인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Background This study aims to identify factors influencing the outcomes of frozen embryo transfer (FET) cycles. Methods A prospective observational study was conducted between July 2020 to December 2021 on 170 participants who underwent 190 FET cycles of autologous embryos after endometrial preparation with hormone therapy. Patient characteristics, ovarian stimulation details, and embryo specifics were recorded. Endometrial thickness, morphology, and Doppler flow were assessed on the day of progesterone start. Embryo details on the transfer day were also recorded. Serum ß-hCG levels were measured twelve days post-transfer, and those with levels > 25 IU/L underwent a 6-week ultrasound to detect a gestational sac. The clinical pregnancy rate (CPR) was calculated, and statistical differences between pregnant and non-pregnant groups were evaluated using Chi-square or Fisher’s exact tests for categorical variables and the Mann–Whitney U-test for continuous variables due to non-normal distribution. Logistic regression analysis was used to identify independent variables associated with successful pregnancy outcomes. Results For a total of 190 cycles, the CPR was 35.7%. Univariate logistic regression revealed that antral follicle count (AFC), Anti-Müllerian hormone (AMH), blastocyst transfer, embryo quality, blastocyst quality and transferring more than one embryo (double or triple) were significantly associated with CPR. On multivariate analysis, embryo quality remained the only independent predictor of successful FET outcomes. Conclusion Embryo quality is the strongest predictor of FET success, with significant effects seen for good-quality embryos, blastocyst transfers, and the number of embryos transferred. Age and ovarian reserve also influenced outcomes. Endometrial factors showed only trends, warranting further investigation. Tailored treatment approaches are crucial for optimising IVF success.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.