[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT05992324":3,"trial-entities:NCT05992324":118,"trial-summary:NCT05992324":122},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":6,"overall_status":7,"completion_date":8,"status_verified_date":9,"last_update_date":10,"start_date":11,"sponsor_name":12,"lead_sponsor_class":13,"has_dmc":14,"brief_summary":15,"detailed_description":16,"conditions":17,"keywords":19,"study_type":23,"primary_purpose":24,"phases":25,"enrollment_info":27,"interventions":30,"primary_outcomes":37,"secondary_outcomes":51,"sex":55,"minimum_age":56,"maximum_age":57,"healthy_volunteers":14,"eligibility_criteria":58,"std_ages":65,"locations":68,"central_contacts":106,"overall_officials":111,"references":112,"see_also_links":117},"NCT05992324","LungPivotal","A Validation Study to Evaluate the Performance of Caption Health Lung Guidance and Interpretation","RECRUITING","2025-03-01","2024-11","2024-11-26","2023-07-17","Caption Health, Inc.","INDUSTRY",false,"The purpose of this study is to assess the efficacy of Caption LungAI.","After being informed about the study, all patients giving written informed consent will undergo two 8-zone protocol lung ultrasound exams. One exam will be conducted by an expert lung ultrasound user without Caption LungAI and one exam conducted by a (non-expert) healthcare provider who is trained on Caption LungAI and will use Caption LungAI to capture images.",[18],"Shortness of Breath",[20,21,22],"Lung Ultrasound","B-Lines","POCUS by non-expert user","INTERVENTIONAL","DIAGNOSTIC",[26],"NA",{"count":28,"type":29},220,"ESTIMATED",[31],{"type":32,"name":33,"description":34,"armGroupLabels":35},"DEVICE","Caption LungAI","Caption LungAI is a software that is designed to help non-expert healthcare professionals acquire diagnostic quality images on an 8-zone lung protocol for both healthy patients and patients presenting with pathology such as B-Lines.",[36],"Patients presenting with clinical suspicion of B-Lines",[38,42,45,48],{"measure":39,"description":40,"timeFrame":41},"Diagnostic Image Quality (Trained Healthcare Professional)","Evaluate the product's ability to assist the user to capture a LUS image with diagnostic quality. Percentage of zones with diagnostic image quality \\> 0.80","Up to 24 weeks from completion of the study.",{"measure":43,"description":44,"timeFrame":41},"B-Lines Detection","Evaluate the product's ability to retrospectively detect present B-lines on images acquired by a local expert with no Caption Lung AI assistance. AUROC \\> 0.80; Sensitivity (Se) \\> 0.80; Specificity (Sp) \\> 0.75",{"measure":46,"description":47,"timeFrame":41},"B-Line Significance","Evaluate the product's ability to retrospectively detect B-lines of significant severity on images acquired by a local expert with no Caption Lung AI assistance. AUROC \\> 0.80; Sensitivity (Se) \\> 0.80; Specificity (Sp) \\> 0.75",{"measure":49,"description":50,"timeFrame":41},"Remote Reader Performance","Evaluate the product's impact on a remote expert reader's ability to interpret LUS images. Difference Between Aided \\&\n\nUnaided Groups:\n\nAUROC \\> 0.00; Sensitivity (Se) \\> 0.00; Specificity (Sp) \\> 0.00",[52],{"measure":53,"description":54,"timeFrame":41},"Sub-group Analyses","The following sub-group analyses will be performed for the primary endpoints: age (\\\u003C 65, ≥ 65), BMI group (\\\u003C 25, 25 ≤ BMI \\\u003C 30, ≥ 30), gender (Male \u002F Female), site location, trained HCP, and zone of the image (1 - 8).","ALL","18 Years",null,{"inclusion":59,"exclusion":62,"raw_text":64},[60,61],"Patients over the age of 18","Patients presenting to the hospital or outpatient setting with shortness of breath and suspected B-lines.",[63],"Patients in extremis\u002Fin whom a research lung ultrasound would not normally be performed due to other priorities","Inclusion Criteria:\n\n* Patients over the age of 18\n* Patients presenting to the hospital or outpatient setting with shortness of breath and suspected B-lines.\n\nExclusion Criteria:\n\n* Patients in extremis\u002Fin whom a research lung ultrasound would not normally be performed due to other priorities",[66,67],"ADULT","OLDER_ADULT",[69,85,94,98],{"facility":70,"status":7,"city":71,"state":72,"zip":73,"country":74,"contacts":75,"geoPoint":82},"Yale New Haven Hospital","New Haven","Connecticut","06510","United States",[76,80],{"name":77,"role":78,"email":79},"Ryan Denkewicz","CONTACT","ryan.denkewicz@yale.edu",{"name":81,"role":78},"Chris Moore, MD",{"lat":83,"lon":84},41.30815,-72.92816,{"facility":86,"status":87,"city":88,"state":89,"zip":90,"country":74,"geoPoint":91},"Northwestern University","COMPLETED","Chicago","Illinois","60611",{"lat":92,"lon":93},41.85003,-87.65005,{"facility":95,"status":87,"city":88,"state":89,"zip":96,"country":74,"geoPoint":97},"Rush University Medical Center","60612",{"lat":92,"lon":93},{"facility":99,"status":87,"city":100,"state":101,"zip":102,"country":74,"geoPoint":103},"The Moses H. Cone Memorial Hospital","Greensboro","North Carolina","27401",{"lat":104,"lon":105},36.07264,-79.79198,[107],{"name":108,"role":78,"phone":109,"email":110},"Angeline Trinidad","619-322-0727","angeline.trinidad@gehealthcare.com",[],[113],{"pmid":114,"type":115,"citation":116},"39813064","DERIVED","Baloescu C, Bailitz J, Cheema B, Agarwala R, Jankowski M, Eke O, Liu R, Nomura J, Stolz L, Gargani L, Alkan E, Wellman T, Parajuli N, Marra A, Thomas Y, Patel D, Schraft E, O'Brien J, Moore CL, Gottlieb M. Artificial Intelligence-Guided Lung Ultrasound by Nonexperts. JAMA Cardiol. 2025 Mar 1;10(3):245-253. doi: 10.1001\u002Fjamacardio.2024.4991.",[],{"nct_id":4,"conditions":119,"biomarkers":121},[120],"Dyspnea",[],{"nct_id":4,"found":123,"summary":124,"prompt_version":134},true,{"design":125,"status":126,"heading":127,"summary":128,"follow_up":129,"word_count":130,"commitments":131,"compensation":132,"drugs_mentioned":133},"This interventional study plans to enroll 220 participants. It compares lung ultrasounds performed by an expert with those done by a non-expert using Caption LungAI.","completed","Caption LungAI for Shortness of Breath","This study is testing a software called Caption LungAI. This software helps healthcare professionals who are not ultrasound experts to take high-quality lung ultrasound images. The study wants to see if Caption LungAI can help detect B-lines (a sign of fluid in the lungs) in people experiencing shortness of breath. You might be able to join if you are over 18, have shortness of breath, and your doctors suspect you have B-lines. The study is looking for 220 participants, but its current recruitment status is unclear.","Your diagnostic image quality and B-line detection will be measured for up to 24 weeks after completing the study.",86,"You would undergo two lung ultrasound exams. One exam will be done by an expert, and the other by a healthcare provider using Caption LungAI.","Not stated in the trial record.",[33],"v2"]