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Barreto EF, Cerda J, Freshly B, Gewin L, Kwong YD, McCoy IE, Neyra JA, Ng JH, Silver SA, Vijayan A, Abdel-Rahman EM. Optimum Care of AKI Survivors Not Requiring Dialysis after Discharge: An AKINow Recovery Workgroup Report. Kidney360 2024; 5:124-132. [PMID: 37986185 PMCID: PMC10833609 DOI: 10.34067/kid.0000000000000309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 11/08/2023] [Indexed: 11/22/2023]
Abstract
AKI survivors experience gaps in care that contribute to worse outcomes, experience, and cost.Challenges to optimal care include issues with information transfer, education, collaborative care, and use of digital health tools.Research is needed to study these challenges and inform optimal use of diagnostic and therapeutic interventions to promote recovery AKI affects one in five hospitalized patients and is associated with poor short-term and long-term clinical and patient-centered outcomes. Among those who survive to discharge, significant gaps in documentation, education, communication, and follow-up have been observed. The American Society of Nephrology established the AKINow taskforce to address these gaps and improve AKI care. The AKINow Recovery workgroup convened two focus groups, one each focused on dialysis-independent and dialysis-requiring AKI, to summarize the key considerations, challenges, and opportunities in the care of AKI survivors. This article highlights the discussion surrounding care of AKI survivors discharged without the need for dialysis. On May 3, 2022, 48 patients and multidisciplinary clinicians from diverse settings were gathered virtually. The agenda included a patient testimonial, plenary sessions, facilitated small group discussions, and debriefing. Core challenges and opportunities for AKI care identified were in the domains of transitions of care, education, collaborative care delivery, diagnostic and therapeutic interventions, and digital health applications. Integrated multispecialty care delivery was identified as one of the greatest challenges to AKI survivor care. Adequate templates for communication and documentation; education of patients, care partners, and clinicians about AKI; and a well-coordinated multidisciplinary posthospital follow-up plan form the basis for a successful care transition at hospital discharge. The AKINow Recovery workgroup concluded that advancements in evidence-based, patient-centered care of AKI survivors are needed to improve health outcomes, care quality, and patient and provider experience. Tools are being developed by the AKINow Recovery workgroup for use at the hospital discharge to facilitate care continuity.
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Affiliation(s)
| | - Jorge Cerda
- Division of Nephrology, Department of Medicine, Albany Medical College, Albany, New York
| | | | - Leslie Gewin
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Y. Diana Kwong
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California
| | - Ian E. McCoy
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California
| | - Javier A. Neyra
- Division of Nephrology, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Jia H. Ng
- Division of Kidney Diseases and Hypertension, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Great Neck, New York
| | - Samuel A. Silver
- Division of Nephrology, Kingston Health Sciences Center, Queen's University, Kingston, Ontario, Canada
| | - Anitha Vijayan
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Emaad M. Abdel-Rahman
- Division of Nephrology, Department of Medicine, University of Virginia, Charlottesville, VA
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Kwong YD, Hsu CY. In CKD, once-daily empagliflozin reduced progression of kidney disease or CV death at 2 y. Ann Intern Med 2023; 176:JC26. [PMID: 36877974 DOI: 10.7326/j23-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/08/2023] Open
Abstract
SOURCE CITATION EMPA-KIDNEY Collaborative Group; Herrington WG, Staplin N, Wanner C, et al. Empagliflozin in patients with chronic kidney disease. N Engl J Med. 2023;388:117-27. 36331190.
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Affiliation(s)
- Y Diana Kwong
- University of California, San Francisco, San Francisco, California, USA (Y.D.K., C.H.)
| | - Chi-Yuan Hsu
- University of California, San Francisco, San Francisco, California, USA (Y.D.K., C.H.)
