Predictors of death and dialysis in severe AKI: the UPHS-AKI cohort

Clin J Am Soc Nephrol. 2013 Apr;8(4):527-37. doi: 10.2215/CJN.06450612. Epub 2012 Dec 20.

Abstract

Background and objectives: AKI carries a substantial risk of mortality, even after adjustment for comorbidities. Effective risk stratification may lead to more effective therapeutic interventions for high-risk subgroups.

Design, setting, participants, & measurements: This study identified adults who suffered severe in-hospital AKI from January 1, 2004 to August 31, 2010 at three hospitals in the University of Pennsylvania Health System (UPHS). Patients were included if baseline creatinine was ≤1.4 mg/dl for men or ≤1.2 mg/dl for women, and serum creatinine doubled during the hospital admission. Cox proportional hazards models predicting death, dialysis, or a combined endpoint of death or dialysis were fit using data from patients admitted to the Hospital of the University of Pennsylvania (n=4263), and validated at the two other UPHS facilities (n=758, n=1098).

Results: In adjusted analyses, strong predictors of the combined endpoint included intensive care unit location (versus floor), medical service, liver disease, higher creatinine, greater rate of change in creatinine, and greater number of pressor medications. Higher absolute creatinine concentration was associated with greater use of dialysis, but lower overall mortality in adjusted analyses. Harrell's c-index (95% confidence interval) for the model predicting the combined endpoint was 0.85 (0.84-0.86) in the derivation cohort, and 0.83 (0.80-0.86) and 0.84 (0.82-0.86) in the validation cohorts.

Conclusions: A small group of easily measured clinical factors has good ability to predict mortality and dialysis in severe AKI.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Acute Kidney Injury / mortality*
  • Acute Kidney Injury / therapy*
  • Adult
  • Aged
  • Aged, 80 and over
  • Cohort Studies
  • Comorbidity
  • Creatinine / blood
  • Female
  • Hospitals, University / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Pennsylvania / epidemiology
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Renal Dialysis / mortality*
  • Risk Factors
  • Severity of Illness Index*

Substances

  • Creatinine