Open AccessModeling Low Muscle Mass Screening in Hemodialysis Patients
Author(s) -
Daiki Senzaki,
Nobutaka Yoshioka,
Osamu Nagakawa,
Emi Inayama,
Takafumi Nakagawa,
Hidehito Takayama,
Toko Endo,
Fumitaka Nakajima,
Masayoshi Fukui,
Yasuaki Kijima,
Yasuo Oyama,
Risshi Kudo,
Tadashi Toyama,
Yoshiaki Yamada,
Kiyoshi Tsurusaki,
Naoki Aoyama,
T Matsumura,
Hideki Yamahara,
Kenro Miyasato,
Tatsuya Kitamura,
Tatsuyoshi Ikenoue
Publication year - 2022
Publication title -
the nephron journals/nephron journals
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.951
H-Index - 72
eISSN - 2235-3186
pISSN - 1660-8151
DOI - 10.1159/000526866
Subject(s) - medicine , sarcopenia , hemodialysis , dialysis , logistic regression , body mass index , kidney disease , area under the curve , nephrology , stepwise regression , urology
Computed tomography (CT) can accurately measure muscle mass, which is necessary for diagnosing sarcopenia, even in dialysis patients. However, CT-based screening for such patients is challenging, especially considering the availability of equipment within dialysis facilities. We therefore aimed to develop a bedside prediction model for low muscle mass, defined by the psoas muscle mass index (PMI) from CT measurement.