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1.
Diagnostics (Basel) ; 12(3)2022 Mar 20.
Article in English | MEDLINE | ID: mdl-35328308

ABSTRACT

Background: Polycystic kidney disease (PKD) is an inherited disorder characterized by renal cysts that may mask lean body loss. This study quantified and compared muscle mass by using computed tomography (CT) and magnetic resonance imaging (MRI) images between the PKD and control groups and correlated muscle mass with total kidney volume (TKV). Methods: We retrospectively enrolled patients who had a new diagnosis of PKD from May 2015 to May 2016. The CT and MRI images at the third lumbar level were processed to measure the total abdominal muscle (TAM) area for the diagnosis of sarcopenia, and TKV was estimated using the ellipsoid formula. Results: We included 37 women and 25 men (mean age: 50.40 years) in the PKD group. There was no difference in body mass index and albumin levels, but significant differences in creatinine level (p < 0.001), TAM area (p = 0.047), and TKV (p < 0.001), were noted between the two groups. A significantly negative correlation was observed between TKV and TAM area after adjustment for body height (r = −0.217, p = 0.003). Conclusions: CT and MRI images can accurately diagnose sarcopenia, which may be masked by cysts in patients with PKD.

2.
Clin Nutr ; 38(2): 862-869, 2019 04.
Article in English | MEDLINE | ID: mdl-29503056

ABSTRACT

BACKGROUND & AIMS: Sarcopenia and cachexia are associated with pancreatic cancer and serve as important adverse prognostic factors. Body composition can be analyzed by routine computed tomography (CT) for cancer staging and has been used to study many types of cancer. The CT measurements are robust, but the diagnostic criteria for sarcopenia vary among different studies. Age, sex and race are important factors that affect muscle and fat masses. This study aimed to analyze the effect of different sarcopenia diagnostic criteria on the prognosis of patients with pancreatic cancer. METHODS: Patients with newly diagnosed pancreatic cancer at National Taiwan University Hospital between October 2013 and October 2016 were retrospectively reviewed in this study. Body composition was assessed using cross-sectional CT images to calculate the total skeletal muscle (TSM) index. The concordance and interobserver variability of the TSM measurements were evaluated using both the Western criteria and the Eastern criteria. Kaplan-Meier analyses and the Cox proportional hazard ratio with two different diagnostic criteria for sarcopenia were used to compare the effect on overall survival (OS). RESULTS: A total of 146 patients with pancreatic cancer were enrolled. The TSM index measured by the Western institute was highly correlated with that measured by the Eastern institute (r = 0.953, p < 0.001). The prevalence of sarcopenia in the patient group at baseline was 66.4% (97/146) by the Western criteria and 11.0% (16/146) by the Eastern criteria, and only low agreement was found between the Western and Eastern criteria (Kappa value = 0.028, p = 0.149). Patients who were sarcopenic by the Western criteria showed no significant difference in OS versus those who were not sarcopenic (p = 0.807). However, patients who were sarcopenic by the Eastern criteria showed a significant difference in OS versus those who were not sarcopenic in a univariate analysis (p = 0.008) and multivariate analysis after adjustment for AJCC stage (p = 0.014). CONCLUSIONS: Our study demonstrates that different diagnostic criteria may result in different diagnoses and that sarcopenia is an important poor prognostic factor for pancreatic cancer when appropriate diagnostic criteria are selected.


Subject(s)
Pancreatic Neoplasms , Sarcopenia , Adult , Aged , Aged, 80 and over , Female , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Muscle, Skeletal/diagnostic imaging , Pancreatic Neoplasms/complications , Pancreatic Neoplasms/diagnosis , Pancreatic Neoplasms/mortality , Prognosis , Retrospective Studies , Sarcopenia/complications , Sarcopenia/diagnostic imaging , Sarcopenia/epidemiology , Taiwan , Tomography, X-Ray Computed
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