A new sarcopenia score prognostic for postoperative complications in hepatic alveolar echinococcosis: a multicenter retrospective study

Abstract

Background: Skeletal muscle depletion and excessive visceral adipose tissue have been shown to be independent risk factors for postoperative complications (PCs) in various diseases. However, their impact on surgical PCs in hepatic alveolar echinococcosis (HAE) is still unknown. Methods:We retrospectively reviewed the clinical data of HAE patients who underwent liver resection at our hospital between January 2008 and December 2018. We segmented skeletal muscle and adipose tissue and measured the area of skeletal muscle tissue and adipose tissue at the level of the third lumbar vertebra by manual tracing from preoperative plain computed tomography (CT) images. Sarcopenia features were selected to construct a formula based on the least absolute shrinkage and selection operator (LASSO) logistic regression model in the primary set. Then, integrating the results of multiple clinicopathologic characteristics, we built a nomogram for predicting major PCs in HAE. The results were validated using bootstrap resampling and clinical data from other HAE centers in western China. Results:The sarcopenia score is based on the personalized levels of the five features from the primary set (n=233). In the multivariate logistic analysis of the primary set, the independent factors for PCs were γ-glutamyl transferase (GGT), and surface area of hepatectomy, which were integrated into the nomogram combined with sarcopenia score. The model had a good prediction capability with a C-index of 0.84 (95% CI, 0.72-0.96). The calibration plot for the probability of PCs showed an optimal agreement between the nomogram predictions and actual observations in the primary and validation sets. Conclusion:Our study showed that sarcopenia score was significantly correlated with PCs in patients with HAE. In addition, we constructed a prognostic nomogram for predicting complications in HAE patients after liver surgery. The nomogram displayed excellent discrimination and calibration. Improving the nutritional status and physical health of patients before surgery might reduce the incidence of postoperative complications for the high-risk patients.

A Sarcopenia-Based Prediction Model for Postoperative Complications of ex vivo Liver Resection and Autotransplantation to Treat End-Stage Hepatic Alveolar Echinococcosis

“…Our previous multicenter research revealed that the sarcopenia was a predictive factor for postoperative complications in HAE patients undergoing liver resection and applied the severity of sarcopenia as a classifier to divide all patients into two groups for prediction. 28 In contrast, we retained the original sarcopenia score model to maintain a higher AUROC for the final nomogram for more accurate prediction.…”

“…We specifically collected plain abdominal CT images of all patients within one month before ELRA. Then, analyses of the image data and measurements of skeletal muscle and adipose tissue were performed at the level of the third lumbar vertebra with three-dimensional visualization software 28 (Mimics Interactive Medical Image Control System, Version 25.0, Materialize Company, Belgium). To divide out skeletal muscle and adipose tissue at the level of the third lumbar vertebra, skeletal muscle areas, which included the psoas, erector spinae, quadratus lumborum, transversus abdominis, and internal and external obliques, were quantified using −29 to 150 Hounsfield units (HU), and adipose tissue areas, which included the subcutaneous adipose tissue and visceral adipose tissue, were quantified using −190 to −30 HU.…”

“…The average CT value of four ROIs placed on the subcutaneous fat at the L3 level was defined as the CT value of subcutaneous fat. 28 …”