Skeletal muscle abnormalities and outcomes after liver transplantation
Notice bibliographique
Résumé
Muscle depletion or sarcopenia in cirrhosis is part of the frailty complex present in these patients, and it is characterized by a decreased reserve and resistance to stressors resulting from cumulative declines across multiple physiologic systems and a predisposition to poor outcomes.1 In addition, muscle depletion is characterized by both a reduction in muscle size and an increased proportion of intramuscular fat, which is called myosteatosis. Myosteatosis increases with age and adiposity and is associated with systemic metabolic abnormalities and decreased strength and mobility.2 At present, several methods are available for evaluating the body composition and muscle mass estimation of patients with cirrhosis; they include total body electrical conductivity, bioelectrical impedance, dual-energy X-ray absorptiometry, air displacement plethysmography, and magnetic resonance spectroscopy. However, most of these techniques have limitations, primarily a lack of objectivity and reproducibility. In this respect, muscularity assessment based on cross-sectional imaging studies [computed tomography (CT) scanning or magnetic resonance imaging] has become an attractive index for nutritional status evaluation in cirrhosis. The analysis is not biased by the fluid overload status or obesity that frequently presents with cirrhosis, and muscle abnormalities reflect a chronic detriment in the general physical condition rather than acute severity of the liver. In this issue of Liver Transplantation, Hamaguchi et al.3 report the impact of the preoperative quality of skeletal muscle on outcomes after living donor liver transplantation (LDLT). They evaluated the intramuscular adipose tissue content (IMAC) in multifidus muscle and the psoas muscle mass index (PMI) via CT analysis in adult patients undergoing LDLT. In male patients, a positive correlation was observed between IMAC and age, and a negative correlation was observed between IMAC and PMI; in females, a positive correlation was observed only between IMAC and age. Survival rates for patients with high IMACs or low PMIs were significantly lower than those for patients with normal IMACs or PMIs. Multivariate analysis showed that a high IMAC and a low PMI were independent risk factors for mortality after LDLT. This study by Hamaguchi et al.3 emphasizes that muscle abnormalities such as sarcopenia and myosteatosis are frequent complications in cirrhosis4-7 and, despite the important role that they play in the prognosis of cirrhosis, are frequently overlooked. Some notes of caution are in order. One important issue to be resolved is which technique is better for muscularity assessment in patients with cirrhosis. For the evaluation of sarcopenia, some studies have used the total psoas area (TPA)6, 7 or PMI3, 8 at the level of the umbilicus. However, to the best of my knowledge, there is actually no evidence confirming that the area of the psoas muscle or the PMI has a good correlation with the whole lumbar or whole body muscle areas. Moreover, the location of the umbilicus may change in patients with ascites, so measures may be recorded at different levels in these patients. In light of this potential limitation, our group has used the third lumbar skeletal muscle index (L3 SMI),4, 9, 10 which has been shown to be the best single imaging correlate of whole body muscle mass11 (Fig. 1A). Also, we have used muscle attenuation in Hounsfield units, which indirectly measures fat infiltration for the entire muscle area at the third lumbar vertebra (Fig. 1B). Therefore, prospective evidence is needed to validate the utility of these techniques and to establish which techniques have the best performance for the evaluation of sarcopenia and myosteatosis as a measure of frailty in liver transplantation. (A) CT was used for the L3 SMI assessment of 2 patients with cirrhosis with an identical body mass index (32 kg/m2). The patient imaged on the left was sarcopenic with an L3 SMI of 50 cm2/m2. The patient imaged on the right was not sarcopenic with an L3 SMI of 71 cm2/m2. (B) CT was used for the muscle attenuation assessment of patients with cirrhosis. A comparison of 2 patients with cirrhosis with similar body mass indices (28 kg/m2) is shown. The patient imaged on the left had myosteatosis (21 HU). The patient imaged on the right had normal mean muscle attenuation (40 HU). Despite these limitations, the findings of Hamaguchi et al.3 are important and add valuable information to the growing evidence that extreme sarcopenia defined with different operational definitions, such as the lowest quartile of the TPA,7 the lowest tertile of the TPA,6 the lowest sextile of the L3 SMI,10 or a low skeletal muscle mass (defined as <90% of the standard with bioelectrical impedance analysis),5 is associated with higher posttransplant mortality. Therefore, the next step will be to establish and validate specific and reproducible cutoff values stratified by sex for sarcopenia and myosteatosis that discriminate those patients with higher mortality after liver transplantation; these could be used in liver transplant centers worldwide to reduce futile liver transplantation. Finally, despite the irrefutable benefits of the Model for End-Stage Liver Disease (MELD) score, such as reductions in the number of patients listed for liver transplantation, in the waiting time for transplantation, and in the number of deaths on the waiting list, one of the major limitations of MELD is that it does not include an assessment of the nutritional and functional status of patients. Therefore, giving some priority to those patients with sarcopenia or myosteatosis before they develop extreme muscle depletion or fatty infiltration may help to decrease mortality in a subgroup of patients with cirrhosis without a negative impact on survival after liver transplantation.12 A couple of retrospective studies have shown that modifications to the MELD score to include sarcopenia (MELD-sarcopenia and MELD-psoas)8, 13 have been associated with improvements in the prediction of mortality for patients with cirrhosis; however, additional validation with larger cohorts of patients with cirrhosis is necessary before the widespread adoption of these novel scores for liver allograft allocation.
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) | 0,001 | 0,000 |
| 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 | 0,001 | 0,001 |
| 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 ».