associated with severe narrowing of the orifice of the aortic valve. Once symptoms occur, the prognosis is poor and without treatment; patients usually die within 2–3 years.2,3 Surgical aortic valve replacement is considered the standard treatment for symptomatic AS. Transcatheter aortic valve implantation (TAVI) has recently emerged as an alternative therapy for patients with severe AS who are not candidates for surgery or are at high risk for complications due to surgery.4 TAVI is non-inferior to surgery in terms of early and mid-term mortality and is likely to be superior if the patient has vascular anatomy and vessels that are healthy enough to be treated with the use of a transfemoral approach.4,5 However, despite its favourable haemodynamics, paravalvular aortic regurgitation (PVAR) is common after TAVI.6 PVAR is an independent predictor of short- and long-term mortality, though the impact of mild regurgitation remains controversial.4,5 The accurate assessment of PVAR severity is warranted but remains challenging. Doppler echocardiography is the most used imaging technique to assess AR severity.7 The origin and direction of the jets should be evaluated.8 The optimal views for detection of regurgitant jets include the parasternal long-axis, short-axis (SAX), apical long-axis, and five-chamber views. Because PVAR jets travel along the natural curvature of the prosthesis annular interface (eccentric jets), imaging in multiple planes including off-axis views is necessary. Colour Doppler evaluation should be performed just below the valve stent for paravalvular jets and at the coaptation point of the leaflets for central regurgitation. The entire circumference of the valve ring must be assessed using the parasternal short-axis view. Apical views should thus be carefully examined to properly detect and quantitate potential posterior jets that maybe missed in the parasternal views (shadowing effect of the stent).9 Generally, the same principles and methods used for quantification of other prosthetic valves are used with determination of flow convergence zone, measurement of the vena contracta, and extent of regurgitation into the left ventricle and spectral Doppler parameters such as the pressure half-time and diastolic flow reversal into the descending aorta.10 However, there are very limited data on the application and validation of these parameters (e.g. vena contracta width, effective regurgitant orifice area, regurgitant volume) in the context of TAVI. Recently, the Valve Academic Research Consortium (VARC) has revisited the echocardiographic criteria for defining PVAR severity after TAVI.8 The VARC-II adopted the SAX criterion as ‘critical’ in assessing the number and severity of paravalvular jets. With this approach, identification of the true neck of the jet is mandatory. Due to the complexity of certain PVARs and the limitation of the echocardiography in certain situations (acoustic shadowing, eccentric jets, multiple jets), the evaluation of the PVAR might need to be completed with other imaging techniques [3D echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), invasive angiography].11,12 3D echocardiography, especially during transoeophageal echocardiography, is ideal for imaging the entire aortic prosthesis, the whole ring, and the extent of paravalvular leak. Limited echocardiographic windows, tissue dropout, poor temporal resolution, and the lack of validated data are the commonest limitations of 3D echocardiography. ECG-gated CT with 3D reconstruction is a promising tool in PVARs evaluation. CMR might be a useful supplement to echocardiography and might be the modality of choice when there is discordance in grading from different echocardiographic windows. However, the lack of evidence, inconsistency of definitions of PVAR severity, and its limited availability represent the main limitations to the widespread use of CMR for assessing AR after TAVI. After implantation, the angiographic grading of PVAR is an easy-to-use method. PVAR can be classified according to the visually estimated density of opacification of the LV into three degrees (mild, moderate, and severe) adapted to the VARC-II 2 criteria.8 Its major challenge is the delimitation of the 3D anatomic and spatial characteristics of the leak. Hence, a considerable overlap from one grade to another can be possible. In recent studies, the angiographically assessed degree of PVAR correlated with echocardiography in patients with TAVI.13 These data are consistent with those elegantly reported by Abdelghani et al.14 in a total of 165 patients treated with a self-expanding bioprosthesis who underwent contemporary angiographic and transthoracic echocardiography (TTE). In this study, the authors sought to investigate inter-technique (angiography and TTE) reproducibility of the assessment of PVAR after TAVI. Consistency between angiography and colour Doppler TTE, using the VARC-II criteria, in the grading of post-TAVI PVAR was modest. These data underscore the difficulty to visualize complex PVAR jets, which can run unpredictable and variable courses (e.g. multiple jets; jets originating at the non-coronary sinus, jets spreading out in all directions; jets running in a circumferential direction into the inflow area of the stent frame).15 To adequately image the origin of the PVAR jet in the SAX, a colour Doppler scanning over the entire height of the stent is necessary. However, as shown by Abdelghani et al., long-axis (LAX) colour Doppler (combining parasternal and apical views) was better correlated with angiography than SAX evaluation. Moreover, the combination of colour Doppler data (=PVAR jet circumferential extent (%) + LAX score) with pressure half-time improved the predictive value of TTE, yielding good positive (85%) and negative (81%) predictive values for identifying greater than mild PVAR. In practice, this methodology although unsatisfactory is easy to use for initial evaluation and monitoring after the procedure. However, the most appropriate time point to assess PVAR after TAVI remains undefined. In their study, TTE was obtained at a maximum interval of 7 days after angiographic evaluation. The different haemodynamic circumstances and the continuing expansion of the nitinol frame of the CoreValve after implantation might have hampered the accuracy of TTE assessment of AR. Therefore, generalization of the results to other devices or when TTE is performed in the cath lab should be done with caution. In conclusion, the main current limitation for PVAR quantification is the absence of a method of reference. Aortic root angiography is the first screening method in the majority of laboratories while echocardiography often serves to confirm and monitor TAVI results. At present, integrating multiple TTE qualitative, semi-quantitative, and quantitative findings should remain the recommended approach for assessing PVAR. With regard to AR, more specific, reproducible, and quantitative criteria need to be developed with the goal of determining the ‘total’ AR, reflecting the total volume load imposed on the left ventricle. Comparison of regurgitant volumes obtained by new quantitative colour Doppler approaches, 3D derived volumetric methods, and CMR might refine the perceived meaning of AR and provide a standardized imaging approach. 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)0,011
score de la tête « metaresearch » (Gemma)0,038
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: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,060

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,038
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0050,002
Bibliométrie0,0030,001
Études des sciences et des technologies0,0010,003
Communication savante0,0060,003
Science ouverte0,0030,001
Intégrité de la recherche0,0130,015
Charge utile insuffisante (le modèle a refusé de juger)0,0030,003

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 Opus0,014
Tête enseignante GPT0,319
Écart entre enseignants0,305 · 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
GenreÉditorial

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

En bref

Citations1
Publié2016
Routes d'admission1
Résumé présentoui

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