Usefulness of the Geriatric Nutritional Risk Index to predict the severity of cholecystitis among older patients in the emergency department

2020 ◽  
Vol 20 (5) ◽  
pp. 455-460
Author(s):  
Jong Seok Lee ◽  
Ki Young Jeong ◽  
Seok Hoon Ko
Nutrients ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2659 ◽  
Author(s):  
Takahiro Yajima ◽  
Kumiko Yajima ◽  
Hiroshi Takahashi ◽  
Keigo Yasuda

The ratio of extracellular fluid (ECF) to intracellular fluid (ICF) may be associated with mortality in patients undergoing hemodialysis, possibly associated with protein-energy wasting. We therefore investigated the relationship of the ECF/ICF ratio and the geriatric nutritional risk index (GNRI) with the all-cause and cardiovascular-specific mortality in 234 patients undergoing hemodialysis. Bioimpedance analysis of the ECF and ICF was performed and the ECF/ICF ratio was independently associated with GNRI (β = −0.247, p < 0.0001). During a median follow-up of 2.8 years, 72 patients died, of which 29 were cardiovascular. All-cause mortality was independently associated with a lower GNRI (adjusted hazard ratio [aHR] 3.48, 95% confidence interval [CI] 2.01–6.25) and a higher ECF/ICF ratio (aHR 11.38, 95%CI 5.29–27.89). Next, we divided patients into four groups: group 1 (G1), higher GNRI and lower ECF/ICF ratio; G2, lower GNRI and lower ECF/ICF ratio; G3, higher GNRI and higher ECF/ICF ratio; and G4, lower GNRI and higher ECF/ICF ratio. Analysis of these groups revealed 10-year survival rates of 91.2%, 67.2%, 0%, and 0% in G1, G2, G3, and G4, respectively. The aHR for G4 versus G1 was 43.4 (95%CI 12.2–279.8). Adding the GNRI alone, the ECF/ICF ratio alone, or both to the established risk model improved the net reclassification improvement by 0.444, 0.793 and 0.920, respectively. Similar results were obtained for cardiovascular mortality. In conclusion, the ECF/ICF ratio was independently associated with GNRI and could predict mortality in patients undergoing hemodialysis. Combining the GNRI and ECF/ICF ratio could improve mortality predictions.


2021 ◽  
Vol 323 ◽  
pp. 30-36
Author(s):  
Shoji Tsuneyoshi ◽  
Yuta Matsukuma ◽  
Yasuhiro Kawai ◽  
Hiroto Hiyamuta ◽  
Shunsuke Yamada ◽  
...  

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