Acute kidney injury adjusted to volume status in critically ill patients: recognition of delayed diagnosis, restaging, and associated outcomes

Critically ill patients receive a significant amount of fluids leading to a positive fluid balance; this dilutes serum creatinine resulting in an overestimated glomerular filtration rate. The goal of our study is to identify undiagnosed or underestimated acute kidney injury (AKI) in the intensive care unit (ICU). It will also identify the morbidity and mortality associated with an underestimated AKI. We reviewed records of patients admitted to our institution (Staten Island University Hospital) between 2012 and 2013 for more than 2 days. Patients with end stage renal disease were excluded. AKI was defined using the Acute Kidney Injury Network criteria. The following formula was used to identify and restage patients with AKI: adjusted creatinine = serum creatinine × [(hospital admission weight (kg) 0.6 + Σ (daily cumulative fluid balance (L))/hospital admission weight × 0.6]. The primary outcome identified newly diagnosed AKI and those who were restaged. The secondary outcome identified associated morbidities. Seven-hundred and thirty-three out of 1,982 ICU records reviewed, were used. Two-hundred and fifty-seven (mean age 69.8±14.9) had AKI, out of which 15.9% were restaged using the equation. Comparison of mean by Student’s t-test showed no difference between patients who were restaged. Similarly, chi-square revealed no differences between both arms, except mean admission weight (lower in patients who were restaged), fluid balance on days 1, 2, and 3 (higher in the restaged arm), and the presence of congestive heart failure (more prevalent in the restaged arm). Of note, the mean cost of stay was US$150,562.82 vs $197,174.63 for same stage vs restaged, respectively, however, without statistical significance (P=0.74). Applying the adjustment equation showed a modest (15.9%) increase in the AKI staging slightly impacting outcomes (mortality, length, and cost of stay) without statistical significance.