Ignite Creation Date:
2025-12-24 @ 9:24 PM
Ignite Modification Date:
2025-12-30 @ 7:07 PM
Study NCT ID:
NCT06247332
Status:
COMPLETED
Last Update Posted:
2025-02-18
First Post:
2024-01-31
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
SENSING-AI in Patients With Long COVID (SENSING-AI)
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000094024', 'term': 'Post-Acute COVID-19 Syndrome'}, {'id': 'D000092862', 'term': 'Psychological Well-Being'}], 'ancestors': [{'id': 'D000086382', 'term': 'COVID-19'}, {'id': 'D011024', 'term': 'Pneumonia, Viral'}, {'id': 'D011014', 'term': 'Pneumonia'}, {'id': 'D012141', 'term': 'Respiratory Tract Infections'}, {'id': 'D007239', 'term': 'Infections'}, {'id': 'D014777', 'term': 'Virus Diseases'}, {'id': 'D018352', 'term': 'Coronavirus Infections'}, {'id': 'D003333', 'term': 'Coronaviridae Infections'}, {'id': 'D030341', 'term': 'Nidovirales Infections'}, {'id': 'D012327', 'term': 'RNA Virus Infections'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}, {'id': 'D000094025', 'term': 'Post-Infectious Disorders'}, {'id': 'D002908', 'term': 'Chronic Disease'}, {'id': 'D020969', 'term': 'Disease Attributes'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D010549', 'term': 'Personal Satisfaction'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 103}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-01-18', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-02', 'completionDateStruct': {'date': '2022-02-25', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-02-14', 'studyFirstSubmitDate': '2024-01-31', 'studyFirstSubmitQcDate': '2024-01-31', 'lastUpdatePostDateStruct': {'date': '2025-02-18', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-02-07', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-02-25', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Retrospective SENSING-AI cohort', 'timeFrame': '1 month', 'description': 'The retrospective SENSING-AI cohort will be fed from clinical information of 100 cases of patients with long COVID-19.'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Long COVID-19', 'Retrospective study', 'Artificial Intelligence', 'Mental Health'], 'conditions': ['Post-acute COVID-19 Syndrome']}, 'descriptionModule': {'briefSummary': 'The retrospective study will be used to develop an artificial intelligence model of risk stratification of physiological and psychological complications arising from the information available in the electronic medical record and first consultation report to support patients and healthcare professionals in better managing the healthcare process for patients diagnosed with long COVID.', 'detailedDescription': "The stratification of the risk of complications related to persistent COVID both physiological and psychological in a personalized way would optimize the cost-effectiveness model for the management of these patients. Similarly, the early detection of complications associated with persistent COVID in patients belonging to vulnerable groups would improve care times and, therefore, the patient's prognosis.\n\nThe primary objective for this study is to gather anonymized retrospective data of patients suffering from long COVID in order to contribute to the generation of the SENSING-AI cohort."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The sample size for the retrospective study enough to generate a first version of the risk stratification models will be around 100 cases. The target population will be as balanced as possible between subjects who needed specialized care due to long COVID-19 complications (either specialized care consultations or any non-planned hospital admission) at 1 month, 3 months, 6 months and 1 year from the long COVID-19 diagnose and those who did not require such specialized care.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Legal adult\n* Diagnosed of long COVID-19 in the last year\n* With the presence of any of these symptoms:\n* Asthenia (Tiredness)\n* Dyspnea\n* Shortness of breath\n* Anxiety\n* Stress\n* Depression\n* Sleep disorder\n\nExclusion Criteria:\n\n* Attended to specialized care consultation\n* Was admitted in hospital in the last year due to a problem not related to the COVID complications'}, 'identificationModule': {'nctId': 'NCT06247332', 'acronym': 'SENSING-AI', 'briefTitle': 'SENSING-AI in Patients With Long COVID (SENSING-AI)', 'organization': {'class': 'INDUSTRY', 'fullName': 'Adhera Health, Inc.'}, 'officialTitle': 'Retrospective Data Collection for SENSING-AI: a Wearable Platform for the Early Diagnosis of Emotional Disorders and Exacerbations in Patients With Long COVID Through the Use of Artificial Intelligence', 'orgStudyIdInfo': {'id': 'SEN-0121'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Retrospective Long COVID cases', 'description': 'The target population will be as balanced as possible between subjects who needed specialized care due to long COVID-19 complications (either specialized care consultations or any non-planned hospital admission) at 1 month, 3 months, 6 months and 1 year from the long COVID-19 diagnose and those who did not require such specialized care.', 'interventionNames': ['Other: Review of available clinical data sources related to use cases']}], 'interventions': [{'name': 'Review of available clinical data sources related to use cases', 'type': 'OTHER', 'description': 'There will be a review of available clinical data sources related to use cases. In addition, this information will be complemented by a cohort of anonymized retrospective data of 100 cases obtained from the clinical information resulting from the assistance to COVID-19 patients managed by the Primary Care Health District of Sevilla Norte and the Infectious Diseases Department of the Virgen Macarena University Hospital', 'armGroupLabels': ['Retrospective Long COVID cases']}]}, 'contactsLocationsModule': {'locations': [{'zip': '41009', 'city': 'Seville', 'state': 'Seville', 'country': 'Spain', 'facility': 'Virgen Macarena University Hospital', 'geoPoint': {'lat': 37.38283, 'lon': -5.97317}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Adhera Health, Inc.', 'class': 'INDUSTRY'}, 'collaborators': [{'name': 'Hospital Universitario Virgen Macarena', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}