title: Maximising Acute Kidney Injury Alerts--A Cross-Sectional Comparison with the Clinical Diagnosis.
abstract: BACKGROUND
  Acute kidney injury (AKI) is serious and widespread across healthcare (1 in 7 hospital admissions) but recognition is often delayed causing avoidable harm. Nationwide automated biochemistry alerts for AKI stages 1-3 have been introduced in England to improve recognition. We explored how these alerts compared with clinical diagnosis in different hospital settings.
  
  
  METHODS
  We used a large population cohort of 4464 patients with renal impairment. Each patient had case-note review by a nephrologist, using RIFLE criteria to diagnose AKI and chronic kidney disease (CKD). We identified and staged AKI alerts using the new national NHS England AKI algorithm and compared this with nephrologist diagnosis across hospital settings.
  
  
  RESULTS
  Of 4464 patients, 525 had RIFLE AKI, 449 had mild AKI, 2185 had CKD (without AKI) and 1305 were of uncertain chronicity. NHS AKI algorithm criteria alerted for 90.5% of RIFLE AKI, 72.4% of mild AKI, 34.1% of uncertain cases and 14.0% of patients who actually had CKD.The algorithm identified AKI particularly well in intensive care (95.5%) and nephrology (94.6%), but less well on surgical wards (86.4%). Restricting the algorithm to stage 2 and 3 alerts reduced the over-diagnosis of AKI in CKD patients from 14.0% to 2.1%, but missed or delayed alerts in two-thirds of RIFLE AKI patients.
  
  
  CONCLUSIONS
  Automated AKI detection performed well across hospital settings, but was less sensitive on surgical wards. Clinicians should be mindful that restricting alerts to stages 2-3 may identify fewer CKD patients, but including stage 1 provides more sensitive and timely alerting.
authors.affiliation: University of Aberdeen Applied Renal Research Collaboration, Aberdeen, United Kingdom; NHS Grampian, Aberdeen, United Kingdom.
authors.forename: Simon
authors.initials: S
authors.lastname: Sawhney
authors.affiliation: University of Aberdeen Applied Renal Research Collaboration, Aberdeen, United Kingdom; NHS Grampian, Aberdeen, United Kingdom.
authors.forename: Angharad
authors.initials: A
authors.lastname: Marks
authors.affiliation: King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
authors.forename: Tariq
authors.initials: T
authors.lastname: Ali
authors.affiliation: NHS Grampian, Aberdeen, United Kingdom.
authors.forename: Laura
authors.initials: L
authors.lastname: Clark
authors.affiliation: NHS Grampian, Aberdeen, United Kingdom.
authors.forename: Nick
authors.initials: N
authors.lastname: Fluck
authors.affiliation: University of Aberdeen Applied Renal Research Collaboration, Aberdeen, United Kingdom.
authors.forename: Gordon J
authors.initials: GJ
authors.lastname: Prescott
authors.affiliation: NHS Grampian, Aberdeen, United Kingdom.
authors.forename: William G
authors.initials: WG
authors.lastname: Simpson
authors.affiliation: University of Aberdeen Applied Renal Research Collaboration, Aberdeen, United Kingdom.
authors.forename: Corri
authors.initials: C
authors.lastname: Black
mesh_terms: D058186:Acute Kidney Injury / Q000175:diagnosis*; D000368:Aged; D000465:Algorithms; D003404:Creatinine / Q000097:blood*; D003422:Critical Care / Q000379:methods; D003430:Cross-Sectional Studies; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis; D012606:Scotland; D012720:Severity of Illness Index
chemical_list: D003404:Creatinine