Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes-Reference-Cited by-同舟云学术

Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes

Published:2023-03-28 Issue:6 Volume:18 Page:716-726
ISSN:1555-9041
Container-title:Clinical Journal of the American Society of Nephrology
language:en
Short-container-title:CJASN

Author:

Vasquez-Rios George¹^ORCID,Oh Wonsuk²³,Lee Samuel⁴^ORCID,Bhatraju Pavan⁵⁶,Mansour Sherry G.⁷,Moledina Dennis G.⁷^ORCID,Gulamali Faris F.²³^ORCID,Siew Edward D.⁸,Garg Amit X.⁹,Sarder Pinaki¹⁰,Chinchilli Vernon M.¹¹,Kaufman James S.¹²,Hsu Chi-yuan¹³^ORCID,Liu Kathleen D.¹³,Kimmel Paul L.¹⁴,Go Alan S.¹⁵,Wurfel Mark M.⁶,Himmelfarb Jonathan⁵,Parikh Chirag R.¹⁶^ORCID,Coca Steven G.¹^ORCID,Nadkarni Girish N.¹²³

Affiliation:

1. Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York

2. Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York

3. Division of Data-Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, New York

4. Icahn School of Medicine at Mount Sinai, New York, New York

5. Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, Seattle, Washington

6. Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, Washington

7. Section of Nephrology, Yale University School of Medicine, New Haven, Connecticut

8. Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee

9. Division of Nephrology, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada

10. Department of Biomedical Engineering, SUNY Buffalo, Buffalo, New York

11. Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania

12. Division of Nephrology, Veterans Affairs New York Harbor Healthcare System and New York University School of Medicine, New York, New York

13. Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California

14. Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland

15. Kaiser Permanente Northern California, Oakland, California

16. Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland

Abstract

Background AKI is a heterogeneous syndrome. Current subphenotyping approaches have only used limited laboratory data to understand a much more complex condition. Methods We focused on patients with AKI from the Assessment, Serial Evaluation, and Subsequent Sequelae in AKI (ASSESS-AKI). We used hierarchical clustering with Ward linkage on biomarkers of inflammation, injury, and repair/health. We then evaluated clinical differences between subphenotypes and examined their associations with cardiorenal events and death using Cox proportional hazard models. Results We included 748 patients with AKI: 543 (73%) of them had AKI stage 1, 112 (15%) had AKI stage 2, and 93 (12%) had AKI stage 3. The mean age (±SD) was 64 (13) years; 508 (68%) were men; and the median follow-up was 4.7 (Q1: 2.9, Q3: 5.7) years. Patients with AKI subphenotype 1 (N=181) had the highest kidney injury molecule (KIM-1) and troponin T levels. Subphenotype 2 (N=250) had the highest levels of uromodulin. AKI subphenotype 3 (N=159) comprised patients with markedly high pro–brain natriuretic peptide and plasma tumor necrosis factor receptor-1 and -2 and low concentrations of KIM-1 and neutrophil gelatinase–associated lipocalin. Finally, patients with subphenotype 4 (N=158) predominantly had sepsis-AKI and the highest levels of vascular/kidney inflammation (YKL-40, MCP-1) and injury (neutrophil gelatinase–associated lipocalin, KIM-1). AKI subphenotypes 3 and 4 were independently associated with a higher risk of death compared with subphenotype 2 and had adjusted hazard ratios of 2.9 (95% confidence interval, 1.8 to 4.6) and 1.6 (95% confidence interval, 1.01 to 2.6, P = 0.04), respectively. Subphenotype 3 was also independently associated with a three-fold risk of CKD and cardiovascular events. Conclusions We discovered four AKI subphenotypes with differing clinical features and biomarker profiles that are associated with longitudinal clinical outcomes.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Transplantation,Nephrology,Critical Care and Intensive Care Medicine,Epidemiology

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