Abstract 9974: Effect of Graves’ Disease on Female Probability Derived from Artificial Intelligence-Enabled Electrocardiograms in Women

Abstract

Introduction: Graves’ disease (GD) is known to cause menstrual changes and has been linked to infertility in women. This can be due to the increased production of androstenedione and testosterone induced by the excess thyroid hormone. However, screening for sex hormone levels in all women diagnosed with GD to identify patients more likely to have infertility is not cost-effective and not clinically indicated. AI-augmented ECG can identify the signature of female with an AUC of 0.97. In this model, AI- ECG gives a probability number between 0-100% of being female, with higher numbers indicating high probability of being female. Hypothesis: We hypothesized that this inexpensive AI ECG tool is reflective of hormonal levels and the resulting changes in menstrual cycle and fertility associated with GD in women. Methods: Patients diagnosed with GD (2009-2019) at our institution were included. Three intervals were identified: 1) Before GD: >2 months before GD diagnosis 2) During GD: within 2 months before GD and before attaining euthyroidism 3) After GD: after attaining euthyroidism. The matched-pairs t-test was used to compare probability of being a female; patients acted as their own controls. A subset analysis was done on females <45 years at GD diagnosis to study the association between female probability during GD and menstrual changes (defined as shorter, lighter, or newly irregular menstrual cycles). Results: 154 females with ECGs both before and during GD were identified. AI ECG female probability decreased with GD diagnosis (85% vs. 77%, P<.001). On the other hand, 137 females with GD had ECGs during and after GD. Female probability increased after attaining euthyroidism (76% vs 83%, P=.005). Moreover, 72 females <45 years were identified; 30 (42%) developed menstrual changes and had significantly lower AI-ECG female probability [77 (58-94)% vs 98 (92-100)%, P<.001] Conclusions: AI-enabled ECG signature of female gender in women was altered by GD and was associated with menstrual changes, likely reflecting changes in sex hormone levels. Future studies to confirm its role in screening for infertility in women with GD are needed.