#3296 ADVERSE MUSCLE COMPOSITION ASSESSED BY MRI ASSOCIATES TO POOR FUNCTIONAL PERFORMANCE AND METABOLIC COMORBIDITIES IN CKD
Authors: Indurain Ainhoa , Karlsson Markus , Uhlin Fredrik , Fernström Anders , Segelmark Mårten , Leinhard Olof Dahlqvist 
Published: June 2023

Abstract

Background and Aims
CKD is associated with alterations in body composition, such as reduced muscle mass, increased amount of fat or both simultaneously. Furthermore, both sarcopenia and sarcopenic obesity are associated with worse physical functioning, poor quality of life, increased morbidity and mortality in CKD. Magnetic resonance imaging (MRI) is considered an accurate method for the study of body composition. A water/fat separated MRI scan with automated image analysis can quantify the skeletal muscle volume and allows a quantitative measure of muscle quality by assessing muscle fat infiltration. The combined observation of low muscle volume and high muscle fat infiltration, i.e. adverse muscle composition (AMC), has been shown to be linked to poor function and metabolic comorbidities within subjects with non-alcoholic fatty liver disease. The aim of this study was to investigate the prevalence of AMC and its association with poorer muscle function and metabolic comorbidity within CKD in the large UK Biobank imaging study.

Method
This is a cross-sectional and prospective study including a total of 647 UK Biobank participants with eGFR cystatin C &lt; 60 ml/min/1,73 m2. A control group was created by selecting participants (matched on sex, age, and BMI) with an eGFR cystatin ≥ 60 ml/min/1,73 m2. Fat-tissue free muscle volume and muscle fat infiltration (MFI) were quantified using a rapid whole-body water and fat separated MRI protocol and automated image analysis (AMRA® Researcher). For each participant, a personalized muscle volume z-score (sex- and body size-specific) was calculated and combined with muscle fat infiltration for AMC detection. AMC was defined as having low muscle volume in combination with high muscle fat infiltration. Sarcopenia was calculated according to the last published recommendation by the European Working Group on Sarcopenia in Older People. Data describing muscle function (hand strength, walking test, stair climbing and number of falls) and metabolic comorbidity (coronary heart disease (CHD) and type 2 diabetes (T2D) have been included and obtained from the study database linked to the study participants' electronic health records. A Cox proportional hazards ratio model, corrected for age, sex, BMI, low hand grip strength, T2D, smoking, and alcohol consumption, was used to assess the association between AMC and CHD incidence.

Results
• The prevalence of AMC was 1,4x higher in CKD participants compared with the control group without CKD (27.7% vs 20.4%, p&lt;0.001). CKD participants had significantly higher prevalence of sarcopenia (7.2% vs 4.4%, p = 0.004), low hand grip strength (16.0% vs 11.8%, p = 0.006), slow walking pace (17.3% vs 9.9%, p &lt;0.001), CHD (17.4% vs 8.9%, p &lt;0.001) and T2D (13.7% vs 9.2%, p = 0.001) compared with the control group without CKD (Fig. 1). • CKD participants with AMC (179 out of 647) had a significantly higher prevalence of sarcopenia (17.3% vs 3.5%, p&lt;0.001), low hand grip strength (22.8% vs 13.4%, p = 0.006), slow walking pace (27.0% vs 13.6%, p &lt;0.001), as well as prevalence of CHD (23.6% vs 15.0%, p = 0.014) and T2D (18.6% vs 11.8%, p = 0.033) compared with CKD participants without AMC (Fig. 2). • CKD participants with prevalent CHD at the study had higher prevalence of AMC (37.5% vs 25.5%, p = 0.014) compared to CKD participants without CHD. • AMC was associated with 1.9x higher incidence of CHD (95% confidence interval 1.15–3.15, p = 0.012) compared to those without AMC.

Conclusion
AMC, as determined by MRI with automated image segmentation, is highly prevalent within CKD and associates with poor function, high prevalence of metabolic comorbidities and an increased risk for CHD. CKD patients with poor muscle health is a highly vulnerable group and this technique enables them to be targeted for accurate interventions in order to improve outcomes.