Ignite Creation Date:
2025-12-25 @ 3:48 AM
Ignite Modification Date:
2026-01-28 @ 5:32 PM
Study NCT ID:
NCT03175302
Status:
RECRUITING
Last Update Posted:
2025-07-31
First Post:
2017-06-01
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
PREsurgical Cognitive Evaluation Via Digital clockfacEdrawing
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D060825', 'term': 'Cognitive Dysfunction'}], 'ancestors': [{'id': 'D003072', 'term': 'Cognition Disorders'}, {'id': 'D019965', 'term': 'Neurocognitive Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'OTHER', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 25240}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2018-06-28', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-07', 'completionDateStruct': {'date': '2027-05-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-07-28', 'studyFirstSubmitDate': '2017-06-01', 'studyFirstSubmitQcDate': '2017-06-01', 'lastUpdatePostDateStruct': {'date': '2025-07-31', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2017-06-05', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-05-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Control and pre-surgery differences between digital behaviors', 'timeFrame': 'up to one year', 'description': 'Measure range of digital outcome differences'}], 'secondaryOutcomes': [{'measure': 'Predictive validity of digital behaviors on outcome', 'timeFrame': 'up to 1 year', 'description': 'Digital tools will predict clinician reported events'}, {'measure': 'Change over time in digital behavior between groups', 'timeFrame': 'up to 6-weeks', 'description': 'Surgery group and control group differences from baseline to 6-weeks'}, {'measure': 'Change over time in digital behavior between groups', 'timeFrame': 'up to 3-months', 'description': 'Surgery group and control group differences from baseline to 3-months'}, {'measure': 'Change over time in digital behavior between groups', 'timeFrame': 'up to one year', 'description': 'Surgery group and control group differences from baseline to one year'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['cognitive processes', 'perioperative cognition', 'neurocognitive impairment'], 'conditions': ['Cognitive Dysfunction']}, 'referencesModule': {'references': [{'pmid': '37149670', 'type': 'DERIVED', 'citation': 'Bandyopadhyay S, Wittmayer J, Libon DJ, Tighe P, Price C, Rashidi P. Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands. Sci Rep. 2023 May 6;13(1):7384. doi: 10.1038/s41598-023-34518-9.'}, {'pmid': '35568709', 'type': 'DERIVED', 'citation': 'Bandyopadhyay S, Dion C, Libon DJ, Price C, Tighe P, Rashidi P. Variational autoencoder provides proof of concept that compressing CDT to extremely low-dimensional space retains its ability of distinguishing dementia. Sci Rep. 2022 May 14;12(1):7992. doi: 10.1038/s41598-022-12024-8.'}]}, 'descriptionModule': {'briefSummary': 'This study leverages a modernized digital version of a well-known cognitive screening tool to examine pre and post operative cognitive function after surgery in adults age 65 years or more. Machine learning algorithms will be applied to the hospital wide standard of care cognitive metric to identify risk for post-operative cognitive complications.', 'detailedDescription': 'This proposal innovatively leverages a brief but informative digital test with machine learning to examine the subtlety of pre-surgery cognition within an extremely large number of older individuals screened preoperatively within an academic tertiary medical center. It also incorporates a unique group of well characterized non-surgery peers for demographic matching to assist with normal versus abnormal machine learning analyses.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['OLDER_ADULT'], 'minimumAge': '65 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients \\>/= 65 years of age scheduled for screening within the UF Health Preoperative clinic', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* \\>/= 65 years of age\n* screening within the University of Florida (UF) Health Preoperative clinic\n* presurgical cognitive screening with the digital Clock Drawing Tool (dCDT)\n\nExclusion Criteria:\n\n* \\< 65 years of age\n* did not complete screening within the UF Health Preoperative clinic\n* did not complete the presurgical cognitive screening with the digital Clock Drawing Tool (dCDT)'}, 'identificationModule': {'nctId': 'NCT03175302', 'acronym': 'PRECEDE', 'briefTitle': 'PREsurgical Cognitive Evaluation Via Digital clockfacEdrawing', 'organization': {'class': 'OTHER', 'fullName': 'University of Florida'}, 'officialTitle': 'PREsurgical Cognitive Evaluation Via Digital clockfacEdrawing', 'orgStudyIdInfo': {'id': 'IRB201700747-N'}, 'secondaryIdInfos': [{'id': 'R01AG055337', 'link': 'https://reporter.nih.gov/quickSearch/R01AG055337', 'type': 'NIH'}, {'id': 'OCR18881', 'type': 'OTHER', 'domain': 'University of Florida'}]}, 'armsInterventionsModule': {'armGroups': [{'label': 'Surgical group', 'description': 'Baseline preoperative digital cognitive testing performance in adults to predict frequency and severity of clinician reported outcomes within the first three months post-surgery.', 'interventionNames': ['Behavioral: digital cognitive testing']}, {'label': 'Control', 'description': 'Non-surgery matched peers with the same testing.', 'interventionNames': ['Behavioral: digital cognitive testing']}], 'interventions': [{'name': 'digital cognitive testing', 'type': 'BEHAVIORAL', 'description': 'The digital testing is hypothesized to identify latent features for differentiating cognitively impaired presurgical patient subgroups', 'armGroupLabels': ['Control', 'Surgical group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '32610', 'city': 'Gainesville', 'state': 'Florida', 'status': 'RECRUITING', 'country': 'United States', 'contacts': [{'name': 'Catherine Price, Ph.D.', 'role': 'CONTACT', 'email': 'cep23@phhp.ufl.edu', 'phone': '352-494-6999'}], 'facility': 'UF Health', 'geoPoint': {'lat': 29.65163, 'lon': -82.32483}}], 'centralContacts': [{'name': 'Catherine Price, Ph.D.', 'role': 'CONTACT', 'email': 'cep23@phhp.ufl.edu', 'phone': '352-494-6999'}, {'name': 'Amy Gunnett, RN', 'role': 'CONTACT', 'email': 'agunnett@anest.ufl.edu', 'phone': '352-273-8911'}], 'overallOfficials': [{'name': 'Catherine Price, Ph.D.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Florida'}, {'name': 'Patrick Tighe, MD, MS', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Florida'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Florida', 'class': 'OTHER'}, 'collaborators': [{'name': 'National Institute on Aging (NIA)', 'class': 'NIH'}, {'name': 'National Center for Advancing Translational Sciences (NCATS)', 'class': 'NIH'}], 'responsibleParty': {'type': 'SPONSOR'}}}}