Seung Bae Yoon1, Moon Hyung Choi2, In Seok Lee1, Chul-Hyun Lim3, Jin Soo Kim3, Yu Kyung Cho3, Jae Myung Park1, Bo-In Lee3, Young-Seok Cho3, Myung-Gyu Choi4. 1. Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea; Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul, South Korea. 2. Department of Radiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea; Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul, South Korea. 3. Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea. 4. Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea. Electronic address: choim@catholic.ac.kr.
Abstract
BACKGROUND/ OBJECTIVES: Obesity is a well-established risk factor for severe acute pancreatitis (AP); however, the impact of visceral obesity or sarcopenic obesity on severity of AP has not been well studied. We compared the relationship between severity of AP and various body parameters including body weight, body mass index (BMI), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and visceral fat-to-muscle ratio (VMR). METHODS: We analyzed the data of patients who were diagnosed with AP from 2009 to 2015. Image analysis software program (Aquarius Workstation software) was used to calculate individual VAT, SAT, and skeletal muscle areas from abdominal computed tomography scans at L3 vertebral levels. Revised Atlanta Classification was adopted to define severity of AP. Receiver operating characteristics (ROC) curves were constructed to determine the optimal threshold for predicting the severity. RESULTS: Among 203 patients, 13 (6.4%) patients had severe AP and 62 (30.5%) patients had moderately severe cases. VMR demonstrated the highest area under the ROC curve [0.757, (95% confidence interval: 0.689-0.825)] in predicting moderately severe or severe AP. The optimal threshold of VMR for predicting severity was 1. The prevalence of various local complications and persistent organ failure were higher in patients with VMR over 1. CONCLUSIONS: High visceral fat with low skeletal muscle volume was strongly correlated with AP severity. VMR had a stronger correlation with AP severity than body weight or BMI. This simple grading system would be useful if incorporated into future predictive scoring models.
BACKGROUND/ OBJECTIVES: Obesity is a well-established risk factor for severe acute pancreatitis (AP); however, the impact of visceral obesity or sarcopenic obesity on severity of AP has not been well studied. We compared the relationship between severity of AP and various body parameters including body weight, body mass index (BMI), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and visceral fat-to-muscle ratio (VMR). METHODS: We analyzed the data of patients who were diagnosed with AP from 2009 to 2015. Image analysis software program (Aquarius Workstation software) was used to calculate individual VAT, SAT, and skeletal muscle areas from abdominal computed tomography scans at L3 vertebral levels. Revised Atlanta Classification was adopted to define severity of AP. Receiver operating characteristics (ROC) curves were constructed to determine the optimal threshold for predicting the severity. RESULTS: Among 203 patients, 13 (6.4%) patients had severe AP and 62 (30.5%) patients had moderately severe cases. VMR demonstrated the highest area under the ROC curve [0.757, (95% confidence interval: 0.689-0.825)] in predicting moderately severe or severe AP. The optimal threshold of VMR for predicting severity was 1. The prevalence of various local complications and persistent organ failure were higher in patients with VMR over 1. CONCLUSIONS: High visceral fat with low skeletal muscle volume was strongly correlated with AP severity. VMR had a stronger correlation with AP severity than body weight or BMI. This simple grading system would be useful if incorporated into future predictive scoring models.
Authors: Andre E Modesto; Charlotte E Stuart; Jaelim Cho; Juyeon Ko; Ruma G Singh; Maxim S Petrov Journal: Eur Radiol Date: 2020-02-10 Impact factor: 5.315
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