Multi-site Study of the Clinical Impact of an AI-assisted Approach to Referring Patients With Interstitial Lung Disease for Diagnostic Evaluation of Pulmonary Hypertension

The goal of this study is to evaluate the use of an ECG-based AI device that may help predict if participants with interstitial lung disease (ILD) are at high risk of undiagnosed pulmonary hypertension (PH). The study seeks to determine whether use of the device increases the rate of new PH diagnoses over a period of 6 months as compared to current standard of care. The study will recruit participants with ILD from lung disease clinics who will each receive a 12-lead ECG (a test that measures the electrical activity of the heart) following consent. The device will analyze the 12-lead ECG results to identify participants that are at high risk of having undiagnosed PH. Participants will be randomly assigned to either the Device or Control group. For participants in the Device group investigators will receive the results of the device. In the Control group investigators will not receive the results of the device. Additionally, participants in the Device group identified as "high risk" by the device will receive a transthoracic echocardiogram and a right heart catheterization (RHC). Participants in the Device group who are not high risk and all participants in the Control group will not receive these additional tests as part of the study, but will receive standard of care treatment as determined by their physicians, which may include an echocardiogram or RHC if clinically indicated.