Sarcopenia detected by computed tomography: a simple tool for screening transcatheter aortic valve implantation candidates
Notice bibliographique
Résumé
Frailty, defined as a clinical state that makes the individual more vulnerable to the effects of stressors, is common in elderly patients affected by aortic stenosis and/or heart failure with a wide range of prevalence based on the tools used.1–4 The assessment of frailty is crucial in the management of patients with severe aortic stenosis, as it can drive the choice between surgery, transcatheter aortic valve implantation (TAVI) or conservative care.5 Indeed, international guidelines strongly recommend to objectively evaluate frailty before planning either surgical or percutaneous valve interventions using the Katz activities of daily living score and the gait speed by the 5-min walking test.6 Other tools for frailty screening and assessment have been even proposed.2,7 Sarcopenia and frailty are strongly related and both are associated with poor outcomes in several cardiovascular settings.8–13 The assessment of sarcopenia by psoas muscle area using computed tomography (CT) recently emerged as a possible tool for screening TAVI recipients. However, evidence regarding its prognostic impact diverges.14,15 In the current issue, Walpot et al.16 sought to retrospectively evaluate the role of psoas muscle attenuation (PMA) assessed by CT in predicting long-term all-cause mortality after TAVI. They analysed 94 consecutive TAVI patients with a median age of 81 years and at intermediate surgical risk (median STS score 4.7%). Common clinical frailty scores were also evaluated. Assessment of PMA was expressed by three variables: psoas mean Hounsfield Units (HU), circumferential surface area low-density muscle (CSA LDM%) and high-density muscle over low-density muscle ratio (HDM/LDM). These measurements were performed using postprocessing CT images routinely obtained during the preprocedural planning. They were reproducible with a low interobserver and intraobserver variability. Psoas muscle attenuation was found to be a strong and independent predictor of clinical outcome after TAVI being associated with an up-to five-fold increased risk of 5-year all-cause mortality. The results of this study clarify and confirm the role of sarcopenia assessed by CT in patients undergoing TAVI. Specific measurements of PMA [mean HU, CSA LDM (%) and HDL/LDM ratio], rather than a mere evaluation of psoas muscle area may help to identify patients more likely to be frail and to have a poor outcome. Another important finding is that PMA was sex-independent and not subject to normalization to body surface area, further increasing its appeal for routine clinical use. Moreover, as well stated by the authors, the advantage of this tool is that it is simple and reproducible and can be obtained by postprocessing the standard pre-TAVI CT images with no additional radiation load. The authors need to be congratulated also for the long follow-up reported, of almost 5 years, which is definitely longer compared with other similar studies. On the contrary, the findings of Walpot et al.16 are limited by the retrospective nature of the study and by the small sample size, which make them hypothesis-generating only. Larger and prospective studies are needed to confirm these interesting results and to identify possible thresholds that may further help in the stratification of TAVI candidates according to their frailty status. Moreover, it would be interesting to investigate the role of nutritional treatment and physiotherapy in this setting.17 The unexplored synergic effect of intervention on aortic valve disease and therapies for frailty/sarcopenia might perhaps be the in the management of these patients. Conflicts of interest There are no conflicts of interest.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,007 |
| Bibliométrie | 0,000 | 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 ».