Nomogram for predicting pregnancy-related relapse of myasthenia gravis

Myasthenia gravis (MG) is an autoimmune disease mediated by autoantibodies primarily affecting the neuromuscular junction. This study aims to identify risk factors for pregnancy-related MG relapse and develop a predictive model to improve clinical outcomes.

We enrolled 113 MG female patients with a pregnancy history during follow-up at Huashan Hospital affiliated with Fudan University, between January 2015 and October 2021. The study analyzed relapse rates and risk factors during pregnancy and postpartum using multivariate logistic regression. A nomogram was constructed to predict relapse probability, with model performance evaluated by discrimination and calibration metrics.

Of the 113 patients, 52 (46.02%) experienced 115 relapses, including 52 (45.22%) occurring during the first trimester of pregnancy, 11 (9.56%) during the second trimester of pregnancy, and 52 relapses (45.22%) during the three months after delivery/abortion. Significant factors associated with pregnancy-relate relapse, included age at delivery/abortion (OR 0.21, 95% CI 0.06–0.65), MG stable duration (OR 0.24, 95% CI 0.09–0.63), thymic hyperplasia (OR 3.45, 95% CI 1.35–9.3), pre-pregnancy thymectomy (OR 0.08, 95% CI 0.01–0.36), and inadequate treatment during pregnancy (OR 4.44, 95% CI 1.35–17.76). The Nomogram model demonstrated robust predictive performance.

The first trimester of pregnancy and three months following delivery or abortion are high-risk periods for MG relapse. Younger ages, shorter MG stable duration before pregnancy, thymic hyperplasia, and inadequate treatments during pregnancy increase relapse risk.