Abstract
BackgroundAcute kidney injury (AKI) is common among intensive care unit (ICU) patients. AKI is highly heterogeneous, with variable links to poor outcomes. Current approaches to classify AKI severity and identify patients at highest risk for poor outcomes focus on the maximum change in serum creatinine (SCr) values. However, these scores are hampered by the need for a reliable baseline SCr value and the absence of a component differentiating transient from persistent rises in SCr. We hypothesized that identification of resolving or nonresolving AKI subphenotypes based on the early trajectory of SCr values in the ICU would better differentiate patients at risk of hospital mortality.MethodsWe performed a secondary analysis of two prospective studies of ICU patients admitted to a trauma ICU (group 1; n = 1914) or general medical-surgical ICUs (group 2; n = 1867). In group 1, we tested definitions for resolving and nonresolving AKI subphenotypes and selected the definitions resulting in subphenotypes with the greatest separation in risk of death relative to non-AKI controls. We applied this definition to group 2 and tested whether the subphenotypes were independently associated with hospital mortality after adjustment for AKI severity.ResultsAKI occurred in 46% and 69% of patients in groups 1 and 2, respectively. In group 1, a resolving AKI subphenotype (defined as a decrease in SCr of 0.3 mg/dl or 25% from maximum in the first 72 h of study enrollment) was associated with a low risk of death. A nonresolving AKI subphenotype (defined as all AKI cases not meeting the “resolving” definition) was associated with a high risk of death. In group 2, the resolving AKI subphenotype was not associated with increased mortality (relative risk [RR] 0.86, 95% CI 0.63–1.17), whereas the nonresolving AKI subphenotype was associated with higher mortality (RR 1.68, 95% CI 1.15–2.44) even after adjustment for AKI severity stage.ConclusionsThe trajectory of SCr levels identifies AKI subphenotypes with different risks for death, even among AKI cases of similar severity. These AKI subphenotypes might better define the patients at risk for poor outcomes who might benefit from novel interventions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13054-016-1546-4) contains supplementary material, which is available to authorized users.
Highlights
Acute kidney injury (AKI) is common among intensive care unit (ICU) patients
The dataset included subjects at risk for acute respiratory distress syndrome (ARDS) enrolled from ICUs as part of the Molecular Epidemiology of Acute Respiratory Distress Syndrome (MEA) at the Massachusetts General Hospital [11] and subjects with ARDS enrolled by the National Heart, Lung, and Blood Institute (NHLBI) ARDS Network [12,13,14,15]
Similar to our findings in group 1, we found that mortality was higher for patients with a nonresolving AKI subphenotype (26%) than for those with a resolving AKI subphenotype (13%), and mortality for both was numerically higher than that observed for subjects without AKI (11%)
Summary
Acute kidney injury (AKI) is common among intensive care unit (ICU) patients. AKI is highly heterogeneous, with variable links to poor outcomes. Current approaches to classify AKI severity and identify patients at highest risk for poor outcomes focus on the maximum change in serum creatinine (SCr) values These scores are hampered by the need for a reliable baseline SCr value and the absence of a component differentiating transient from persistent rises in SCr. We hypothesized that identification of resolving or nonresolving AKI subphenotypes based on the early trajectory of SCr values in the ICU would better differentiate patients at risk of hospital mortality. The KDIGO group classifies patients from stage 0 (no AKI) to stage 3 AKI, based on maximum change in SCr or minimum urine output throughout the hospital stay This definition for AKI includes a broad range of underlying pathophysiologic processes that would be expected to have different risks for poor clinical outcomes and may need to be treated differently. These limitations of the current AKI definition hamper the ability to better understand the pathophysiology of AKI and, potentially, the identification of effective novel therapies [1]
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