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Sarcopenia on lumbar paraspinal muscles is receiving renewed attention as a cause of spinal degeneration. However, there are few studies on the precise concept and diagnostic criteria for spinal sarcopenia. Here, we develop the concept of spinal sarcopenia in community-dwelling healthy elderly people. In addition, we aim to observe the natural aging course of paraspinal muscle and back muscle strength, and investigate the association between conventional sarcopenic indices and spinal sarcopenia.
This is a prospective observational cohort study with 120 healthy community-dwelling elderly people for 4 years. All subjects will be recruited according to no sarcopenia, possible sarcopenia, sarcopenia, and severe sarcopenia groups. The primary outcomes of this study are isokinetic back muscle strength and lumbar paraspinal muscle quantity and quality using lumbar spine MRI. Conventional sarcopenic indices and spine specific outcomes such as spinal sagittal balance, back performance scale, and Sorenson test will be also assessed. The data will be analysed using the intention-to-treat principle.
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This is a prospective observational cohort study with 120 healthy community-dwelling elderly people in a single center (SMG-SNU Boramae Medical Center). Individual follow-up will last 4 years. Elderly people (≥ 65 years old) who are community-dwellers and able to walk with or without assistive devices) will be included. Sarcopenia can be divided by two stages: 1) possible sarcopenia (PS) defined by low handgrip strength and/or low gait speed and 2) sarcopenia (SA) confirmed by low handgrip strength and/or low gait speed and low muscle mass by the consensus report of the Asian working group for sarcopenia. No sarcopenia (NS) group is added to this classification, and the study participants are classified into three groups (NS, PS, and SA) after the screening tests. All outcome variables will be collected at baseline, 2 and 4 years. However, L-S spine MRI for lumbar paraspinal muscle quantity and quality will be performed only at baseline.
Data will be collected using a standardised data entry form and entered into the data management system. The intention-to-treat principle will be used for data analysis. Participant characteristics will be described using means and standard deviations for continuous data and frequencies and percentages for categorical data. The three groups will be compared using an analysis of variance (ANOVA) or the non-parametric equivalence Kruskal-Wallis test if required. To compare paired data (intra-group) between two different points, we will use repeated-measures ANOVA and Friedman tests for continuous and non-parametric data, respectively.
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