[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100546492":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":35,"locations":44,"responsibleParty":103,"collaborators":105,"id":114,"slug":12,"hasResults":115,"nctId":116,"briefTitle":117,"officialTitle":118,"acronym":119,"eligibilityCriteria":120,"healthyVolunteers":115,"sex":121,"minAge":122,"maxAge":123,"enrollmentInfo":124,"targetDuration":12,"studyType":127,"phases":128,"briefSummary":130,"conditions":131,"keywords":135,"overallStatus":47,"whyStopped":12,"lastUpdateSubmitDate":144,"lastUpdatePostDateStruct":145,"startDateStruct":148,"completionDateStruct":150,"leadSponsor":152,"locationsCount":153},{"fullName":5,"class":6},"Ann & Robert H Lurie Children's Hospital of Chicago","OTHER",[8,13],{"label":9,"type":10,"description":11,"interventionNames":12},"Aim 1 - Validation","NO_INTERVENTION","1a. Development and Internal validation\n\n* analyze Fitbit data (PA, HR, sleep) by applying ML methods to create an infection algorithm indicating onset of infection.\n\n  1b. External Validation\n* Once the ML classifier has been internally validated (using Lurie Children's data only) for its ability to detect the presence or absence of postoperative infection using LOSO cross-validation, where each subject is iteratively held out from the training data and used as a test set. External validation will involve applying this classifier to a newer cohort at LCH and cohorts at Loyola University Hospital and CDH and evaluating its performance.",null,{"label":14,"type":15,"description":16,"interventionNames":17},"Aim 2 - Implementation of Algorithm","EXPERIMENTAL","2a. Exploratory \\& Inductive analysis\n\n* one transcript will be coded to generate initial themes, using qualitative analytic software 2b. Time to first contact with the healthcare system \\& Healthcare use\n* Cox regression model will be used to model the time to first contact, adjusted for covariates\n* All comparisons between the two groups will be tested using a chi-square test. Cost will be modeled as a continuous variable and is expected to be skewed, as is typical of cost data. We will use a general linear model (GLM) to model cost outcomes.",[18],"Device: Infection-Prediction Algorithm",[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":12},"DEVICE","Infection-Prediction Algorithm","This machine learning algorithm will be developed(Aim1a) and validated(Aim 1b) using the participant Fitbit data and survey results collected during Aim 1. In Aim 2 the algorithm will be used in real time to predict postoperative infection.",[14],[26,29,32],{"name":27,"affiliation":5,"role":28},"Fizan Abdullah, MD, PhD","PRINCIPAL_INVESTIGATOR",{"name":30,"affiliation":31,"role":28},"Hassan Ghomrawi, PhD, MPH","University of Alabama at Birmingham",{"name":33,"affiliation":34,"role":28},"Arun Jayaraman, PT, PhD","Shirley Ryan AbilityLab",[36,40],{"name":27,"role":37,"phone":38,"phoneExt":12,"email":39},"CONTACT","312-227-4210","fabdullah@luriechildrens.org",{"name":41,"role":37,"phone":42,"phoneExt":12,"email":43},"Arianna Edobor, CRC","312-227-2118","idetect@luriechildrens.org",[45,65,76,90],{"facility":46,"status":47,"city":48,"state":49,"zip":50,"country":51,"cosmosGeoPoint":52,"geoPoint":57,"contacts":58},"Ann & Robert H. Lurie Children's Hospital of Chicago","RECRUITING","Chicago","Illinois","60611","United States",{"type":53,"coordinates":54},"Point",[55,56],-87.65005,41.85003,{"lat":56,"lon":55},[59,61,64],{"name":27,"role":37,"phone":38,"phoneExt":12,"email":60},"FAbdullah@luriechildrens.org",{"name":62,"role":37,"phone":42,"phoneExt":12,"email":63},"Arianna Edobor, BS","aedobor@luriechildrens.org",{"name":27,"role":28,"phone":12,"phoneExt":12,"email":12},{"facility":66,"status":67,"city":48,"state":49,"zip":50,"country":51,"cosmosGeoPoint":68,"geoPoint":70,"contacts":71},"Northwestern University (Feinberg School of Medicine, Shirley Ryan AbilityLab)","NOT_YET_RECRUITING",{"type":53,"coordinates":69},[55,56],{"lat":56,"lon":55},[72,73,75],{"name":27,"role":37,"phone":38,"phoneExt":12,"email":39},{"name":74,"role":37,"phone":42,"phoneExt":12,"email":63},"Clinical Research Coordinator",{"name":27,"role":28,"phone":12,"phoneExt":12,"email":12},{"facility":77,"status":67,"city":78,"state":49,"zip":79,"country":51,"cosmosGeoPoint":80,"geoPoint":84,"contacts":85},"Loyola University Medical Center","Maywood","60153",{"type":53,"coordinates":81},[82,83],-87.84312,41.8792,{"lat":83,"lon":82},[86,87],{"name":74,"role":37,"phone":42,"phoneExt":12,"email":63},{"name":88,"role":89,"phone":12,"phoneExt":12,"email":12},"Steven A De Jong, MD","SUB_INVESTIGATOR",{"facility":91,"status":47,"city":92,"state":49,"zip":93,"country":51,"cosmosGeoPoint":94,"geoPoint":98,"contacts":99},"Northwestern Medicine Central DuPage Hospital","Winfield","60190",{"type":53,"coordinates":95},[96,97],-88.1609,41.8617,{"lat":97,"lon":96},[100,101],{"name":74,"role":37,"phone":42,"phoneExt":12,"email":63},{"name":102,"role":89,"phone":12,"phoneExt":12,"email":12},"Guillermo Ares, MD",{"type":28,"investigatorFullName":27,"investigatorTitle":104,"investigatorAffiliation":5,"oldNameTitle":12,"oldOrganization":12},"Fizan Abdullah M.D., Ph.D",[106,108,110,112],{"name":107,"class":6},"Northwestern University",{"name":109,"class":6},"Central DuPage Hospital",{"name":111,"class":6},"University of Chicago",{"name":113,"class":6},"Loyola University Chicago","100546492",false,"NCT06395636","Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients","Using the Fitbit for Early Detection of Infection and Reduction of Healthcare Utilization After Discharge in Pediatric Surgical Patients","i-DETECT","Inclusion Criteria:\n\n* children aged 3-18 years\n* must be post-surgical laparoscopic appendectomy for complicated appendicitis (Appendicitis is categorized as complicated if perforation, phlegmon, or abscess was present at surgery.)\n\nExclusion Criteria:\n\n* children who are non-ambulatory or have any pre-existing mobility limitations\n* children who have a doctor-ordered physical activity limit \\>48 hours post-surgery\n* children who have a comorbidity which will impact a patient's recovery\n* children and\u002For parents who do not speak English or Spanish (Translation services beyond Spanish will not be available at this time)","ALL","3 Years","18 Years",{"count":125,"type":126},500,"ESTIMATED","INTERVENTIONAL",[129],"NA","The purpose of this study is to analyze Fitbit data to predict infection after surgery for complicated appendicitis and the effect this prediction has on clinician decision making.",[132,133,134],"Appendectomy","Appendicitis","Appendicitis Acute",[136,137,138,139,140,141,142,143],"consumer wearables","machine learning","ML","Fitbit","infection","detection","algorithm","prediction","2026-05-11",{"date":146,"type":147},"2026-05-13","ACTUAL",{"date":149,"type":147},"2025-01-07",{"date":151,"type":126},"2027-06-30",{"name":5,"class":6},4]