Doctorate
Doctorate Title: The derivation and validation of the Rhabdomyolysis Evaluation in the Emergency Department Score (REED Score) - a risk prediction model for patients in the Emergency Department with rhabdomyolysis after prolonged immobilisation (“long lie”).
Doctorate Description: The population in the UK is ageing and the number of falls whether in a private dwelling or a care setting is substantial with a significant risk of a ‘long lie’ occurring. The ambulance service and the Emergency Departments (ED) are overstretched resulting in long delays for ambulances and prolonged ED attendances. This can contribute to hospital admissions where patients can be deconditioned, develop infections or delirium and further contribute to prolonged hospital stays, thus compounding the problem further. Some patients that develop rhabdomyolysis are often admitted to hospital based exclusively on an arbitrarily defined CK value, developing the aforementioned sequelae needlessly. Conversely, others may be discharged when the arbitrarily defined CK is not met but deteriorate due to under recognition of the rhabdomyolysis risk, which may increase subsequent renal replacement therapy (RRT) need and mortality. This highlights the current state of the population, health systems and management of patients in the UK who are older, fall and remain immobilised. To help identify which patients who develop rhabdomyolysis after a fall and attend the ED are safe for discharge, a risk prediction model needs to be developed. This could reduce the burden on the health system by giving the right treatment and care in an appropriate setting. If identified to be low risk, patients could be safely managed in the community as opposed to an acute hospital. Alternatively, high risk patients could be identified, admitted and more aggressive, necessary interventions provided to reduce subsequent morbidity and mortality. To develop a risk prediction model in this specific patient population the risk factors need to be identified which strongly correlate with developing an acute kidney injury (AKI), needing RRT or subsequently dying. These factors may be related to demographic data (e.g. age, gender, ethnicity), circumstantial (e.g. time on floor), biochemical (e.g. CK, phosphate, lactate) or based on comorbidities, polypharmacy or frailty. This study will derive and validate the risk score for rhabdomyolysis evaluation in the ED.
Details:
Type: Professional Doctorate
University: University of Salford
Primary Supervisor: Professor Helen Hurst
Category: Older Adult
Funding:
Start Date: 2024
End Date: 2027
Status: Ongoing
Thesis
Awaiting
