Ignite Creation Date:
2025-12-26 @ 10:58 AM
Ignite Modification Date:
2025-12-29 @ 1:39 PM
Study NCT ID:
NCT05533606
Status:
COMPLETED
Last Update Posted:
2023-11-18
First Post:
2022-09-02
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Risk Factors and Machine Learning Model for Beta-Lactam Drugs Related Acute Kidney Injury
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D058186', 'term': 'Acute Kidney Injury'}, {'id': 'D004194', 'term': 'Disease'}], 'ancestors': [{'id': 'D051437', 'term': 'Renal Insufficiency'}, {'id': 'D007674', 'term': 'Kidney Diseases'}, {'id': 'D014570', 'term': 'Urologic Diseases'}, {'id': 'D052776', 'term': 'Female Urogenital Diseases'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 19000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-07-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-11', 'completionDateStruct': {'date': '2023-06-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2023-11-15', 'studyFirstSubmitDate': '2022-09-02', 'studyFirstSubmitQcDate': '2022-09-08', 'lastUpdatePostDateStruct': {'date': '2023-11-18', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-09-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-06-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The incidence of acute kidney injury in hospitalized patients treated with β-lactam drugs', 'timeFrame': 'Through study completion，up to half a year.', 'description': 'To analyze the incidence of acute kidney injury in hospitalized patients after using β-lactam drugs and to build a prediction model.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Beta-Lactam drugs', 'Acute kidney injury', 'Pharmacoepidemiology', 'Miss diagnosis', 'Risk factors', 'Logic regression'], 'conditions': ['Acute Kidney Injury', 'Beta-Lactam Antibiotic Toxicity (Diagnosis)']}, 'descriptionModule': {'briefSummary': 'Acute kidney injury (AKI), also known as acute kidney failure (ARF), is a common and complex kidney disease in clinic and an important factor related to poor prognosis of patients in clinic. In the present study, a single-center retrospective study was conducted in our center. The clinical data of hospitalized patients received β-Lactam drugs from January 2018 to December 2020 was retrospectively analyzed. The multiple logistic regression analysis suggested that complicated with hypertension, anemia, pneumonia, shock, sepsis, heart failure, combined use of proton pump inhibitors (PPI), angiotensin-converting enzyme inhibitor (ACEI), angiotensin Ⅱ receptor antagonist (ARB) were independent risk factors for AKI related to β-Lactam drugs. In clinical practice, patients with acute kidney injury risk factors should be closely monitored for changes in their blood creatinine and urine output to avoid acute kidney injury. For patients who have suffered from acute kidney injury, the cause should be removed in time and corresponding symptomatic treatment should be given.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '100 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The patients were included if received treatment with β-lactam drugs and discharged from the hospital between January 1, 2018 and December 31, 2020', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* All inpatients who used β-lactam drugs during hospitalization\n* Hospital stay ≥ 48h\n* Age ≥18 years\n* There are two or more blood creatinine tests during hospitalization\n\nExclusion Criteria:\n\n* Hospital stay \\< 48h\n* Age \\<18 years\n* Glomerular filtration rate (GFR)\\< 30ml/min/1.73m2 within 48 hours after admission\n* AKI was diagnosed on admission\n* Less than two Scr test results during hospitalization\n* The Scr values were always lower than 40 μmol/L during hospitalization\n* Cases with incomplete medical history information'}, 'identificationModule': {'nctId': 'NCT05533606', 'briefTitle': 'Risk Factors and Machine Learning Model for Beta-Lactam Drugs Related Acute Kidney Injury', 'organization': {'class': 'OTHER', 'fullName': 'Qianfoshan Hospital'}, 'officialTitle': 'Analysis of Risk Factors of Beta-Lactam Drugs Related Acute Kidney Injury in Hospitalized Patients and Developments of Machine Learning Model', 'orgStudyIdInfo': {'id': 'LCYY-LX-20220103'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'AKI Group', 'interventionNames': ['Drug: Beta-Lactam Drugs']}, {'label': 'Non-AKI Group', 'interventionNames': ['Drug: Beta-Lactam Drugs']}], 'interventions': [{'name': 'Beta-Lactam Drugs', 'type': 'DRUG', 'description': 'During hospitalization，patients used Beta-Lactam drugs.', 'armGroupLabels': ['AKI Group', 'Non-AKI Group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '250014', 'city': 'Jinan', 'state': 'Shandong', 'country': 'China', 'facility': 'Xiao Li，MD', 'geoPoint': {'lat': 36.66833, 'lon': 116.99722}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Qianfoshan Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Associate professor of pharmacy', 'investigatorFullName': 'Xiao Li，MD', 'investigatorAffiliation': 'Qianfoshan Hospital'}}}}