Acute Kidney Injury; Prediction and causal contributions.
Research type
Research Study
Full title
Acute Kidney Injury; Prediction and causal contributions.
IRAS ID
257328
Contact name
Nicholas Timpson
Contact email
Sponsor organisation
University of Bristol
Duration of Study in the UK
2 years, 0 months, 1 days
Research summary
Research Summary
Acute Kidney Injury (AKI) is a found in up to 30% of all patients who undergo cardiac surgery leading to around 1% who require dialysis. The development of kidney injury is associated with a high mortality, a more complicated hospital course, and a higher risk for infectious complications. There are few therapeutic options to prevent or treat AKI and the low incidence of AKI and lack of specific studies makes this a difficult complication to examine. Prediction scores are currently available to try and mark the likely occurrence of this complication, but these are not calibrated to large studies nor do they comment on the aetiology of this complication (and hence causal underpinning in those presenting with this complication). Ultimately, it has been suggested that further research is needed to determine whether the application of such risk scores in the clinical setting leads to improved outcomes (Huen & Parika, 2012).The aim of this study is to follow outcomes of surgery (including adverse outcomes) and both individual and profiled metabolites to try and (a) predict outcomes of surgery and (b) identify biological pathways potential contributing to these events.
Summary of Results
Working with Professor Dunn (previously University of Birmingham Phenome Centre) we initiated Mass Spectrometry data collection in order to derived metabolomic profiles on OMACS patients (https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fu2790089.ct.sendgrid.net%2Fls%2Fclick%3Fupn%3DXv3JSvJ-2B3M71ppf7N9agbUbT4HxfZR04UBHuM3eC9-2FvbQD4ByFZFJXAR8duCde50USpFXCcP83-2B6VVB-2BMNXyGDmLRSyBLzdsDfQC1iAL5n8xR26eU2VFzKcjyKjpBu0P-MYR_E1aO2-2BZlVOSJJV-2FajQqskegTd6IRomHYTi-2Fbt8SH3YIW0W2laAuCtRNH1Wtraswo5W47QNju5t2HpoQH7TCbuD2pZ4MmH4rSI5Xl5o0wUcrHxJEb5u3FiqzfHnSHOV3zwAvgPQ4-2FLaia8MTXsGu-2FafX5NB-2B4naq0VONmlWyHFNtJyV-2FzOad453ZJc9Ex-2BuPGZXkMCcrMj2MUkcogJNdpuQ-3D-3D&data=05%7C01%7Capprovals%40hra.nhs.uk%7C87364c6baaf945c2a62b08dad20fe17e%7C8e1f0acad87d4f20939e36243d574267%7C0%7C0%7C638053262889222870%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=JFjNsJv%2FF8L0YQ%2FMQrK4l8CjVLAEV9uCUZ7nJE2r3yg%3D&reserved=0 The study objective was to define metabolic changes related to AKI onset following cardiac surgery in a small human cohort to define a predictive metabolite panel of AKI to be applied prior to cardiac surgery using pre-operative urine samples and to define a predictive metabolite panel of AKI to be applied after cardiac surgery using post-operative plasma/serum samples. The sampling for this work includes the collection of urine prior to surgery (pre-op) and plasma/serum collected post-surgery (2hr post-surgery EDTA). These samples were then available for untargeted metabolomics applied to both sample types. Analysis was run on the pilot data generated by this project. Results illustrated an association between measured metabolites and AKI status in patients going through surgery. Of particular interest, these results are those taken from the analysis of urinary samples before surgery. The performance of prediction from metabolic data was sufficient to justify a followup examination of a larger sample set which has allowed the collection of labelled metabolite data. Analyses with both of these data sets is currently underway.REC name
North West - Preston Research Ethics Committee
REC reference
19/NW/0101
Date of REC Opinion
20 Feb 2019
REC opinion
Favourable Opinion