Ignite Creation Date:
2025-12-25 @ 4:58 AM
Ignite Modification Date:
2025-12-26 @ 3:58 AM
Study NCT ID:
NCT04570618
Status:
COMPLETED
Last Update Posted:
2021-11-03
First Post:
2020-09-22
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Early Prediction of Sepsis
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': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'TRIPLE', 'whoMasked': ['PARTICIPANT', 'CARE_PROVIDER', 'INVESTIGATOR']}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 320}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-12-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2021-11', 'completionDateStruct': {'date': '2021-11-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2021-11-02', 'studyFirstSubmitDate': '2020-09-22', 'studyFirstSubmitQcDate': '2020-09-25', 'lastUpdatePostDateStruct': {'date': '2021-11-03', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-09-30', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-11-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Validate the prognostic accuracy of the algorithm at predicting sepsis.', 'timeFrame': 'Up to 30 days (ICU hospitalization period)', 'description': 'In order to clinically validate the sepsis prediction performance the following endpoints have been selected:\n\n* accuracy,\n* specificity, and\n* sensitivity of the AlgoDx Sepsis Prediction Algorithm in the SoC group (not possible to assess these in the SoC + Algorithm cohort).'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Prediction'], 'conditions': ['Sepsis']}, 'referencesModule': {'references': [{'pmid': '38245375', 'type': 'DERIVED', 'citation': 'Persson I, Macura A, Becedas D, Sjovall F. Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY(R) Sepsis, a prospective randomized clinical validation study. J Crit Care. 2024 Apr;80:154400. doi: 10.1016/j.jcrc.2023.154400.'}]}, 'descriptionModule': {'briefSummary': 'In this clinical trial a novel Medical Device Software will be validated prospectively. The software incorporates a machine learning algorithm capable of predicting sepsis by using routine clinical variables in adult patients at Intensive Care Units.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n1. Adult patient (age ≥18 years).\n2. Patient is admitted to the ICU during the recruitment period of the trial.\n\nExclusion Criteria:\n\n1. Patient is participating in another interventional clinical trial which, as judged by the investigator, could potentially impact variables used by the sepsis prediction algorithm or has participated in such interventional clinical trial within the last 30 days.\n2. Patient is known to be pregnant.\n3. Death is deemed imminent and inevitable, at the investigator's discretion.\n4. Patient has, due to chronic reduced mental capacity, been assessed by the investigator as incapable of making an informed decision\n5. Patient has previously been enrolled in this trial."}, 'identificationModule': {'nctId': 'NCT04570618', 'acronym': 'ExPRESS', 'briefTitle': 'Early Prediction of Sepsis', 'organization': {'class': 'INDUSTRY', 'fullName': 'AlgoDx'}, 'officialTitle': 'Early Prediction of Sepsis in Hospitalized Patients Using a Machine Learning Algorithm, a Randomized Clinical Validation Trial.', 'orgStudyIdInfo': {'id': 'SEP-SE-02'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'SHAM_COMPARATOR', 'label': 'Standard of Care', 'description': 'Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines.', 'interventionNames': ['Other: Blinded AlgoDx Sepsis Prediction Algorithm']}, {'type': 'EXPERIMENTAL', 'label': 'Standard of Care + AlgoDx Sepsis Prediction Algorithm', 'description': 'Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines, and sepsis prediction algorithm alerts are unblinded to clinical staff.', 'interventionNames': ['Device: Unblinded AlgoDx Sepsis Prediction Algorithm']}], 'interventions': [{'name': 'Unblinded AlgoDx Sepsis Prediction Algorithm', 'type': 'DEVICE', 'description': 'When applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software.', 'armGroupLabels': ['Standard of Care + AlgoDx Sepsis Prediction Algorithm']}, {'name': 'Blinded AlgoDx Sepsis Prediction Algorithm', 'type': 'OTHER', 'description': 'Standard of Care, i.e. no sepsis prediction alert.', 'armGroupLabels': ['Standard of Care']}]}, 'contactsLocationsModule': {'locations': [{'zip': '20502', 'city': 'Malmo', 'country': 'Sweden', 'facility': 'Intensiv- och perioperativ vård', 'geoPoint': {'lat': 55.60587, 'lon': 13.00073}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'AlgoDx', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}