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
송은곤 (서울대학교) 김경수 (서울대학교병원)
저널정보
대한응급의학회 대한응급의학회지 대한응급의학회지 제31권 제5호
발행연도
2020.1
수록면
511 - 517 (7page)

이용수

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

초록· 키워드

오류제보하기
Objective: This study examined the effects of the new law on life-sustaining treatment (LST) in emergency patients with advanced malignancy. Methods: This was a retrospective before-after study performed at a single hospital. The enrollment criteria were as follows: patients who visited the emergency department during the study period, age ≥18 years, Korean Triage and Acuity Scale 1-2 to enroll severely ill patients requiring LST, solid malignancy with metastasis, and admitted to the study hospital. The after group was defined as those enrolled in May 2018, and the before group was defined as those enrolled in May 2017. The primary outcomes were defined as LST, including intensive care unit (ICU) admission, renal replacement therapy, mechanical ventilation, and cardiopulmonary resuscitation. Secondary outcomes were defined as each component of the primary outcomes, hospital length of stay, cost, and mortality. Results: Ninety-seven patients were enrolled (before group [n=46], after group [n=51]). LST was provided more frequently in the after group (19.6% vs. 47.1%, P=0.004). The ICU admission rate was higher (19.6% vs. 43.1%, P=0.013), and mechanical ventilation was applied more frequently (6.5% vs. 21.6%, P=0.044) in the after group. Furthermore, the median hospital length of stay (six-day vs. 11-day, P=0.016) was longer, and the median hospital cost was higher (3,777 USD vs. 7,882 USD, P<0.001) in the after group. Hospital mortality did not differ (19.6% vs. 35.3%, P=0.084). Conclusion: New end-of-life care law increased the rate of LST in emergency patients with advanced malignancy regardless of the improved survival rate.

목차

등록된 정보가 없습니다.

참고문헌 (13)

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