Including body composition in MELD scores improves mortality prediction among patients awaiting liver transplantation.


Journal

Clinical nutrition (Edinburgh, Scotland)
ISSN: 1532-1983
Titre abrégé: Clin Nutr
Pays: England
ID NLM: 8309603

Informations de publication

Date de publication:
06 2020
Historique:
received: 30 01 2019
revised: 13 08 2019
accepted: 13 08 2019
pubmed: 5 9 2019
medline: 17 8 2021
entrez: 5 9 2019
Statut: ppublish

Résumé

The Model for End-stage Liver Diseases (MELD) is widely accepted for prioritizing candidates awaiting liver transplantation (LT). However, MELD scores do not reflect the severity of the nutritional or functional status of patients with cirrhosis. This retrospective study analyzed data from 173 patients who were waitlisted for LT at our institution between April 2006 and December 2016. By including skeletal muscle mass, muscle quality and visceral adiposity evaluated using plain computed tomography imaging in MELD scores, we developed body composition-MELD (BC-MELD), and investigated its impact on the prediction of mortality among patients awaiting LT. The equation generated using Cox regression analysis was as follows: BC-MELD = MELD score + 3.59 × low SMI + 5.42 × high IMAC + 2.06 × high VSR. (IMAC, intramuscular adipose tissue content; SMI, skeletal muscle mass index; VSR, visceral-to-subcutaneous adipose tissue area ratio). The median BC-MELD score was 17.4 and the area under the receiver operating characteristic curve (AUC) revealed a cut-off BC-MELD score of 21.4 (AUC = 0.835, P < 0.001, sensitivity 87.5%, specificity 70.7%). Waitlist mortality in patients with high BC-MELD was significantly higher in all tested cohorts (P < 0.001) and among patients with lower conventional MELD scores (<15) (P < 0.001). The discriminatory power was significantly better for BC-MELD than MELD scores (AUC; 0.835 vs. 0.732, P = 0.001 for 3-month, AUC; 0.765 vs. 0.671, P = 0.002 for 6-month, AUC; 0.716 vs. 0.615, P < 0.001 for 12-month, AUC; 0.636 vs. 0.584, P = 0.014 for overall mortality). BC-MELD is the first to include not only muscularity but also visceral adiposity. It predicted waitlist mortality more accurately than the conventional MELD score. A new allocation system based on BC-MELD might lead to better outcomes for patients with cirrhosis awaiting LT.

Sections du résumé

BACKGROUND & AIMS
The Model for End-stage Liver Diseases (MELD) is widely accepted for prioritizing candidates awaiting liver transplantation (LT). However, MELD scores do not reflect the severity of the nutritional or functional status of patients with cirrhosis.
METHODS
This retrospective study analyzed data from 173 patients who were waitlisted for LT at our institution between April 2006 and December 2016. By including skeletal muscle mass, muscle quality and visceral adiposity evaluated using plain computed tomography imaging in MELD scores, we developed body composition-MELD (BC-MELD), and investigated its impact on the prediction of mortality among patients awaiting LT.
RESULTS
The equation generated using Cox regression analysis was as follows: BC-MELD = MELD score + 3.59 × low SMI + 5.42 × high IMAC + 2.06 × high VSR. (IMAC, intramuscular adipose tissue content; SMI, skeletal muscle mass index; VSR, visceral-to-subcutaneous adipose tissue area ratio). The median BC-MELD score was 17.4 and the area under the receiver operating characteristic curve (AUC) revealed a cut-off BC-MELD score of 21.4 (AUC = 0.835, P < 0.001, sensitivity 87.5%, specificity 70.7%). Waitlist mortality in patients with high BC-MELD was significantly higher in all tested cohorts (P < 0.001) and among patients with lower conventional MELD scores (<15) (P < 0.001). The discriminatory power was significantly better for BC-MELD than MELD scores (AUC; 0.835 vs. 0.732, P = 0.001 for 3-month, AUC; 0.765 vs. 0.671, P = 0.002 for 6-month, AUC; 0.716 vs. 0.615, P < 0.001 for 12-month, AUC; 0.636 vs. 0.584, P = 0.014 for overall mortality).
CONCLUSIONS
BC-MELD is the first to include not only muscularity but also visceral adiposity. It predicted waitlist mortality more accurately than the conventional MELD score. A new allocation system based on BC-MELD might lead to better outcomes for patients with cirrhosis awaiting LT.

Identifiants

pubmed: 31481263
pii: S0261-5614(19)33024-9
doi: 10.1016/j.clnu.2019.08.012
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1885-1892

Informations de copyright

Copyright © 2019 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Auteurs

Yuhei Hamaguchi (Y)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Toshimi Kaido (T)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan. Electronic address: kaido@kuhp.kyoto-u.ac.jp.

Shinya Okumura (S)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Atsushi Kobayashi (A)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Hisaya Shirai (H)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Siyuan Yao (S)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Shintaro Yagi (S)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Naoko Kamo (N)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Shinji Uemoto (S)

Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

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