[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"leadSponsorName\":\"Eko Devices, Inc.\",\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:":169},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,7,0,[8,40,64,87,110,130,148],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":4,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":28,"lastUpdatePostDateStruct":29,"startDateStruct":32,"completionDateStruct":34,"leadSponsor":36,"locationsCount":39},"100599678","deep-learning-detection-of-pulmonary-hypertension-and-low-ejection-fraction-via-digital-stethoscope-and-3-lead-ecg-100599678",false,"NCT07087613","Deep Learning Detection of Pulmonary Hypertension and Low Ejection Fraction Via Digital Stethoscope and 3-Lead ECG","Deep Learning for Detection of Pulmonary Hypertension and Reduced Left Ventricular Ejection Fraction Using a Combined Digital Stethoscope and Three-lead Electrocardiogram","PH ELEFT 2-0","Inclusion Criteria:\n\n* Adults aged 18 years and older\n* Able and willing to provide informed consent\n* Completed a clinical echocardiogram or right heart catheterization within 7 days before or after study procedures\n\nExclusion Criteria:\n\n* Unwilling or unable to provide informed consent\n* Patients who are hospitalized\n* Patients undergoing echocardiography with a limited echocardiogram (does not apply to patients undergoing right heart catheterization)","ALL","18 Years",{"count":20,"type":21},3850,"ESTIMATED","OBSERVATIONAL","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.\n\nIn this study, adults undergoing clinically indicated echocardiograms or right heart catheterization 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 or right heart catheterization, those data may also be used for analysis. A clinically indicated echocardiogram or right heart catheterization (RHC) performed 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.\n\nUp 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.",[25,26],"Hypertension, Pulmonary","Heart Failure With Reduced Ejection Fraction","RECRUITING","2026-06-16",{"date":30,"type":31},"2026-06-18","ACTUAL",{"date":33,"type":31},"2025-06-15",{"date":35,"type":21},"2027-05-31",{"name":37,"class":38},"Eko Devices, Inc.","INDUSTRY",4,{"id":41,"slug":42,"hasResults":11,"nctId":43,"briefTitle":44,"officialTitle":45,"acronym":46,"eligibilityCriteria":47,"healthyVolunteers":48,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":49,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":51,"conditions":52,"keywords":54,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":56,"lastUpdatePostDateStruct":57,"startDateStruct":59,"completionDateStruct":61,"leadSponsor":62,"locationsCount":63},"100603446","detecting-pulmonary-hypertension-with-the-eko-core-500-digital-stethoscope-100603446","NCT07136623","Detecting Pulmonary Hypertension With the Eko CORE 500 Digital Stethoscope","Deep Learning for Algorithmic Detection of Pulmonary Hypertension Using a Combined Digital Stethoscope and Three-lead Electrocardiogram","EKO-PH","Inclusion Criteria:\n\nAge ≥ 18 years.\n\nAble and willing to provide informed consent.\n\nClinically indicated transthoracic echocardiogram (TTE) or right heart catheterization (RHC) scheduled\u002Fperformed within ±7 days of the study recording visit.\n\nExclusion Criteria:\n\nUnwilling or unable to provide informed consent.\n\nCurrently hospitalized at the time of study procedures.\n\nIf enrolled via TTE path: limited (non-diagnostic) echocardiogram.",true,{"count":50,"type":21},1513,"This prospective, observational study will evaluate whether synchronized heart sound (phonocardiogram, PCG) and three-lead electrocardiogram (ECG) recordings (entered as separate interventions in PRS, though collected together in practice) collected with the Eko CORE 500 can help screen for pulmonary hypertension (PH). Adults (≥18 years) undergoing clinically indicated transthoracic echocardiography (TTE) and\u002For right heart catheterization (RHC) will complete one study visit (\\~20 minutes). During the visit, study staff will obtain at least four 15-second CORE 500 recordings (aortic, pulmonic, tricuspid, and mitral areas). The clinical echocardiogram (and RHC, if performed) within ±7 days of the recordings will provide reference labels for the presence and severity of PH; de-identified demographic and clinical data may also be abstracted from the medical record.