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Published on: August 2, 2017
Pregnancy planning may impact maternal and neonatal outcomes in people with myasthenia gravis
Saja Anabusi1,2, Aaron Izenberg3, Carolina Barnett4
1Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Accessible Care Pregnancy Clinic, Sunnybrook Health Sciences Centre, Toronto, Canada.
Introduction:
Myasthenia Gravis (MG) is an acquired autoimmune condition commonly diagnosed in young people of reproductive age resulting in neuromuscular junction dysfunction. The course of MG during pregnancy and its impact on maternal and neonatal outcomes is vary in the literature. Pregnancy planning is a known strategy and modifiable risk factor in obstetric practice to decrease maternal and neonatal morbidity. We aim to assess if planning a pregnancy impacts maternal and neonatal outcomes, MG exacerbation, and pregnancy-related complications.
Methods:
This study utilized data from an online, North American survey entitled "A Patient Centered study on Pregnancy in People with Myasthenia Gravis", distributed with the assistance of MG advocacy groups in the United States and Canada. It included individuals with MG who had at least one pregnancy in the last 10-years. Key maternal and neonatal outcomes were compared between planned and unplanned pregnancies.
Results:
Out of 156 survey participants, 58 had a pregnancy following MG diagnosis, totaling 90 reported pregnancies. Of these, 56 (62.2%) were planned and 34 (37.8%) were unplanned pregnancies. The unplanned pregnancies were associated with more MG exacerbations, hospitalizations, and intensive care unit admission (37.7% vs. 13.7%, 26.5% vs. 11%, and 17.6% vs. 8.9%, respectively, p ≤ .05). The neonatal outcomes did not significantly differ between the groups.
Discussion:
Planned pregnancies in people with MG may be associated with a reduced gestational and post-partum risk of MG exacerbation, hospitalizations, and ICU admissions. Larger studies are required to confirm this association and account for potential contributing variables.
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