Ignite Creation Date:
2025-12-25 @ 4:16 AM
Ignite Modification Date:
2025-12-26 @ 3:15 AM
Study NCT ID:
NCT05095220
Status:
COMPLETED
Last Update Posted:
2023-05-22
First Post:
2021-09-30
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Integration of NAVOY® Sepsis in an Electronic Health Record System
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D018805', 'term': 'Sepsis'}], 'ancestors': [{'id': 'D007239', 'term': 'Infections'}, {'id': 'D018746', 'term': 'Systemic Inflammatory Response Syndrome'}, {'id': 'D007249', 'term': 'Inflammation'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 1000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-05-27', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-05', 'completionDateStruct': {'date': '2023-03-08', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2023-05-19', 'studyFirstSubmitDate': '2021-09-30', 'studyFirstSubmitQcDate': '2021-10-14', 'lastUpdatePostDateStruct': {'date': '2023-05-22', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-10-27', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-03-08', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'NAVOY® Sepsis prediction performance', 'timeFrame': '6 months', 'description': 'NAVOY® Sepsis prediction output within the simulated environment will be monitored and compared to the observed fulfilment of Sepsis-3 diagnosis criteria and sepsis specific management.'}], 'secondaryOutcomes': [{'measure': 'Integration validation', 'timeFrame': '6 months', 'description': 'A technical checklist will be used in order to validate the integration between NAVOY® Sepsis and the electronic health record system.'}, {'measure': 'NAVOY® Sepsis prediction results', 'timeFrame': '6 months', 'description': 'The NAVOY® Sepsis predictions results indicate if the subject is at risk of developing sepsis within the coming hours. The results are not made available to ICU staff.'}, {'measure': 'Fulfilment of Sepsis-3 criteria', 'timeFrame': '6 months', 'description': 'The dimensions of the Sepsis-3 diagnosis criteria that the subjects meet during their ICU stay.'}, {'measure': 'Sepsis specific management', 'timeFrame': '6 months', 'description': 'Actions taken at the ICU specifically as part of sepsis detection, prevention, or treatment.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['sepsis', 'ICU', 'prediction', 'decision support', 'machine learning', 'intensive care'], 'conditions': ['Sepsis']}, 'descriptionModule': {'briefSummary': 'The study aims to evaluate the performance of NAVOY® Sepsis in predicting the sepsis risk in adult ICU patients. Data collection is performed via automatic retrieval from the electronic health record system to AlgoDx proprietary cloud service where it is analysed in a simulated environment.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Adult ICU patients admitted to the ICU during the enrolment period.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* The subject is admitted to the ICU during the enrolment period.\n* The subject is 18 years of age or older at the time of admission to the ICU.\n\nExclusion Criteria:\n\n* None.'}, 'identificationModule': {'nctId': 'NCT05095220', 'acronym': 'GENIUS', 'briefTitle': 'Integration of NAVOY® Sepsis in an Electronic Health Record System', 'organization': {'class': 'INDUSTRY', 'fullName': 'AlgoDx'}, 'officialTitle': 'Integration and Evaluation of a Machine Learning Algorithm for Sepsis Prediction in an Electronic Health Record System - a Prospective Observational Study', 'orgStudyIdInfo': {'id': 'SEP-SE-03'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Observational Cohort'}]}, 'contactsLocationsModule': {'locations': [{'city': 'Stockholm', 'country': 'Sweden', 'facility': 'Southern General Hospital', 'geoPoint': {'lat': 59.32938, 'lon': 18.06871}}], 'overallOfficials': [{'name': 'Martin Arlbrandt, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Southern General Hospital'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'AlgoDx', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}