High incidence of renal failure requiring short-term dialysis: a prospective observational study

QJM. 2002 Sep;95(9):585-90. doi: 10.1093/qjmed/95.9.585.

Abstract

Background: Previous estimates of incidence of acute renal failure (ARF) requiring renal replacement therapy have varied from 18 to 75 patients per million per year, but have been beset by problems of definition.

Aim: To investigate whether the '90-day rule' provides a more reliable, reproducible and robust estimate of the need for short-term dialysis.

Setting: District general hospital serving a population of 147 000.

Design: Prospective observational study.

Methods: Patients who received renal replacement therapy in Dumfries and Galloway between 01/01/94 and 31/12/2000 were divided into two groups: long-term dialysis (> or =90 days) and short-term dialysis (<90 days).

Results: Of 302 patients, 193 received short-term dialysis, giving an incidence for short-term dialysis of 187 patient episodes per million per year (95%CI 170-203). Use of a more conventional definition for ARF (including all ARF and acute-on-chronic renal failure, but excluding patients with chronic renal failure who present acutely) produced a similar estimate at 176 patients per million per year (95%CI 160-193).

Discussion: The 90-day rule estimated the incidence of short-term dialysis/ARF at nearly twice the incidence of chronic renal failure requiring dialysis, and more than twice the most recent estimate of the incidence of ARF in the UK. The main attraction of the 90-day rule is its simplicity. If the high level of short-term dialysis/ARF found in our study is confirmed by other centres, there are significant resource implications for the provision of renal care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Kidney Injury / epidemiology
  • Acute Kidney Injury / therapy*
  • Adult
  • Aged
  • Aged, 80 and over
  • Female
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Prospective Studies
  • Renal Dialysis / methods
  • Renal Dialysis / statistics & numerical data*
  • Scotland / epidemiology