Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 9481}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2024-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-06', 'completionDateStruct': {'date': '2024-06-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-07-08', 'studyFirstSubmitDate': '2024-06-27', 'studyFirstSubmitQcDate': '2024-07-08', 'lastUpdatePostDateStruct': {'date': '2024-07-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-07-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-06-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'the incidence of postoperative pulmonary infection during hospitalization', 'timeFrame': 'through study completion, an average of 30 days', 'description': 'the incidence of postoperative pulmonary infection during hospitalization'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Postoperative Pulmonary Infection in Elderly Patients']}, 'referencesModule': {'references': [{'pmid': '40108569', 'type': 'DERIVED', 'citation': 'Liu J, Li X, Wang Y, Xu Z, Lv Y, He Y, Chen L, Feng Y, Liu G, Bai Y, Xie W, Wu Q. Predicting postoperative pulmonary infection in elderly patients undergoing major surgery: a study based on logistic regression and machine learning models. BMC Pulm Med. 2025 Mar 19;25(1):128. doi: 10.1186/s12890-025-03582-4.'}]}, 'descriptionModule': {'briefSummary': 'Although a number of clinical predictive models were developed to predict postoperative pulmonary infection, few predictive models have been used in elderly patients. In this study, the researchers aim to compare different algorithms to predict postoperative pulmonary infection in elderly patients and to assess the risk of postoperative pulmonary infection in elderly patients.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['OLDER_ADULT'], 'minimumAge': '65 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Elderly patients underwent surgery at the tertiary hospital Hospital from January 2014 to December 2019.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. age ≥ 65 years\n2. patients who were mechanically ventilated under major surgery\n\nExclusion Criteria:\n\n1. preoperative tracheal intubation\n2. preoperative pneumonia\n3. organ transplantation\n4. missing data'}, 'identificationModule': {'nctId': 'NCT06491459', 'briefTitle': 'Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery: a Study Based on Logistic Regression and Machine Learning Models', 'organization': {'class': 'OTHER', 'fullName': 'Union Hospital, Tongji Medical College, Huazhong University of Science and Technology'}, 'officialTitle': 'Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery: a Study Based on Logistic Regression and Machine Learning Models', 'orgStudyIdInfo': {'id': 'UHCT21772'}}, 'contactsLocationsModule': {'locations': [{'zip': '430022', 'city': 'Wuhan', 'state': 'Hubei', 'country': 'China', 'facility': 'Union Hospital, Tongji Medical College, Huazhong University of Science and Technology', 'geoPoint': {'lat': 30.58333, 'lon': 114.26667}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Union Hospital, Tongji Medical College, Huazhong University of Science and Technology', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}