Artificial Intelligence Evaluation of Electrocardiographic Characteristics and Interval Changes in Transgender Patients on Gender-Affirming Hormone Therapy

Background

Gender-affirming hormone therapy (GAHT) is used by some transgender individuals (TG), who comprise 1.4% of US population. However, the effects of GAHT on ECG remain unknown.

Objective

To assess the effects of GAHT on ECG changes in TG.

Methods

Twelve-lead ECGs of TG on GAHT at the Mayo Clinic were inspected using a validated artificial intelligence algorithm. The algorithm assigns a patient’s ECG male pattern probability on a scale of 0 (female) to 1 (male). In the primary analysis, done separately for transgender women (TGW) and transgender men (TGM), 12-lead ECGs were used to estimate the male pattern probability before and after GAHT. In a subanalysis, only patients with both pre- & post-GAHT EGCs were included. Further, the autopopulated PR, QRS and QTc intervals were compared before and after GAHT.

Results

Among TGW (n=86), the probability (mean ±SD) of an ECG male pattern was 0.84 ±0.25 in the pre-GAHT group, and it was lowered to 0.59 ±0.36 in the post-GAHT group (n=173, p < 7 .8 x 10-10). Conversely, among TGM, male pattern probability was 0.16 ±0.28 (n =47) in the pre-GAHT group, and it was higher at 0.41±0.38 in the post-GAHT group (n=53, p<2.4 X 10-4). The trend persisted in the subanalysis. Furthermore, both the PR (p = 5.68x10-4) and QTc intervals (p= 6.65 x10-6) prolonged among TGW. Among TGM, the QTc interval shortened (p= 4.8x10-2).

Conclusion

Among TG, GAHT is associated with ECG changes trending towards gender congruence, as determined by the AI algorithm and ECG intervals. Prospective studies are warranted to understand GAHT effects on cardiac structure and function.

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