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Critical appraisal and narrative review of the literature in IVF/ICSI patients with adenomyosis and endometriosis
被引:0
|作者:
Mercan, Ramazan
[1
]
Benlioglu, Can
[1
]
Aksakal, Gulumser Ece
[2
]
机构:
[1] Koc Univ, Sch Med, Dept Obstet & Gynecol, Istanbul, Turkiye
[2] Amer Hosp, Dept Obstet & Gynecol, Istanbul, Turkiye
来源:
FRONTIERS IN REPRODUCTIVE HEALTH
|
2024年
/
6卷
关键词:
endometriosis;
<italic>in vitro</italic> fertilization;
coexisting endometriosis and adenomyosis;
Ultralong GnRH suppression;
frozen embryo transfer;
UTERINE ADENOMYOSIS;
OUTCOMES;
WOMEN;
FERTILITY;
PATHOPHYSIOLOGY;
IMPLANTATION;
ASSOCIATION;
INFERTILITY;
PREVALENCE;
IMPACT;
D O I:
10.3389/frph.2024.1525705
中图分类号:
R1 [预防医学、卫生学];
学科分类号:
1004 ;
120402 ;
摘要:
Endometriosis and adenomyosis are prevalent causes of infertility, often coexisting in a significant proportion of patients. Although endometriosis typically does not negatively impact assisted reproductive technology (ART) outcomes, the presence of coexisting adenomyosis, mainly non-severe external forms, may slightly influence IVF/ICSI success rates. However, this impact is often minimal and may result in insignificant changes in statistical analyses. Recent studies underscore the critical role of accurate diagnostic techniques, such as ultrasound or MRI, in identifying severe adenomyosis characteristics, including diffuse involvement with junctional zone participation. This precise delineation is reassuring, as it is essential for tailoring assisted reproductive technology (ART) strategies to enhance success rates and reduce the confounding effects of adenomyosis, particularly when it coexists with endometriosis. Strategic approaches, such as ultralong GnRH agonist protocols or freeze-all strategies, may provide advantages in these scenarios. However, the need for extensive research is vital to understanding the complex interactions between endometriosis, adenomyosis, and ART outcomes. This ongoing exploration is particularly important in cases where coexisting adenomyosis might not significantly influence statistical results.
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