Kidney Week

Abstract: SA-OR015

Plasma Biomarkers to Identify Patients at Increased Risk of CKD Following an Episode of AKI

Session Information

• AKI: Risk Factors, Biomarkers, and Predictors
  November 09, 2019 | Location: Salon C, Walter E. Washington Convention Center
  Abstract Time: 05:18 PM - 05:30 PM

Category: Acute Kidney Injury

• 102 AKI: Clinical, Outcomes, and Trials

Authors

• Selby, Nicholas M., University of Nottingham, Nottingham, United Kingdom

Nicholas M. Selby, MBBS, MD

Dr Selby studied medicine at the University of Nottingham, UK, graduating in 1998, and after completing post-graduate training in the East Midlands was appointed a full-time NHS consultant nephrologist at the Royal Derby Hospital in 2009. In 2015 he was appointed Associate Professor of Nephrology at the University of Nottingham, based in the Centre for Kidney Research and Innovation (www.nottingham.ac.uk/research/groups/renal Twitter:@CKRIresearch), Royal Derby Hospital Postgraduate Medical School. Dr. Selby is a clinical academic with primary interests in Acute Kidney Injury (AKI), Magnetic Resonance Imaging (MRI) of the kidney and the haemodynamic consequences of dialysis. He led the development of one of the first e-alert systems for AKI in the UK and is CI on several investigator-instigated studies in these areas including the Tackling AKI study. Since 2011 Dr Selby has been awarded peer reviewed grant funding from NIHR, MRC, the Health Foundation, Kidney Research UK and British Renal Society. He has published over 75 peer-reviewed articles. Dr Selby has several national AKI roles, including leadership of the AKI Clinical Study Group that sits within the UK Kidney Research Consortium, the co-chair of the UK Renal Imaging Network and programme board of the NHS England ‘Think Kidneys’ programme.

• Hutchinson, Michelle, University of Leeds, Leeds, United Kingdom

Michelle Hutchinson,

• Packington, Rebecca A., University Hospitals of Derby and Burton, Derby, United Kingdom

Rebecca A. Packington,

• McCole, Eibhlin M., Randox Teoranta, Donnegal, Ireland

Eibhlin M. McCole,

• Kurth, Mary Jo, Randox Laboratories Ltd, Antrim, United Kingdom

Mary Jo Kurth,

• Richardson, Ciaran, Randox Teoranta, Donnegal, Ireland

Ciaran Richardson,

• Fitzgerald, Peter, Randox Laboratories Ltd, Antrim, United Kingdom

Peter Fitzgerald,

• Banks, Rosamonde Elizabeth, University of Leeds, Leeds, United Kingdom

Rosamonde Elizabeth Banks,

Background

The long-term sequelae of acute kidney injury (AKI) on renal function and mortality are increasingly appreciated, but there remains the need for prospective studies to develop strategies to identify those at greatest risk. We aimed to test whether biomarkers improve prediction of long-term outcomes of AKI.

Methods

In a single centre, participants were identified using a hospital-wide electronic AKI detection system. Plasma samples were collected at 3months after hospitalisation and a panel of 14 biomarkers were measured using a multiplex biochip array method. This was done firstly in a discovery cohort (112 AKI patients) with the most promising markers assayed in the remaining 388 AKI patients (validation cohort). Measures of renal function, proteinuria and survival were assessed at 1 and 3 years. CKD progression was defined as ≧25% decline in eGFR from baseline (pre-AKI) with a decline in eGFR stage.

Results

Median age was 70yrs (IQR 14), AKI episodes were predominantly stage 1 with median duration 3 days (IQR 3) and 29% had pre-existing CKD. There was no difference in age, gender or smoking status between discovery and validation cohorts. The proportion of AKI patients with CKD progression was 21% and 22% at year 1 and 3 respectively. Mortality was 4.3% at year 1 and 15.8% at year 3. Clinical factors associated with CKD progression included eGFR at 3months, albuminuria, severity and duration of AKI.
In the discovery cohort, four markers were associated with CKD progression, including NGAL and cystatin C. Multiplexed models were developed to include biomarkers and clinical variables; when the models derived in the discovery cohort were applied to the validation cohort, AUC’s improved e.g. AUC of best performing model in validation cohort 0.81 (95% CI 0.75 to 0.87) to discriminate those with CKD progression at 1 year.

Conclusion

Non-recovery of renal function is common following AKI, even in a general hospital population with predominantly AKI stage 1. We present data evaluating the utility of a panel of biomarkers to identify those at highest risk.

Funding

• Private Foundation Support