Kidney Week

Abstract: TH-PO004

Derivation of a Prediction Model for Emergency Department AKI

Session Information

• AKI: Epidemiology, Risk Factors, Prevention
  October 25, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Acute Kidney Injury

• 101 AKI: Epidemiology, Risk Factors, and Prevention

Authors

• Foxwell, David A., Cardiff University School of Medicine, Cardiff, United Kingdom

David A. Foxwell,

• Pradhan, Sara, Cardiff University School of Medicine, Cardiff, United Kingdom

Sara Pradhan,

• Zouwail, Soha, University Hospital of Wales, Cardiff, United Kingdom

Soha Zouwail,

• Rainer, Timothy Hudson, Cardiff University School of Medicine, Cardiff, United Kingdom

Timothy Hudson Rainer,

• Phillips, Aled O., Cardiff University School of Medicine, Cardiff, United Kingdom

Aled O. Phillips,

Background

Acute Kidney Injury (AKI) is an independent risk factor for death. Over 50% of community acquired AKI cases are identified in the Emergency Department (ED), which is the main route for acute hospital admissions. Accurate risk stratification is essential to facilitate prompt medical investigation and treatment. This study aimed to derive a hospital front-door model for predicting AKI in the ED (ED-AKI).

Methods

Between April and August 2016 20,421 adult patients attended the ED of a University Teaching Hospital in Wales and had a serum creatinine measurement. A retrospective analysis was conducted on 1119 cases (548 incident ED-AKI patients and 571 randomly selected non-AKI ED patients). Univariate and stepwise backwards removal of insignificant variables in a multivariate analyses were used to derive a pragmatic model for predicting and risk-stratifying AKI. The primary outcome was ED-AKI.

Results

An 18-point model using four variables was derived for assessing patients on ED arrival, where 0 is low chance of ED-AKI and 18 a high chance. The adjusted odds ratios for AKI were: age 1.03; male gender 1.45; known Chronic Kidney Disease 2.08; and number of comorbidities (from 0 to 10) 1.31. At a score of >2, the sensitivity was 99.8% (95%CI 99.0-11.0), and specificity was 5.1% (95%CI 3.4-7.2). At a score of >5.5, the sensitivity was 85.8% (95%CI 82.6-88.6), and specificity was 52.7% (95%CI 48.5-56.9). At a score of >11, the sensitivity was 15.0% (95%CI 12.1-18.2), and specificity was 96.5% (95%CI 94.6-97.8). The probability of AKI increased with score groups (chi-squared <0.0001). The AUROC was 0.745 (95%CI 0.720-0.772; p<0.0001; R² 18%). There were positive correlations between the score and peak creatinine (r=0.415; p<0.0001) but not with AKI stage.

Conclusion

A simple, pragmatic 18-point score for predicting probability of ED-AKI on ED arrival has been derived. This now requires refinement and prospective validation.