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
윤시현 (Department of Plastic and Reconstructive Surgery Sanggye Paik Hospital Inje University College of) 김영준 (인제대학교부속상계백병원) 최영웅 (Department of Plastic and Reconstructive Surgery Inje University Sanggye Paik Hospital Inje Univer)
저널정보
대한미용성형외과학회 Archives of Aesthetic Plastic Surgery Archives of Aesthetic Plastic Surgery Vol.28 No.1
발행연도
2022.1
수록면
31 - 35 (5page)

이용수

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

초록· 키워드

오류제보하기
Background The annual incidence of skin cancer has been increasing, and surgical ablation is presently the treatment of choice for skin cancer. However, it leaves soft tissue defects that require reconstruction. The methods for reconstruction include locoregional flaps (LRFs) and full-thickness skin grafts (FTSGs). We compared these two surgical methods for reconstruction of defects in the nose, which is prominently visible and the most common site of facial skin cancer, and assessed the cosmetic results by evaluating the scars. Methods This retrospective study was conducted between July 2012 and January 2021. Patients were evaluated for scars after at least 6 months of follow-up. Patients were divided into LRF and FTSG groups. The scars were evaluated using the Vancouver Scar Scale. Results In total, 27 patients were included in this study. Their mean age was 66.8 years. Eighteen patients underwent LRF, and nine patients underwent FTSG. The average defect size was 1.55 cm² in the LRF group, and 1.38 cm² in the FTSG group. The average scar score was 1.44 points in the LRF group and 3.67 points in the FTSG group. The LRF group showed significantly lower total scores than the FTSG group. Conclusions Although LRFs and FTSGs are useful reconstructive methods for nasal soft tissue defects, this study showed that LRFs are superior to FTSGs in terms of aesthetic results.

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