\n\nThe primary objective is to develop and validate a software algorithm to detect PH and, where possible, stratify severity using noninvasive PCG+ECG signals. These recordings are investigational data acquisitions for algorithm development only; they are not diagnostic procedures and will not be used for clinical decision-making. Primary performance measures are sensitivity and specificity versus echocardiogram and RHC references. No clinical decisions will be based on the investigational algorithm, and no changes to standard care are required. The study plans to enroll up to \\~1,513 participants to obtain approximately 1,375 evaluable datasets across multiple outpatient sites.",[53],"Pulmnary Hypertension",[55],"pulmonary hypertension","2026-06-15",{"date":58,"type":31},"2026-06-17",{"date":60,"type":31},"2025-08-01",{"date":35,"type":21},{"name":37,"class":38},2,{"id":65,"slug":66,"hasResults":11,"nctId":67,"briefTitle":68,"officialTitle":69,"acronym":4,"eligibilityCriteria":70,"healthyVolunteers":48,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":71,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":73,"conditions":74,"keywords":76,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":56,"lastUpdatePostDateStruct":81,"startDateStruct":82,"completionDateStruct":84,"leadSponsor":85,"locationsCount":86},"100506361","development-of-an-algorithm-to-detect-pulmonary-hypertension-using-an-electronic-stethoscope-100506361","NCT05873387","Development of an Algorithm to Detect Pulmonary Hypertension Using an Electronic Stethoscope","Deep Learning for Algorithmic Detection of Pulmonary Hypertension Using a Combined Digital Stethoscope and Single-lead Electrocardiogram","Inclusion Criteria:\n\n* Patients, ages \\>18 years, referred for complete 2-dimensional echocardiography or right heart catheterization will be screened for inclusion.\n\nExclusion Criteria:\n\n* Patients undergoing limited echocardiography\n* Intubated patients",{"count":72,"type":21},2420,"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.",[75],"Pulmonary Hypertension",[77,78,79,80],"digital stethoscopes","deep learning","auscultation","electrocardiogram",{"date":58,"type":31},{"date":83,"type":31},"2023-07-12",{"date":35,"type":21},{"name":37,"class":38},3,{"id":88,"slug":89,"hasResults":11,"nctId":90,"briefTitle":91,"officialTitle":91,"acronym":4,"eligibilityCriteria":92,"healthyVolunteers":11,"sex":17,"minAge":4,"maxAge":4,"enrollmentInfo":93,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":95,"conditions":96,"keywords":98,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":102,"lastUpdatePostDateStruct":103,"startDateStruct":105,"completionDateStruct":107,"leadSponsor":109,"locationsCount":63},"100610422","data-collection-using-eko-digital-devices-in-a-clinical-setting-100610422","NCT07227376","Data Collection Using Eko Digital Devices in a Clinical Setting","Inclusion Criteria:\n\n* Suspected or diagnosed lower respiratory condition OR Presence of wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough discovered during routine auscultation\n* Normal patients with no adventitious lung sounds\n* Adults and pediatric patients (as available)\n\nExclusion Criteria:\n\n* Unable to have multiple recordings taken on chest and back (e.g. compromised mobility)\n* On mechanical ventilation",{"count":94,"type":21},250,"The purpose of this research is to prospectively train and validate an artificial intelligence machine learning (ML) algorithm to detect the presence of adventitious lung sounds in adults. Clinicians will use the Eko CORE and\u002For Eko CORE 500 device(s) in real clinical settings to collect normal and abnormal lung sounds, as part of standard of care clinical practice, which will then be used to explore an ML algorithm for classifiers for wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough, as well as determine any correspondences between the type and\u002For location of adventitious lung sounds and the type of pulmonary conditions as reported by clinicians.",[97],"Lung Diseases",[99,100,101],"lung sounds","adventitious lung sounds","abnormal lung sounds","2026-05-21",{"date":104,"type":31},"2026-05-26",{"date":106,"type":31},"2025-09-14",{"date":108,"type":21},"2027-11-30",{"name":37,"class":38},{"id":111,"slug":112,"hasResults":11,"nctId":113,"briefTitle":114,"officialTitle":91,"acronym":4,"eligibilityCriteria":115,"healthyVolunteers":48,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":116,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":118,"conditions":119,"keywords":120,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":121,"lastUpdatePostDateStruct":122,"startDateStruct":124,"completionDateStruct":126,"leadSponsor":128,"locationsCount":129},"100613757","data-collection-using-eko-devices-in-a-clinical-setting-100613757","NCT07270744","Data Collection Using Eko Devices in a Clinical Setting","Inclusion Criteria:\n\n* Patients suspected or