Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D058186', 'term': 'Acute Kidney Injury'}], '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'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITHOUT_DNA', 'description': 'Urine'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 20}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2017-02-03', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-05', 'completionDateStruct': {'date': '2020-01-09', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-05-21', 'studyFirstSubmitDate': '2017-02-08', 'studyFirstSubmitQcDate': '2017-02-08', 'lastUpdatePostDateStruct': {'date': '2024-05-22', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2017-02-09', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2017-05-29', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Acute Kidney Injury', 'timeFrame': 'Within 7 days', 'description': 'Defined by KDIGO Criteria'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Urine', 'Mass Spectometry', 'Observational'], 'conditions': ['Acute Kidney Injury']}, 'descriptionModule': {'briefSummary': 'To determine whether MALDI, a type of Mass-Spectometry, can use protein pattern detection within urine to predict postoperative (after an operation) kidney damage in adults who have undergone emergency hip fracture surgery?', 'detailedDescription': 'The PRE-RENAL study is a prognostic accuracy study testing the ability of the MALDI-MS assay to predict incident acute kidney injury after fractured neck of femur surgery. The study aims to validate the findings of a urinary peptide panel previously developed and validated on a cohort of septic patients.\n\nKidney injury following surgery or as a part of severe illness is an important complication, because it can delay and reduce the chances of recovery. A reliable early test for kidney injury would be useful so that treatments to prevent or minimise it can be started as early as possible. This study, based with a group of medical researchers working with chemists, will analyse clinical urine specimens from patients undergoing major orthopaedic (bone) surgery. We will explore whether patterns of proteins in the urine could be used as an early warning that kidney injury is present before existing tests demonstrate it.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '50 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients over 50 years old who have suffered fractured neck of the femur', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Fractured Neck of Femur\n* Age \\>50\n* Informed consent\n\nExclusion Criteria:\n\n* Refusal of Consent'}, 'identificationModule': {'nctId': 'NCT03049150', 'acronym': 'PRE-RENAL', 'briefTitle': 'PREdicting RENAL Injury In Patient After Hip Fracture Surgery', 'organization': {'class': 'OTHER', 'fullName': 'University of Edinburgh'}, 'officialTitle': 'The Use of Urinary MALDI-MS in Predicting Post-Operative Acute Kidney Injury in Patients After Fixation of Fractured Neck of Femur.', 'orgStudyIdInfo': {'id': 'AC16138'}}, 'contactsLocationsModule': {'locations': [{'city': 'Edinburgh', 'country': 'United Kingdom', 'facility': 'NHS Lothian', 'geoPoint': {'lat': 55.95206, 'lon': -3.19648}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Edinburgh', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}