Abstract
Background Early recognition of acute kidney injury (AKI) is important. It frequently develops first in the community. KDIGO-based AKI e-alert criteria may help clinicians recognize AKI in hospitals, but their suitability for application in the community is unknown.
Methods In a large renal cohort (n = 50 835) in one UK health authority, we applied the NHS England AKI ‘e-alert’ criteria to identify and follow three AKI groups: hospital-acquired AKI (HA-AKI), community-acquired AKI admitted to hospital within 7 days (CAA-AKI) and community-acquired AKI not admitted within 7 days (CANA-AKI). We assessed how AKI criteria operated in each group, based on prior blood tests (number and time lag). We compared 30-day, 1- and 5-year mortality, 90-day renal recovery and chronic renal replacement therapy (RRT).
Results In total, 4550 patients met AKI e-alert criteria, 61.1% (2779/4550) with HA-AKI, 22.9% (1042/4550) with CAA-AKI and 16.0% (729/4550) with CANA-AKI. The median number of days since last blood test differed between groups (1, 52 and 69 days, respectively). Thirty-day mortality was similar for HA-AKI and CAA-AKI, but significantly lower for CANA-AKI (24.2, 20.2 and 2.6%, respectively). Five-year mortality was high in all groups, but followed a similar pattern (67.1, 64.7 and 46.2%). Differences in 5-year mortality among those not admitted could be explained by adjusting for comorbidities and restricting to 30-day survivors (hazard ratio 0.91, 95% confidence interval 0.80–1.04, versus hospital AKI). Those with CANA-AKI (versus CAA-AKI) had greater non-recovery at 90 days (11.8 versus 3.5%, P < 0.001) and chronic RRT at 5 years (3.7 versus 1.2%, P < 0.001).
Conclusions KDIGO-based AKI criteria operate differently in hospitals and in the community. Some patients may not require immediate admission but are at substantial risk of a poor long-term outcome.
Original language | English |
---|---|
Pages (from-to) | 922-929 |
Number of pages | 8 |
Journal | Nephrology Dialysis Transplantation |
Volume | 31 |
Issue number | 6 |
Early online date | 7 Apr 2016 |
DOIs | |
Publication status | Published - Jun 2016 |
Keywords
- acute kidney injury
- delivery of health care
- epidemiology
- primary health care
- survival analysis
Fingerprint
Dive into the research topics of 'KDIGO-based acute kidney injury criteria operate differently in hospitals and the community—findings from a large population cohort'. Together they form a unique fingerprint.Profiles
-
Corri Black
- Aberdeen Centre For Health Data Science
- School of Medicine, Medical Sciences & Nutrition, Applied Health Sciences - Personal Chair (Clinical)
- School of Medicine, Medical Sciences & Nutrition, Grampian Data Safe Haven (DaSH)
- School of Medicine, Medical Sciences & Nutrition, Chronic Disease Research Group
- School of Medicine, Medical Sciences & Nutrition, Farr Aberdeen
Person: Clinical Academic
-
Simon Sawhney
- School of Medicine, Medical Sciences & Nutrition, Applied Health Sciences - Senior Clinical Lecturer
- Aberdeen Centre For Health Data Science
- School of Medicine, Medical Sciences & Nutrition, Farr Aberdeen
- School of Medicine, Medical Sciences & Nutrition, Grampian Data Safe Haven (DaSH)
Person: Clinical Academic