Subphenotypes in acute kidney injury: a narrative review

(2022) 26:251 Vaara et al. Critical Care https://doi.org/10.1186/s13054-022-04121-x Open Access REVIEW Subphenotypes in acute kidney injury: a narrative review Suvi T. Vaara1* , Pavan K. Bhatraju2,3, Natalja L. Stanski4, Blaithin A. McMahon5, Kathleen Liu6, Michael Joannidis7 and Sean M. Bagshaw8 Abstract Acute kidney injury (AKI) is a frequently encountered syndrome especially among the critically ill. Current diagnosis of AKI is based on acute deterioration of kidney function, indicated by an increase in creatinine and/or reduced urine output. However, this syndromic definition encompasses a wide variety of distinct clinical features, varying pathophysiology, etiology and risk factors, and finally very different short- and long-term outcomes. Lumping all AKI together may conceal unique pathophysiologic processes specific to certain AKI populations, and discovering these AKI subphenotypes might help to develop targeted therapies tackling unique pathophysiological processes. In this review, we discuss the concept of AKI subphenotypes, current knowledge regarding both clinical and biomarkerdriven subphenotypes, interplay with AKI subphenotypes and other ICU syndromes, and potential future and clinical implications. Keywords: Acute kidney injury, Biomarkers, Critically ill, Heterogeneity, Latent class analysis, Subphenotypes Background Acute kidney injury (AKI) is a common syndrome in hospitalized populations and especially in the critically ill [1, 2]. It is associated with prolonged hospitalization, receipt of kidney replacement therapy (KRT), persistent loss of kidney function, and death [1–3]. AKI is diagnosed based on clinical features indicating the deterioration of kidney function, namely increased level of serum creatinine and/ or decreased urine output [4]. While the current definition of AKI has enhanced clinical recognition of AKI and promoted critical concepts applicable to AKI populations, combining all patients with AKI into one group may hide sub-groups that are more tightly linked to clinical outcomes [5] and conceal unique pathophysiologic processes specific to certain AKI populations [6]. Supporting this notion, multiple research groups have shown that diversity within the AKI clinical syndrome exists and a ‘one size fits all’ approach may not be ideal [7–10]. Thus, existing heterogeneity within the group of AKI patients may explain why multiple clinical trials have yet to identify effective pharmacotherapy for its prevention or treatment [3, 4, 11]. Furthermore, the efficacy of certain already tested pharmacotherapies may have been concealed by the existing heterogeneity in the trial population and lack of suitable measures to detect improved outcomes [12, 13]. This review aims to describe the concept of subphenotypes in AKI, current knowledge regarding both clinical and biomarker-driven subphenotypes, interplay with the subphenotypes with other ICU syndromes such as acute respiratory distress syndrome (ARDS), and potential future and clinical implications. *Correspondence: 1 Division of Intensive Care Medicine, Department of Anesthesiology, Intensive Care and Pain Medicine, Meilahti Hospital, University of Helsinki and Helsinki University Hospital, PO Box 340, 00290 Helsinki, Finland Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Vaara et al. Critical Care (2022) 26:251 Page 2 of 10 Concept of subphenotypes Among critically ill patients, several syndromic diagnoses (or phenotypes) are recognized, such as AKI [4], ARDS [14], sepsis [15], and delirium. These diagnoses encompass a wide variety of distinct clinical features, varying pathophysiology, etiology, risk factors and clinical course, and finally, very different short- and long-term outcomes. A subphenotype is a distinct group of patients within a phenotype such as AKI who share common features, risk factors, biomarker positivity, response to treatment, or outcomes that separates this subphenotype from other groups of patients within the phenotype [16]. Thus, multiple ways to classify patients into subphenotypes exist (Fig. 1). Severity scoring according to clinical features (such as magnitude of creatinine rise) into subgroups of differing outcomes (such as stage 1 to 3 AKI) [4] has a long tradition in daily clinical practice. However, classifying patients using multiple clinical variables and biomarkers to more specific biologic subphenotypes may better reflect the underlying pathophysiology, facilitate customized approaches to care, and ultimately find targeted therapies. Regardless of the strategy used to subphenotype AKI, the overarching goal should remain the same: to cohort patients into groups with unique prognostic and/or therapeutic implications [17, 18]. Subgrouping patients in this manner is termed enrichment, a central tenet of precision medicine. A general schematic of how subphenotyping can facilitate prognostic enrichment (i.e. identifying patients likely to have a disease-related outcome of interest) and predictive enrichment (i.e. selecting patients more likely to respond to a given therapy on the basis of biology) to personalize AKI management is shown in Fig. 2. Methodological aspects Relatively novel methods to find subphenotypes within phenotypes include clustering methods such as latent class analysis (LCA) and k-means clustering. LCA is a frequently used mixture model that presumes that an unobserved categorical variable exists that classifies the heterogeneous population into mutually exclusive latent classes (homogeneous subgroups) [19]. Observed variables are used to predict the membership of these unobserved or latent groups [19]. As in other types of statistical models, selection of the variables for the model should be carefully considered and be based on the research question. From the fitted LCA model, probabilities of class membership are generated that can then (...truncated)