Ignite Creation Date:
2025-12-25 @ 2:52 AM
Ignite Modification Date:
2025-12-31 @ 9:24 PM
Study NCT ID:
NCT06646133
Status:
WITHDRAWN
Last Update Posted:
2025-12-19
First Post:
2024-10-15
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001835', 'term': 'Body Weight'}], 'ancestors': [{'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'CASE_CROSSOVER'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 0}, 'patientRegistry': False}, 'statusModule': {'whyStopped': 'No funding received.', 'overallStatus': 'WITHDRAWN', 'startDateStruct': {'date': '2027-07-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2028-02-28', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-15', 'studyFirstSubmitDate': '2024-10-15', 'studyFirstSubmitQcDate': '2024-10-16', 'lastUpdatePostDateStruct': {'date': '2025-12-19', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2024-10-17', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2028-02-28', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Weight estimation accuracy', 'timeFrame': 'During the simulation (intervention) procedure', 'description': 'The accuracy of estimations of total body weight, ideal body weight and lean body weight will be compared against ground truth data, and against other weight estimation systems.'}, {'measure': 'Weight estimation time', 'timeFrame': 'During the simulation (intervention) procedure', 'description': 'The time taken to obtain a weight estimate will be compared against other weight estimation systems.'}, {'measure': 'Drug dose accuracy', 'timeFrame': 'During the simulation (intervention) procedure', 'description': 'The accuracy of drug doses calculated using estimated weight will be compared against a ground truth value, and compared with other weight estimation systems.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['weight estimation', 'emergency drug dosing', '3D camera', 'computer vision'], 'conditions': ['Body Weights and Measures', 'Body Weight in the Overweight and Obese Class - I Population', 'Weight Estimation', 'Emergency Drug Dosing']}, 'referencesModule': {'references': [{'pmid': '36190388', 'type': 'BACKGROUND', 'citation': 'Wells M, Goldstein L. Appropriate Statistical Analysis and Data Reporting for Weight Estimation Studies. Pediatr Emerg Care. 2023 Jan 1;39(1):62-63. doi: 10.1097/PEC.0000000000002862. Epub 2022 Oct 1. No abstract available.'}, {'pmid': '36123560', 'type': 'BACKGROUND', 'citation': 'Wells M, Goldstein LN, Cattermole G. Development and Validation of a Length- and Habitus-Based Method of Ideal and Lean Body Weight Estimation for Adults Requiring Urgent Weight-Based Medical Intervention. Eur J Drug Metab Pharmacokinet. 2022 Nov;47(6):841-853. doi: 10.1007/s13318-022-00796-3. Epub 2022 Sep 19.'}, {'pmid': '36277563', 'type': 'BACKGROUND', 'citation': 'Wells M, Goldstein LN. Estimating Lean Body Weight in Adults With the PAWPER XL-MAC Tape Using Actual Measured Weight as an Input Variable. Cureus. 2022 Sep 17;14(9):e29278. doi: 10.7759/cureus.29278. eCollection 2022 Sep.'}, {'pmid': '37439214', 'type': 'BACKGROUND', 'citation': 'Wells M, Henry B, Goldstein L. Weight Estimation for Drug Dose Calculations in the Prehospital Setting - A Systematic Review. Prehosp Disaster Med. 2023 Aug;38(4):471-484. doi: 10.1017/S1049023X23006027. Epub 2023 Jul 13.'}, {'pmid': '38056057', 'type': 'BACKGROUND', 'citation': 'Wells M, Goldstein LN, Alter SM, Solano JJ, Engstrom G, Shih RD. The accuracy of total body weight estimation in adults - A systematic review and meta-analysis. Am J Emerg Med. 2024 Feb;76:123-135. doi: 10.1016/j.ajem.2023.11.037. Epub 2023 Nov 29.'}, {'pmid': '39371964', 'type': 'BACKGROUND', 'citation': 'Wells M, Goldstein LN, Wells T, Ghazi N, Pandya A, Furht B, Engstrom G, Jan MT, Shih R. Total body weight estimation by 3D camera systems: Potential high-tech solutions for emergency medicine applications? A scoping review. J Am Coll Emerg Physicians Open. 2024 Oct 4;5(5):e13320. doi: 10.1002/emp2.13320. eCollection 2024 Oct.'}]}, 'descriptionModule': {'briefSummary': 'The goal of this prospective crossover simulation study is to evaluate the accuracy and usability of a 3D camera weight estimation system during simulated emergency care in adult simulated patients, when used by emergency physicians. The main questions the study aims to answer are:\n\n* to evaluate the accuracy of 3D camera weight estimation during simulated emergency care, when compared with standard methods\n* to evaluate the usability of 3D camera weight estimation during emergency care, when compared with standard methods\n* to evaluate the inter-user reliability of 3D camera weight estimates Volunteers for simulated patients will be required to have anthropometric measurements, a DXA scan, and 3D camera weight estimates.