Kiyonori Ito1, Susumu Ookawara2, Sojiro Imai3, Hideo Kakuda4, Yusaku Bandai3, Mariko Fueki3, Masatoshi Yasuda3, Tatsuya Kamimura3, Satoshi Kiryu3, Noriko Wada3, Yuri Hamashima5, Mitsutoshi Shindo1, Tadanao Kobayashi6, Hidenori Sanayama7, Yoshio Kaku1, Keisuke Tanno8, Yasushi Ohnishi6, Noriaki Iino9, Katsuya Dezaki10, Masafumi Kakei6, Kaoru Tabei6, Yoshiyuki Morishita1. 1. Division of Nephrology, Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan. 2. Division of Nephrology, Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan. Electronic address: su-ooka@hb.tp1.jp. 3. Department of Dialysis, Minami-Uonuma City Hospital, Niigata, Japan. 4. Department of Radiology, Minami-Uonuma City Hospital, Niigata, Japan. 5. Department of Population Health Science, Bristol Medical School, University of Bristol, England, UK. 6. Department of Internal Medicine, Minami-Uonuma City Hospital, Niigata, Japan. 7. Division of Neurology, Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan. 8. Division of Radiology, Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan. 9. Division of Nephrology, Uonuma Institute of Community Medicine, Niigata University Medical and Dental Hospital, Niigata, Japan. 10. Division of Integrative Physiology, Department of Physiology, Jichi Medical University, Tochigi, Japan; Department of Pharmacy, Iryo Sosei University, Fukushima, Japan.
Abstract
BACKGROUND AND AIMS: The use of the psoas muscle mass index (PMI) using computed tomography (CT) has become a marker of interest to evaluate whole body muscle mass. However, in hemodialysis (HD) patients, reports about the clinical significance of psoas muscle evaluation are limited. We aimed to clarify the association between PMI and skeletal muscle mass index (SMI) using bioelectrical impedance analysis (BIA), and to investigate factors affecting PMI in HD patients. METHODS: In this prospective observational study, to evaluate muscle mass, SMI was measured using BIA after HD, and PMI was measured by the manual trace method on routinely available CT scans. PMI measurement was assessed twice by two physicians to compute intra-rater and inter-rater reliability. The correlations between PMI and the clinical factors were evaluated using Pearson's correlation coefficient and a linear regression analysis. Variables with a p-value < 0.05 in the simple linear regression analysis were included in the multivariable linear regression analysis to identify the factors that affected PMI of the HD patients. RESULTS: Fifty HD patients were recruited (31 males and 19 females; HD duration, 9.0 ± 8.8 years). The SMI was 6.10 ± 1.20 kg/m2, and the PMI was 4.79 ± 1.61 cm2/m2. Regarding the reliability of PMI measurements, intra-rater reliability [intra-class correlation (ICC) = 0.999] and inter-rater reliability (ICC = 0.998) were high in this study. The mean PMI of male patients was 5.40 ± 1.62 cm2/m2, while that of female patients was significantly lower (3.78 ± 0.98 cm2/m2; p < 0.001). The PMI was significantly and positively correlated with SMI (r = 0.630, p < 0.001), in addition to HD duration, body mass index (BMI), serum phosphate and serum creatinine (Cr). In the multivariate linear regression analysis by two models using SMI or BMI, they were respectively extracted as an independent factor associating with PMI, in addition to serum Cr and the difference of sex. CONCLUSIONS: PMI assessed with CT positively correlated with SMI measured using BIA. PMI might be one of the methods for evaluating the muscle mass in HD patients, when CT scans are taken as part of routine care.
BACKGROUND AND AIMS: The use of the psoas muscle mass index (PMI) using computed tomography (CT) has become a marker of interest to evaluate whole body muscle mass. However, in hemodialysis (HD) patients, reports about the clinical significance of psoas muscle evaluation are limited. We aimed to clarify the association between PMI and skeletal muscle mass index (SMI) using bioelectrical impedance analysis (BIA), and to investigate factors affecting PMI in HDpatients. METHODS: In this prospective observational study, to evaluate muscle mass, SMI was measured using BIA after HD, and PMI was measured by the manual trace method on routinely available CT scans. PMI measurement was assessed twice by two physicians to compute intra-rater and inter-rater reliability. The correlations between PMI and the clinical factors were evaluated using Pearson's correlation coefficient and a linear regression analysis. Variables with a p-value < 0.05 in the simple linear regression analysis were included in the multivariable linear regression analysis to identify the factors that affected PMI of the HDpatients. RESULTS: Fifty HDpatients were recruited (31 males and 19 females; HD duration, 9.0 ± 8.8 years). The SMI was 6.10 ± 1.20 kg/m2, and the PMI was 4.79 ± 1.61 cm2/m2. Regarding the reliability of PMI measurements, intra-rater reliability [intra-class correlation (ICC) = 0.999] and inter-rater reliability (ICC = 0.998) were high in this study. The mean PMI of male patients was 5.40 ± 1.62 cm2/m2, while that of female patients was significantly lower (3.78 ± 0.98 cm2/m2; p < 0.001). The PMI was significantly and positively correlated with SMI (r = 0.630, p < 0.001), in addition to HD duration, body mass index (BMI), serum phosphate and serum creatinine (Cr). In the multivariate linear regression analysis by two models using SMI or BMI, they were respectively extracted as an independent factor associating with PMI, in addition to serum Cr and the difference of sex. CONCLUSIONS: PMI assessed with CT positively correlated with SMI measured using BIA. PMI might be one of the methods for evaluating the muscle mass in HDpatients, when CT scans are taken as part of routine care.