[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100605133":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":12,"centralContacts":16,"locations":21,"responsibleParty":38,"collaborators":40,"id":44,"slug":45,"hasResults":46,"nctId":47,"briefTitle":48,"officialTitle":49,"acronym":50,"eligibilityCriteria":51,"healthyVolunteers":46,"sex":52,"minAge":53,"maxAge":10,"enrollmentInfo":54,"targetDuration":10,"studyType":57,"phases":10,"briefSummary":58,"conditions":59,"keywords":65,"overallStatus":68,"whyStopped":10,"lastUpdateSubmitDate":69,"lastUpdatePostDateStruct":70,"startDateStruct":73,"completionDateStruct":75,"leadSponsor":77,"locationsCount":78},{"fullName":5,"class":6},"University of Salford","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Older Adults",null,"Adults aged 60 or older who have a fall and remain immobilised for \\>1 hour",[13],{"name":14,"affiliation":5,"role":15},"Ashley Reed, MSc MResCP BSc (Hons)","PRINCIPAL_INVESTIGATOR",[17],{"name":14,"role":18,"phone":19,"phoneExt":10,"email":20},"CONTACT","+447534964854","A.D.Reed@edu.salford.ac.uk",[22],{"facility":23,"status":10,"city":24,"state":25,"zip":26,"country":27,"countryCode":28,"cosmosGeoPoint":29,"geoPoint":34,"contacts":35},"Southend University Hospital","Westcliff-on-Sea","Essex","SS0 0RY","United Kingdom","UK",{"type":30,"coordinates":31},"Point",[32,33],0.69179,51.54424,{"lat":33,"lon":32},[36,37],{"name":14,"role":18,"phone":19,"phoneExt":10,"email":20},{"name":14,"role":15,"phone":10,"phoneExt":10,"email":10},{"type":39,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[41],{"name":42,"class":43},"Mid & South Essex NHS Foundation Trust","UNKNOWN","100605133","the-rhabdomyolysis-evaluation-in-the-emergency-department-reed-score-100605133",false,"NCT07158554","The Rhabdomyolysis Evaluation in the Emergency Department (REED) Score","The Rhabdomyolysis Evaluation in the Emergency Department (REED) Score - a Risk Prediction Model for Older Adults in the Emergency Department With Rhabdomyolysis After Prolonged Immobilisation (\"Long Lie\")","The REED Score","Inclusion Criteria:\n\nThe participants need to fulfil all three parts of the inclusion criteria:\n\n1. 60 years old or older at time of ED presentation\n2. Developed rhabdomyolysis (defined as CK \\>999U\u002FL)\n3. Have had a fall and been \u002F suspected to have been on the floor \u002F immobilised in one position for \\> 59 minutes.\n\nExclusion Criteria:\n\n1. Patient opted out of research studies via the National Data Opt Out (NDOO) Service.\n2. Principal Investigator (PI) had clinical input into patient care.\n3. Other causes of elevated creatine kinase (e.g. seizures, acute coronary syndromes, burns, myositis, muscular dystrophy, cardiac arrest)","ALL","60 Years",{"count":55,"type":56},1000,"ESTIMATED","OBSERVATIONAL","One in three adults over 65 fall annually, with one in five remaining on the floor for greater than one hour, which is referred to as a long lie. Pressure on the National Health Service has resulted in extended stays in the Emergency Department (ED) (sometimes longer than 12 hours) and prolonged ambulance response times. This impacts the older adults who have fallen and remain on the floor.\n\nThis project aims to develop a risk prediction model (RPM) for use within the ED to understand which older adults (60 years or older) who fall over and remain on the floor for longer than one hour (\"long lie\") and develop rhabdomyolysis (a serious condition where muscle breaks down and releases substances into the blood that can damage the kidneys) will develop poor outcomes and need admission to hospital for treatment and which patients can be safely discharged home.\n\nAim:\n\nTo develop a RPM to identify which older adults who have a fall and a long lie and attend the ED develop poor outcomes such as Acute kidney Injury (AKI) \\[kidneys suddenly stop working properly\\], needing kidney replacement therapy (KRT) \\[a treatment that helps kidneys that aren't working properly do their job of cleaning the blood\\] and mortality \\[death\\].\n\nObjectives:\n\n1. Abstract patient level data (e.g. biochemical, demographic, situational, medical history, medication history) from medical records combined with outcomes to understand which variables lead to poor outcomes such as AKI, needing KRT and mortality.\n2. Analyse the data using a statistical package (Statistical Package for Social Sciences \\[SPSS\\]) to develop a RPM with good discriminative abilities \\[how well the score can tell high-risk from low-risk patients\\].\n3. Demonstrate the ability of the RPM to identify which patients need admission to hospital with treatment and which patients can be safely discharged home.",[60,61,62,63,64],"Rhabdomyolysis","Death","Kidney Replacement Therapy","Fall Patients","Acute Kidney Injury",[50,60,66,67],"Emergency Department","Long Lie","NOT_YET_RECRUITING","2025-09-10",{"date":71,"type":72},"2025-09-17","ACTUAL",{"date":74,"type":56},"2025-10",{"date":76,"type":56},"2026-04",{"name":5,"class":6},1]