The influence of acute kidney injury on the outcome of Stevens-Johnson syndrome and toxic epidermal necrolysis: The prognostic value of KDIGO staging.

Abstract

BACKGROUND:Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), and SJS/TEN overlap syndrome are severe drug-induced cutaneous adverse reactions with high mortality. Acute kidney injury (AKI) was a common complication in an SJS/TEN group and noted as an independent risk factor for mortality in patients with SJS/TEN. To determine whether AKI staging can predict the outcome of patients with SJS/TEN, we compared the discriminative power of an AKI KDIGO staging system with that of SCROTEN, APACHE II, APACHE III, and SOFA. MATERIALS AND METHODS:We retrospectively analyzed the data of 75 patients who were diagnosed with SJS, TEN, or SJS/TEN overlap syndrome at a tertiary care university hospital between January 1, 2011 and December 31, 2014. The baseline characteristics, biochemical analysis data, medication use, and outcomes of the patients were assessed, and the discriminative ability for predicting mortality was determined for each prognostic model. RESULTS:Of the 75 patients, 23 (30.7%) had AKI, of whom 13 (56.5%) died during the index admission. Of the prognostic risk models analyzed, the KDIGO staging system showed similar discriminative ability in predicting in-hospital mortality as did the other models. In addition, combining KDIGO with other scoring systems yielded significantly more accurate risk prediction for in-hospital mortality compared with the other individual scores alone, as measured by net reclassification index. The patients with KDIGO stages 2 and 3 exhibited a significantly lower 1-year survival rate than did those with KDIGO stages 0 and 1. CONCLUSION:AKI KDIGO staging has good discriminative ability and is easy to utilize for predicting mortality.