Kudo W, Terui K, Takenouchi A, Komatsu S, Hishiki T. Establishment of a quantitative assessment model and web-based calculation tool for the skeletal muscle index in children.
Clin Nutr ESPEN 2023;
58:160-164. [PMID:
38057001 DOI:
10.1016/j.clnesp.2023.09.918]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 09/05/2023] [Accepted: 09/19/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND & AIMS
The skeletal muscle index (SMI) is widely used in adults. The reference values for SMI in children are inadequate and require validation in pediatric patients for clinical usefulness. Therefore, this study developed a quantitative assessment model for SMI in children using standard deviation (SD) curves and validated the model's utility and generalizability.
METHODS
We examined three compartments of the abdominal skeletal muscle region. SMI was calculated as skeletal muscle area divided by height squared for each compartment (PMI, psoas muscle index; PSMI, paraspinal muscle index; TSMI, total skeletal muscle index). The optimal model was generated using random grouping methods (training and testing), polynomial regression analysis, and the mean squared error evaluation methods. The generated model was validated with previously published SMI data and clinical data of patients with inflammatory bowel disease.
RESULTS
The data of 474 children were analyzed. The previously reported SMI reference values overlapped well with our model. In patients with inflammatory bowel disease, the mean (SD) Z-scores for SMI were low in boys (PMI, -1.15 [1.11]; PSMI, -1.31 [1.07]; TSMI, -0.84 [0.91]) and girls (PMI, -1.22 [1.08]; PSMI, -1.44 [1.19]; TSMI, -0.74 [1.16]). Furthermore, SMI was positively correlated with body weight, body mass index, and serum albumin level, a nutritional marker, and negatively correlated with erythrocyte sedimentation rate, an inflammatory marker.
CONCLUSION
We established a quantitative assessment model for SMI and validated the model's generalizability and clinical usefulness. We generated an easy-to-use calculation tool for Z-scores from skeletal muscle area obtained from computed tomography images, age, and height information; it has been made publicly available (http://square.umin.ac.jp/ped-muscle-calc/index.html).
Collapse