인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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 Cerebral cavernous malformations (CCMs) are vascular anomalies that may pose unique challenges during pregnancy due to potential hormonal and hemodynamic influences on lesion behavior, including risks of growth or hemorrhage. Management strategies must balance maternal neurological safety with fetal well-being, yet evidence-based guidelines remain limited. Methods A systematic review was conducted following PRISMA guidelines. Databases (PubMed, Embase, Scopus, Web of Science) were searched from inception to July 2025 using terms such as “cerebral cavernous malformation,” “cavernoma,” “pregnancy,” “management.” Inclusion criteria encompassed English-language studies reporting CCMs in pregnant women. Data extraction focused on epidemiology, hemorrhage risk, management (conservative, microsurgical, radiosurgical), and outcomes. Risk of bias was assessed using Newcastle-Ottawa and Joanna Briggs Institute tools. A case illustration exemplifies clinical decision-making. Results Of 1256 records, 45 studies (512 pregnancies, 478 women) were included. Hemorrhage risk was 1.1–3.6% per pregnancy, comparable to non-pregnant rates (0.7–1.1% annually), with brainstem lesions showing higher risk. Conservative management was used in 68%, microsurgery (second trimester) in 22%, and stereotactic radiosurgery (SRS) in 10%, often postpartum. Maternal mortality was 0.8%, with 92% favorable fetal outcomes. Conclusions Pregnancy does not significantly elevate CCM hemorrhage risk, supporting conservative management for asymptomatic lesions. Second-trimester microsurgery is safe for progressive cases; postpartum SRS suits inaccessible lesions. Multidisciplinary approaches optimize outcomes.
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.
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