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3
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Kwong YD, Liu KD, Hsu RK. Kidney Dysfunction After Acute Heart Failure: Is Acute Kidney Disease the New Acute Kidney Injury? Kidney Int Rep 2021; 7:378-380. [PMID: 35257051 PMCID: PMC8897667 DOI: 10.1016/j.ekir.2021.12.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Y. Diana Kwong
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Kathleen D. Liu
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
- Division of Critical Care Medicine, Department of Anesthesia, University of California, San Francisco, San Francisco, California, USA
| | - Raymond K. Hsu
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
- Correspondence: Raymond K. Hsu, Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
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Kwong YD, Mehta KM, Miaskowski C, Zhuo H, Yee K, Jauregui A, Ke S, Deiss T, Abbott J, Kangelaris KN, Sinha P, Hendrickson C, Gomez A, Leligdowicz A, Matthay MA, Calfee CS, Liu KD. Using best subset regression to identify clinical characteristics and biomarkers associated with sepsis-associated acute kidney injury. Am J Physiol Renal Physiol 2020; 319:F979-F987. [PMID: 33044866 PMCID: PMC7792692 DOI: 10.1152/ajprenal.00281.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/24/2020] [Accepted: 10/07/2020] [Indexed: 12/23/2022] Open
Abstract
Sepsis-associated acute kidney injury (AKI) is a complex clinical disorder associated with inflammation, endothelial dysfunction, and dysregulated coagulation. With standard regression methods, collinearity among biomarkers may lead to the exclusion of important biological pathways in a single final model. Best subset regression is an analytic technique that identifies statistically equivalent models, allowing for more robust evaluation of correlated variables. Our objective was to identify common clinical characteristics and biomarkers associated with sepsis-associated AKI. We enrolled 453 septic adults within 24 h of intensive care unit admission. Using best subset regression, we evaluated for associations using a range of models consisting of 1-38 predictors (composed of clinical risk factors and plasma and urine biomarkers) with AKI as the outcome [defined as a serum creatinine (SCr) increase of ≥0.3 mg/dL within 48 h or ≥1.5× baseline SCr within 7 days]. Two hundred ninety-seven patients had AKI. Five-variable models were found to be of optimal complexity, as the best subset of five- and six-variable models were statistically equivalent. Within the subset of five-variable models, 46 permutations of predictors were noted to be statistically equivalent. The most common predictors in this subset included diabetes, baseline SCr, angiopoetin-2, IL-8, soluble tumor necrosis factor receptor-1, and urine neutrophil gelatinase-associated lipocalin. The models had a c-statistic of ∼0.70 (95% confidence interval: 0.65-0.75). In conclusion, using best subset regression, we identified common clinical characteristics and biomarkers associated with sepsis-associated AKI. These variables may be especially relevant in the pathogenesis of sepsis-associated AKI.
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Affiliation(s)
- Y Diana Kwong
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California
| | - Kala M Mehta
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California
| | - Christine Miaskowski
- Department of Physiological Nursing, University of California, San Francisco, California
| | - Hanjing Zhuo
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Kimberly Yee
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Alejandra Jauregui
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Serena Ke
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Thomas Deiss
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Jason Abbott
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Kirsten N Kangelaris
- Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, California
| | - Pratik Sinha
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Carolyn Hendrickson
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Antonio Gomez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Aleksandra Leligdowicz
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Michael A Matthay
- Cardiovascular Research Institute, Department of Medicine and Department of Anesthesia, University of California, San Francisco, California
| | - Carolyn S Calfee
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California
| | - Kathleen D Liu
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California
- Division of Critical Care Medicine, Department of Anesthesia, University of California, San Francisco, California
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Kwong YD, Liu KD, Hsu RK, Johansen KL, McCulloch CE, Seth D, Fallahzadeh MK, Grimes BA, Ku E. Recovery of Kidney Function Among Patients With Glomerular Disease Starting Maintenance Dialysis. Am J Kidney Dis 2020; 77:303-305. [PMID: 32771649 DOI: 10.1053/j.ajkd.2020.06.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 06/03/2020] [Indexed: 11/11/2022]
Affiliation(s)
- Y Diana Kwong
- Division of Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA.
| | - Kathleen D Liu
- Division of Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA; Division of Critical Care Medicine, Department of Anesthesia, University of California at San Francisco School of Medicine, San Francisco, CA
| | - Raymond K Hsu
- Division of Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA
| | - Kirsten L Johansen
- Division of Nephrology, Hennepin Healthcare, University of Minnesota Minneapolis, MN; Department of Medicine, University of Minnesota Minneapolis, MN
| | - Charles E McCulloch
- Department of Epidemiology and Biostatistics, University of California at San Francisco School of Medicine, San Francisco, CA
| | - Divya Seth
- Division of Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA
| | - Mohammad Kazem Fallahzadeh
- Division of Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA
| | - Barbara A Grimes
- Department of Epidemiology and Biostatistics, University of California at San Francisco School of Medicine, San Francisco, CA
| | - Elaine Ku
- Division of Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA; Department of Epidemiology and Biostatistics, University of California at San Francisco School of Medicine, San Francisco, CA; Division of Pediatric Nephrology, Department of Medicine, University of California at San Francisco School of Medicine, San Francisco, CA
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