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
Jaewoo Song (Department of Laboratory Medicine Severance Hospital Yonsei University College of Medicine Seoul)
저널정보
대한혈액학회 Blood Research Blood Research Vol.57
발행연도
2022.4
수록면
93 - 100 (8page)
DOI
10.5045/br.2022.2022048

이용수

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

초록· 키워드

오류제보하기
Technologies in laboratory diagnostics are changing fast with progress in understanding and therapy of diseases. Unfortunately, new analyzers are often needed to be installed in a clinical laboratory to implement such techniques. The demand for new hardware is a bottleneck in improving the diagnostic services for many facilities with limited resources. In this regard, hemostasis laboratories take a slightly different position. Because many in vitro diagnostic tests target the functional aspects of hemostasis, further meaningful information can be obtained from the same analyzers as in current use. Automated coagulometers are good candidates for such further utilization. Clot waveform analysis is a leading example. Behind the simple values reported as clotting time, clotting curves exist that represent the process of fibrin clot formation. Clot waveform analysis examines the clotting curves and derives new parameters other than clotting times. The clot waveform parameters are now in active use in assessing the hemostatic potential of hemorrhagic patients. Clinical application of coagulometers can also be widened by modifying the reagent formulation. For example, the chromogenic factor VIII assay with bovine source reagent compositions has recently been introduced for hemophilia A patients on emicizumab prophylaxis. Also, new immunoturbidimetric functional assays for von Willebrand factor have been developed recently. Thus, new clinically relevant information can be mined from the automated coagulometers that are based on old technology.

목차

등록된 정보가 없습니다.

참고문헌 (0)

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