title: Impact of routine reporting of estimated glomerular filtration rate using the CKD-EPI formula in a community population: A cross-sectional cohort study.
abstract: OBJECTIVE
  Most laboratories are moving to report estimated glomerular filtration rates (eGFR) using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula. However, data on the prevalence of chronic kidney disease (CKD) in the population and its economic impact have to date been modelled using data derived from the modification of diet in renal disease (MDRD) equation. Evaluating the impact of CKD-EPI on prevalence has important implications for referral patterns and health expenditure.
  
  
  METHODS
  eGFR were calculated from 2 295313 creatinine results from 833334 patients using the MDRD and CKD-EPI formulae. The proportion of patients in each CKD stage was determined and annual rates of change of eGFR in patients assigned to a new CKD stage compared with their previous CKD stage calculated. The effects of age on eGFR were assessed.
  
  
  RESULTS
  Reporting of eGFR using the CKD-EPI equation reduced the prevalence of CKD stages III-V from 9.2% to 7.6%. A total of 181126 patients were reclassified using CKD-EPI with 171298 changing to a better CKD stage. Reclassification rates were highest in CKD stages II and III. Patients reclassified from stage III to II tended to be younger or female. eGFR declines rapidly after the age of 60.
  
  
  CONCLUSIONS
  Introduction of routine eGFR reporting using the CKD-EPI formula will reduce the population prevalence of CKD. CKD-EPI reporting better identifies patients at risk of further decline in renal function. Improvement in the classification should reduce unnecessary costs related to surveillance and referral. The impact of ageing on renal function should be appreciated.
authors.affiliation: Renal Unit, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.
authors.forename: Tim
authors.initials: T
authors.lastname: Mitchell
authors.forename: Narelle
authors.initials: N
authors.lastname: Hadlow
authors.forename: Aron
authors.initials: A
authors.lastname: Chakera
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D018450:Disease Progression; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007668:Kidney / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015876:Northern Territory / Q000453:epidemiology; D011237:Predictive Value of Tests; D015995:Prevalence; D011379:Prognosis; D051436:Renal Insufficiency, Chronic / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology* / Q000503:physiopathology; D012189:Retrospective Studies; D012307:Risk Factors; D012737:Sex Factors; D013997:Time Factors; D014904:Western Australia / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D003404:Creatinine
keywords: ageing; chronic renal failure; classification; eGFR; prevalence