메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
저널정보
한국임상영양학회 Clinical Nutrition Research Clinical Nutrition Research Vol.4 No.1
발행연도
2015.1
수록면
32 - 40 (9page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Malnutrition is common in the critically ill patients and known to cause a variety of negative clinical outcomes. However, various conventional methods for nutrition assessment have several limitations. We hypothesized that body composition data, as measured using bioelectrical impedance analysis (BIA), may have a significant role in evaluating nutritional status and predicting clinical outcomes in critically ill patients. We gathered clinical, biochemical, and BIA data from 66 critically ill patients admitted to an intensive care unit. Patients were divided into three nutritional status groups according to their serum albumin level and total lymphocyte counts. The BIA results, conventional indicators of nutrition status, and clinical outcomes were compared and analyzed retrospectively. Results showed that the BIA indices including phase angle (PhA), extracellular water (ECW), and ECW/ total body water (TBW) were significantly associated with the severity of nutritional status. Particularly, PhA, an indicator of the health of the cell membrane, was higher in the well-nourished patient group, whereas the edema index (ECW/TBW) was higher in the severely malnourished patient group. PhA was positively associated with albumin and ECW/TBW was negatively associated with serum albumin, hemoglobin, and duration of mechanical ventilation. In non-survivors, PhA was significantly lower and both ECW/TBW and %TBW/fat free mass were higher than in survivors. In conclusion, several BIA indexes including PhA and ECW/ TBW may be useful for nutritional assessment and represent significant prognostic factors in the care of critically ill patients.

목차

등록된 정보가 없습니다.

참고문헌 (34)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0