Acute kidney injury (AKI) is serious and complicates up to 1 in 7 hospital admissions. It is usually diagnosed from rapidly deteriorating blood tests. Much of the focus of clinical research into AKI has been on strategies to improve recognition and timely intervention. However, emerging evidence suggests that even when people survive AKI, they remain at an elevated risk of poor long-term outcomes. The aim of this thesis was to determine which people with AKI have an ongoing increased risk of poor outcomes (mortality, kidney failure, recurrent illness episodes) after hospital discharge. The design was a population-based data-linkage cohort study involving the Grampian Laboratory Outcomes Morbidity and Mortality Study (GLOMMS-II). Data linkages included population biochemistry, hospital episode data, mortality records, intensive care records and renal registry data from 1999-2013. A cohort of 17,630 people hospitalised in 2003 were followed through to 2013. Outcomes were mortality, progression of kidney disease and unplanned hospital readmission episodes. There have been several novel research outputs. I evaluated and adapted international AKI criteria for use in large population biochemistry datasets. I developed a clinical risk prediction model for unplanned readmissions after hospital discharge, for which AKI was a strong independent predictor. I described long-term survival after AKI, showing that people with AKI (vs no AKI) have a substantially higher risk of death in the first year, but diminishing excess risk thereafter. Finally, I conducted a novel analysis of renal prognosis after AKI, showing that mortality and non-recovery are more common than subsequent renal progression after AKI, but that renal progression is nevertheless increased after AKI. Overall, AKI is a serious condition and marker of people who have a long lasting poorer prognosis. The first year after discharge is a period of particularly heightened risk that could potentially be targeted with initiatives to improve care.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:742370 |
| Date | January 2017 |
| Creators | Sawhney, Simon Amrit |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=236457 |
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