Acute mesenteric thrombosis in a pregnant woman with Factor V Leiden mutation with a history of in vitro fertilization and embryo transfer: case report and literature review

OBJECTIVES: To report the case of a patient diagnosed with acute mesenteric vein thrombosis (AMVT) associated with Factor V Leiden mutation and a history of embryo transfer (IVF-ET) and review the literature on risk factors and treatments performed for AMVT. MATERIALS AND METHODS: A 37-year-old pregnant woman with a 7-week pregnancy achieved by IVF-ET was treated in a high complexity hospital because of acute abdominal pain and pregnancy loss. A necrotic small bowel resection was performed and a secundary thrombus in the superior mesenteric vein (SMV) and pulmonary embolism was diagnosed on the first posoperatory day, which were treated medically with satisfactory evolution. A bibliographic search was carried out in Medline/PubMed and LILACS, filtering by type of language (English and Spanish). Primary cohort studies, cases and controls, case reports and case series were included, which addressed the risk factors associated with the development of acute mesenteric thrombosis during pregnancy and treatments performed. RESULTS: The search identified cases and control studies, case reports and case series related to mesenteric ischemia, pregnancy and embryo transfer (IVF-ET). The literature reported that the main factors associated with mesenteric ischemia are pregnancy itself, genetic factors, drugs, protein C and protein S deficiency and idiopathic causes. Surgical treatment was applied to 14 of 17 patients. CONCLUSIONS: SMV thrombosis is a life-threatening and very rarely seen condition that emerges in pregnancies. The literature suggests that, during gestation, the factors associated with the development of acute mesenteric thrombosis are hypercoagulability induced by pregnancy, the administration of oral estrogen during IVF-ET, and other precipitating factors. More studies are required to better understand the possible additional factors and build better optimal treatment algorithms.