Search clinical trials by condition, location and status
This is a prospective, observational study evaluating whether heart sounds (phonocardiograms) and three-lead electrocardiograms (ECGs) recorded using the Eko CORE 500 digital stethoscope can help detect pulmonary hypertension (PH) and low left ventricular ejection fraction (EF ≤ 40%). PH is a condition characterized by high blood pressure in the pulmonary arteries, which can lead to heart failure and carries significant risks if undiagnosed. Low EF, which indicates reduced pumping ability of the heart, is also associated with increased risk of severe cardiac events but can remain undetected because patients often have no symptoms or only nonspecific symptoms. In this study, adults undergoing clinically indicated echocardiograms at outpatient sites will be invited to participate. Participants will complete a single study session lasting about 20 minutes, during which heart sounds and a three-lead ECG will be collected using the Eko CORE 500 device. If participants have had a clinical 12-lead ECG within 30 days of their echocardiogram, those data may also be used for analysis. The echocardiogram performed as part of routine care within seven days before or after the Eko CORE 500 recording will serve as the reference standard to confirm the presence or absence of PH and low EF. Up to 3,850 participants may be enrolled across multiple sites to ensure that approximately 3,500 complete the study. The data collected will be used to develop and validate artificial intelligence (AI) algorithms that aim to detect PH and identify low EF, potentially enabling earlier and simpler screening for these conditions in clinical practice.
The goal of this clinical trial is to evaluate whether an AI tool that alerts providers to patients at high 6-year risk of lung cancer based on their chest x-ray images will improve lung cancer screening CT participation. The main question it aims to answer is: Does the AI tool improve lung cancer screening CT participation at 6 months after the baseline outpatient visit The intervention is an alert to the provider to discuss lung cancer screening CT eligibility, for patients considered at high risk of lung cancer based on CXR-LC AI tool. If there is a comparison group: Researchers will compare intervention and non-intervention arms to determine if lung cancer screen CT participation increases.
Hypothesis: BR's Gen3 DL algorithms, combined with its subxiphoid body sensor, can accurately diagnose OSA, categorize its severity, identify REM OSA and supine OSA, and detect central sleep apnea (CSA). Primary Objective: To rigorously evaluate the overall performance of the BR with Gen3 DL Algorithms and Subxiphoid Body Sensor in assessing SDB in individuals referred to the sleep labs with clinical suspicion of sleep apnea and a STOP-Bang score \> 3, by comparing to the attended in-lab PSG, the gold standard. Secondary Objectives: To determine the accuracy of BR sleep stage parameters using the Gen3 DL algorithms by comparing to the in-lab PSG; To assess the accuracy of the BR arrhythmia detection algorithm; To assess the impact of CPAP on HRV (both time- and frequency-domain), delta HR, hypoxic burden, and PWADI during split night studies; To assess if any of the baseline HRV parameters (both time- and frequency-domain), delta heart rate (referred to as Delta HR), hypoxic burden, and pulse wave amplitude drop index (PWADI) or the change of these parameters may predict CPAP compliance; To evaluate the minimum duration of quality data necessary for BR to achieve OSA diagnosis; To examine the performance of OSA screening tools using OSA predictive AI models formulated by National Taiwan University Hospital (NTUH) and Northeast Ohio Medical University (NEOMED).
This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.
This multicenter prospective study aims to evaluate the correlation between quantitative ultrasound fat fraction (USFF) and MRI-PDFF (Proton Density Fat Fraction) for liver fat quantification in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). The study will compare the diagnostic accuracy of quantitative ultrasound imaging against MRI-PDFF as the reference standard.
This is a single center, diagnostic clinical trial in which the investigators aim to prospectively validate a deep learning model that identifies patients with features suggestive of cardiac amyloidosis, including transthyretin cardiac amyloidosis (ATTR-CA). Cardiac Amyloidosis is an age-related infiltrative cardiomyopathy that causes heart failure and death that is frequently unrecognized and underdiagnosed. The investigators have developed a deep learning model that identifies patients with features of ATTR-CA and other types of cardiac amyloidosis using echocardiographic, ECG, and clinical factors. By applying this model to the population served by NewYork-Presbyterian Hospital, the investigators will identify a list of patients at highest predicted risk for having undiagnosed cardiac amyloidosis. The investigators will then invite these patients for further testing to diagnose cardiac amyloidosis. The rate of cardiac amyloidosis diagnosis of patients in this study will be compared to rate of cardiac amyloidosis diagnosis in historic controls from the following two groups: (1) patients referred for clinical cardiac amyloidosis testing at NewYork-Prebysterian Hospital and (2) patients enrolled in the Screening for Cardiac Amyloidosis With Nuclear Imaging in Minority Populations (SCAN-MP) study.
Balance problems and falls are among the most common complaints in Veterans with Parkinson's Disease (PD), but there are no effective treatments and the ability to measure balance and falls remains quite poor. This study uses wearable sensors to measure balance and uses deep brain stimulation electrodes to measure electric signals from the brain in Veterans with PD. The investigators hope to use this data to better understand the brain pathways underlying balance problems in PD so that new treatments to improve balance and reduce falls in Veterans with PD can be designed.
The main purpose of this study is to assess the usability and value of the multiple sclerosis (MS) care management platform in terms of improved monitoring of people with MS (pwMS) in clinical practice. This is a two-year prospective data collection study with additional data collection at baseline evaluating medical practice over a period of at least one year before the introduction of the MS care management platform.
The major goal of the study is to determine whether phonocardiography (using the Eko DUO stethoscope which can capture a three lead ECG reading) can present features that relate to the presence of PH diagnosed by echocardiography or right heart catheterization (RHC), and therefore have a potential to assist the provider to suspect PH.
Background: The genes a person is born with can sometimes cause serious diseases. Genetic diseases are rare, but they can have a big impact on the people they affect. Researchers have already made great strides in understanding how some genes cause disease. But they would like to have even better tools to analyze and understand genetic data. To create these new tools, they need to gather health and genetic data from a lot of people. Objective: This natural history study will gather medical information from people with genetic conditions. Eligibility: People of any age who (1) are known or suspected to have a genetic condition or (2) have a family member with a known or suspected genetic condition. Design: Participants will come to the clinic for up to 4 days. Tests to be performed will vary depending on the nature of each participant s health issue. The tests may include: Blood and saliva. Blood may be drawn from a vein; cells and saliva may be collected by rubbing the inside of the cheek with a swab. These would be used for genetic testing. Imaging scans. Participants may have X-rays or other scans of their bodies. They may lie still on a table while a machine records the images. Heart tests. Participants may lie still while a technician places a probe on their chest. They may also have stickers attached to wires placed on their chest. Photographs and recordings. Pictures may be taken of facial features, skin changes, or other effects of the genetic condition. Video and audio recordings may also be made. Some people may be able to participate via telehealth.