Utilization of Small Changes in Serum Creatinine with Clinical Risk Factors to Assess the Risk of AKI in Critically lll Adults

Abstract

Background and objectives Disease biomarkers require appropriate clinical context to be used effectively. Combining clinical risk factors, in addition to small changes in serum creatinine, has been proposed to improve the assessment of AKI. This notion was developed in order to identify the risk of AKI early in a patient's clinical course. We set out to assess the performance of this combination approach.Design, setting, participants, & measurements A secondary analysis of data from a prospective multicenter intensive care unit cohort study (September 2009 to April 2010) was performed. Patients at high risk using this combination approach were defined as an early increase in serum creatinine of 0.1-0.4 mg/dl, depending on number of clinical factors predisposing to AKI. AKI was defined and staged using the Acute Kidney Injury Network criteria. The primary outcome was evolution to severe AKI (Acute Kidney Injury Network stages 2 and 3) within 7 days in the intensive care unit.Results Of 506 patients, 214 (42.2%) patients had early creatinine elevation and were deemed at high risk for AKI. This group was more likely to subsequently develop the primary endpoint (16.4% versus 1.0% [not at high risk], P,0.001). The sensitivity of this grouping for severe AKI was 92%, the specificity was 62%, the positive predictive value was 16%, and the negative predictive value was 99%. After adjustment for Sequential Organ Failure Assessment score, serum creatinine, and hazard tier for AKI, early creatinine elevation remained an independent predictor for severe AKI (adjusted relative risk, 12.86; 95% confidence interval, 3.52 to 46.97). Addition of early creatinine elevation to the best clinical model improved prediction of the primary outcome (area under the receiver operating characteristic curve increased from 0.75 to 0.83, P,0.001). ConclusionCritically ill patients at high AKI risk, based on the combination of clinical factors and early creatinine elevation, are significantly more likely to develop severe AKI. As initially hypothesized, the high-risk combination group methodology can be used to identify patients at low risk for severe AKI in whom AKI biomarker testing may be expected to have low yield. The high risk combination group methodology could potentially allow clinicians to optimize biomarker use.

A Simple Scoring Method for Predicting the Low Risk of Persistent Acute Kidney Injury in Critically Ill Adult Patients

“…The condition component was determined based on a multivariable logistic regression analysis including the following risk factors: older age, diabetes mellitus, cardiovascular disease, chronic kidney disease (CKD), hypertension, morbid obesity, hyperbilirubinemia, cerebrovascular accident, cancer, high-risk surgery, nephrotoxic drugs, sepsis, and ventilator or vasoactive. We selected these candidate variables according to the previous study 14,15 . Age, CKD, morbid obesity and hyperbilirubinemia were diagnosed based on patients' medical charts including Figure 1.…”

Delayed Nephrology Consultation and High Mortality on Acute Kidney Injury: A Meta-Analysis

“…The term 'subclinical AKI' was introduced, challenging the traditional view that a renal issue is clinically relevant only when a loss of filtration function becomes apparent. Variations in GFR may occur after the initial injury, but before the clinical evidence of rising SCr, which explains why a minimal rise in SCr is often a sign of severe kidney damage [20,22,23] . …”

“…Cruz et al [23] hypothesized a high-risk combination group, in which clinical factors combining small changes in SCr (0.1-0.4 mg/dl) could predict the risk for severe AKI in cases where AKI biomarker testing may be used effectively. In a large heterogeneous multicenter cohort of critically ill adults, they showed that early SCr elevation and risk grouping is a good predictor of severe AKI [23] .…”

“…In a large heterogeneous multicenter cohort of critically ill adults, they showed that early SCr elevation and risk grouping is a good predictor of severe AKI [23] . It can be used as a screening test to identify patients at low risk for severe AKI, in whom AKI biomarker could be expected to have a low yield [23] .…”

Advancing the Use of Clinical Decision Support to Prevent Drug-Associated AKI

“…The idea of a risk model for early detection of drug-associated AKI could be beneficial. We have an understanding of the risk factors for AKI and many likely apply to drug-associated AKI, although this should be confirmed [12,13]. …”