Ignite Creation Date:
2025-12-25 @ 3:19 AM
Ignite Modification Date:
2025-12-26 @ 1:57 AM
Study NCT ID:
NCT03533205
Status:
COMPLETED
Last Update Posted:
2018-05-23
First Post:
2018-04-26
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Prediction of Hemodynamic Instability in Patients Undergoing Surgery
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 507}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2015-04-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2018-05', 'completionDateStruct': {'date': '2018-04-26', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2018-05-22', 'studyFirstSubmitDate': '2018-04-26', 'studyFirstSubmitQcDate': '2018-05-22', 'lastUpdatePostDateStruct': {'date': '2018-05-23', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2018-05-23', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2016-12-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Sensitivity of the HPI algorithm', 'timeFrame': 'three minutes prior to the hypotensive event', 'description': 'Sensitivity'}, {'measure': 'Specifity of the HPI algorithm', 'timeFrame': 'three minutes prior to the hypotensive event', 'description': 'Specifity'}], 'secondaryOutcomes': [{'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': 'one minute prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': 'two minutes prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': 'three minutes prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': 'four minutes prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': 'five minutes prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': 'ten minutes prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Predictive positive value of the HPI algorithm', 'timeFrame': '15 minutes prior to the hypotensive event', 'description': 'Predictive positive value'}, {'measure': 'Negative predictive value of the HPI algorithm', 'timeFrame': 'one minute prior to the hypotensive event', 'description': 'Negative predictive value'}, {'measure': 'Negative predictive value of the HPI algorithm', 'timeFrame': 'two minutes prior to the hypotensive event', 'description': 'Negative predictive value'}, {'measure': 'Negative predictive value of the HPI algorithm', 'timeFrame': 'four minutes prior to the hypotensive event', 'description': 'Negative predictive value'}, {'measure': 'Negative predictive value of the HPI algorithm', 'timeFrame': 'five minutes prior to the hypotensive event', 'description': 'Negative predictive value'}, {'measure': 'Negative predictive value of the HPI algorithm', 'timeFrame': 'ten minutes prior to the hypotensive event', 'description': 'Negative predictive value'}, {'measure': 'Negative predictive value of the HPI algorithm', 'timeFrame': '15 minutes prior to the hypotensive event', 'description': 'Negative predictive value'}, {'measure': 'Time from HPI alarm to hypotensive event during surgery', 'timeFrame': 'From the onset of the HPI alarm to the hypotensive event during surgery, this is in minutes. (this can range from 0,1 min to a high number such as 30 or even 40 minutes)', 'description': 'Time from HPI alarm to hypotensive event, this can range from 0,1 min to a high number such as 30 or even 40 minutes.'}, {'measure': 'Sensitivity of the HPI algorithm', 'timeFrame': 'one minute prior to the hypotensive event', 'description': 'Sensitivity'}, {'measure': 'Sensitivity of the HPI algorithm', 'timeFrame': 'two minutes prior to the hypotensive event', 'description': 'Sensitivity'}, {'measure': 'Sensitivity of the HPI algorithm', 'timeFrame': 'five minutes prior to the hypotensive event', 'description': 'Sensitivity'}, {'measure': 'Sensitivity of the HPI algorithm', 'timeFrame': 'ten minutes prior to the hypotensive event', 'description': 'Sensitivity'}, {'measure': 'Sensitivity of the HPI algorithm', 'timeFrame': '15 minutes prior to the hypotensive event', 'description': 'Sensitivity'}, {'measure': 'Specifity of the HPI algorithm', 'timeFrame': 'one minute prior to the hypotensive event', 'description': 'Specifity'}, {'measure': 'Specifity of the HPI algorithm', 'timeFrame': 'two minutes prior to the hypotensive event', 'description': 'Specifity'}, {'measure': 'Specifity of the HPI algorithm', 'timeFrame': 'five minutes prior to the hypotensive event', 'description': 'Specifity'}, {'measure': 'Specifity of the HPI algorithm', 'timeFrame': 'ten minutes prior to the hypotensive event', 'description': 'Specifity'}, {'measure': 'Specifity of the HPI algorithm', 'timeFrame': '15 minutes prior to the hypotensive event', 'description': 'Specifity'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Blood Pressure', 'Prediction Models', 'Machine Learning', 'Hemodynamic Instability']}, 'referencesModule': {'references': [{'pmid': '33927105', 'type': 'DERIVED', 'citation': 'Wijnberge M, van der Ster BJP, Geerts BF, de Beer F, Beurskens C, Emal D, Hollmann MW, Vlaar APJ, Veelo DP. Clinical performance of a machine-learning algorithm to predict intra-operative hypotension with noninvasive arterial pressure waveforms: A cohort study. Eur J Anaesthesiol. 2021 Jun 1;38(6):609-615. doi: 10.1097/EJA.0000000000001521.'}]}, 'descriptionModule': {'briefSummary': 'Intraoperative hypotension occurs often and is associated with adverse patient outcomes such as stroke, myocardial infarction and renal injury.\n\nThe aim of this study was to test the accuracy of a physiology-based machine-learning algorithm using continuous non-invasive measurement of the blood pressure waveform with the Nexfin® finger cuff during surgery.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'All adult patients undergoing surgery in the AMC were included in the study. Subjects were only excluded when technical problems or strong local vasoconstriction (i.e., cold fingers) prevented the Nexfin® non-invasive blood pressure finger cuff measurement. Subjects were not excluded for any other reason besides technical failure.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* all adult patients undergoing surgery\n\nExclusion Criteria:\n\n* none'}, 'identificationModule': {'nctId': 'NCT03533205', 'briefTitle': 'Prediction of Hemodynamic Instability in Patients Undergoing Surgery', 'organization': {'class': 'OTHER', 'fullName': 'Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)'}, 'officialTitle': 'Prediction of Hemodynamic Instability in Patients Undergoing Surgery', 'orgStudyIdInfo': {'id': 'W15_080'}}, 'armsInterventionsModule': {'interventions': [{'name': 'Hypotension Probability Indicator', 'type': 'DIAGNOSTIC_TEST', 'description': 'The accurary of the Hypotension Probability Indicator (HPI) is tested in the created offline database. This means data was prospectively collected but the HPI algorithm was not tested prospectively but after collection in the offline database.'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'MD PhD', 'investigatorFullName': 'D.P.Veelo', 'investigatorAffiliation': 'Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)'}}}}