\n\nPhysician volunteers will need to participate in simulated emergency scenarios during which weight-based therapy must be administered.\n\nThere will be no interventions.', 'detailedDescription': 'The performance of the 3D camera system needs to be evaluated in conditions in which it will be used in a clinical setting, but without the risk to patients. It also needs to be compared against other, standard, methods of weight estimation. In addition the downstream accuracy of drug doses, with the correct use of alternative dose scalars (such as ideal body weight or lean body weight) in patients with obesity needs to be evaluated.\n\nIn this prospective crossover simulation study, resident and attending emergency physician volunteers will conduct simulated emergency care on simulated patient volunteers. The physicians will be randomised to start with either 3D camera systems, or standard care systems. After completing the scenario they will perform a new simulation scenario on a different patient using standard methods of weight estimation (crossover). At the end of the data collection session, each physician will have performed four scenarios (two standard methods, two 3D camera methods). Each simulated patient will similarly have participated in two standard method scenarios and two 3D camera scenarios. Each simulated patient and each physician will only have a single encounter.\n\nIn this way the accuracy of weight estimation and drug dosing can be compared between the 3D camera system and standard methods. In addition, inter-rater reliability can be determined and compared between resident and attending physicians.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Simulated patients will be enrolled from students, staff and faculty at the Boca Raton campus of Florida Atlantic university.\n\nEmergency physician participants will be enrolled from resident and attending emergency physicians in south Florida.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria for simulated patients:\n\n* Any volunteer aged ≥18 years.\n\nExclusion Criteria for simulated patients:\n\n* Participants with a body weight exceeding the DXA machine capacity \\>204kg (450lbs);\n* Pregnant participants; participants with medical conditions that could confound the study;\n* Participants with any metallic surgical implants;\n* Participants who have had an x-ray with contrast in the past week;\n* Participants who have taken calcium supplements in the 24 hours prior to the study.\n\nInclusion criteria for Emergency Physicians:\n\n\\- Any willing emergency medicine resident or attending physician.\n\nExclusion criteria for Emergency Physicians:\n\n\\- Any physical limitation to performing anthropometric measurements as part of simulation scenario.'}, 'identificationModule': {'nctId': 'NCT06646133', 'briefTitle': 'Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2', 'organization': {'class': 'OTHER', 'fullName': 'Florida Atlantic University'}, 'officialTitle': 'Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2 - Measure the Accuracy and Speed of Weight Estimations Using a 3D Camera System During Simulated Medical Emergencies', 'orgStudyIdInfo': {'id': '1791994(2)'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Standard care weight estimation', 'description': 'Simulated patients in whom standard methods of weight estimation will be used.', 'interventionNames': ['Diagnostic Test: Standard methods of weight estimation']}, {'label': '3D camera weight estimation', 'description': 'Simulated patients in whom 3D camera estimates of weight will be used.', 'interventionNames': ['Diagnostic Test: 3D camera weight estimate']}], 'interventions': [{'name': '3D camera weight estimate', 'type': 'DIAGNOSTIC_TEST', 'description': 'Weight estimation using 3D camera system', 'armGroupLabels': ['3D camera weight estimation']}, {'name': 'Standard methods of weight estimation', 'type': 'DIAGNOSTIC_TEST', 'description': 'Standard methods of weight estimation will be used', 'armGroupLabels': ['Standard care weight estimation']}]}, 'contactsLocationsModule': {'locations': [{'zip': '33143', 'city': 'Boca Raton', 'state': 'Florida', 'country': 'United States', 'facility': 'Florida Atlantic University', 'geoPoint': {'lat': 26.35869, 'lon': -80.0831}}]}, 'ipdSharingStatementModule': {'infoTypes': ['STUDY_PROTOCOL'], 'timeFrame': 'Within 6 months after the completion of the study.', 'ipdSharing': 'YES', 'description': 'The data will be made available on request.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Florida Atlantic University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}