diagnosed lower respiratory condition OR Presence of wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough discovered during routine auscultation\n* Normal patients with no adventitious lung sounds\n* Adults patients, over 18 years old\n* Able to provide verbal consent\n\nExclusion Criteria:\n\n* Patients unable to have multiple recordings taken on chest and back (e.g. compromised mobility)\n* Patients on mechanical ventilation\n* Patients unwilling or unable to provide informed consent",{"count":117,"type":21},200,"The main objectives of the study are to: train and validate binary classifiers for wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough, as well as determine correspondence between type\u002Flocation of adventitious lung sound and type of pulmonary condition.",[97],[99,100,101],"2025-12-10",{"date":123,"type":31},"2025-12-18",{"date":125,"type":31},"2025-10-01",{"date":127,"type":21},"2026-12-31",{"name":37,"class":38},1,{"id":131,"slug":132,"hasResults":11,"nctId":133,"briefTitle":134,"officialTitle":134,"acronym":4,"eligibilityCriteria":135,"healthyVolunteers":48,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":136,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":138,"conditions":139,"keywords":141,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":121,"lastUpdatePostDateStruct":143,"startDateStruct":144,"completionDateStruct":145,"leadSponsor":147,"locationsCount":129},"100613753","detection-of-reduced-left-ventricular-ejection-fraction-with-three-lead-ecg-using-artificial-intelligence-100613753","NCT07270692","Detection of Reduced Left Ventricular Ejection Fraction With Three-Lead ECG Using Artificial Intelligence","Inclusion Criteria:\n\n* Adults aged 18 years and older\n* Able and willing to provide informed consent\n* Complete a clinical echocardiogram within 7 days before or after study procedures\n\nExclusion Criteria:\n\n* Unwilling or unable to provide informed consent\n* Patients who are hospitalized",{"count":137,"type":21},500,"The main objectives of this study are to train and evaluate an algorithm that predicts whether an individual has an ejection fraction ≤ 40%, using heart sounds and a 3-lead ECG as inputs, as well as determine the impact of gender, age, and race on algorithm performance.",[140],"Low Ejection Fraction",[142],"low ejection fraction",{"date":123,"type":31},{"date":60,"type":31},{"date":146,"type":21},"2026-11-01",{"name":37,"class":38},{"id":149,"slug":150,"hasResults":11,"nctId":151,"briefTitle":152,"officialTitle":152,"acronym":4,"eligibilityCriteria":153,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":154,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":156,"conditions":157,"keywords":159,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":162,"lastUpdatePostDateStruct":163,"startDateStruct":164,"completionDateStruct":166,"leadSponsor":168,"locationsCount":129},"100608480","improvement-of-an-algorithm-to-detect-structural-heart-murmurs-in-adult-patients-using-electronic-stethoscopes-100608480","NCT07202104","Improvement of an Algorithm to Detect Structural Heart Murmurs in Adult Patients Using Electronic Stethoscopes","Inclusion Criteria:\n\n* 18+ years old\n* Patient or patient's legal healthcare proxy consents to participation\n* Documented history of SHD\n* Undergoing (or has undergone, within 30 days) a complete echocardiogram\n* Willing to have heart recordings done with two different electronic stethoscopes\n\nExclusion Criteria:\n\n* Patient or proxy is unwilling\u002Funable to give written informed consent\n* Unable to complete a complete echocardiogram, or none recent completed within the last 30 days\n* No documented history of SHD\n* Experiencing a known or suspected acute cardiac event\n* Mechanical ventricular support (such as ECMO, LVAD, RVAD, BiVAD, Impella, intra-aortic balloon pumps, TAH, VentrAssist, DuraHeart, HVAD, EVAHEART LVAS, HeartMate, Jarvik 2000)\n* Unwilling or unable to follow or complete study procedures",{"count":155,"type":21},125,"The main objective of this study is to evaluate a machine learning model's ability to detect murmurs indicative of structural heart disease (\"structural murmur\") by analyzing phonocardiogram waveforms-and simultaneous electrocardiogram waveforms when available-in multiple auscultatory positions per subject. Diagnosis of structural murmur will be confirmed by gold-standard echocardiography and reviewed by an expert panel of cardiologists.",[158],"Structural Heart Disease",[160,161],"structural heart disease","structural murmur","2025-09-23",{"date":125,"type":31},{"date":165,"type":21},"2025-09",{"date":167,"type":21},"2026-05",{"name":37,"class":38},""]