Diagnosis and Management of Acute Kidney Injury

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 5566

Special Issue Editors

Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China
Interests: kidney; transplantation; immunology; fibrosis; kidney injury
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Guest Editor
1. Department of Cardiovascular Sciences, University Hospitals of Leicester, University of Leicester, Leicester, UK
2. Nantong-Leicester Joint Institute of Kidney Science, Department of Nephrology, Affiliated Hospital of Nantong University, Nantong, China
Interests: apoptosis; phagocytosis; inflommation; innate immunity and repair

Special Issue Information

Dear Colleagues,

Acute kidney injury (AKI) is a worldwide burden in our health care system. It occurs in about 13.3 million people per year, 85% of whom live in developing countries. Unfortunately, AKI is thought to contribute to about 1.7 million deaths every year, and, no specific prediction and treatment method is available so far. In 2015, the International Society of Nephrology initiated the “0by25” slogan for AKI (zero preventable deaths by 2025). With the development of diagnostic technology, we can detect AKI as early as serval hours. In animal models, various gene and cell therapies demonstrate exciting results. However, there are still so many issues that need to be solved in basic and clinic. In this Special Issue, we focus on AKI diagnosis and management. We welcome high-quality original basic, clinical and translational research, reviews and case reports. The topics are included but are not limited to:

  1. Novel biomarkers of AKI;
  2. New non-invasive diagnosis technology of AKI;
  3. Systemic or new management of AKI in clinic.
  4. New findings on AKI mechanisms;
  5. Novel therapy on AKI in translational studies.

Dr. Cheng Yang
Prof. Dr. Bin Yang
Guest Editors

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Published Papers (3 papers)

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Research

12 pages, 2856 KiB  
Article
Eplet-Predicted Antigens: An Attempt to Introduce Eplets into Unacceptable Antigen Determination and Calculated Panel-Reactive Antibody Calculation Facilitating Kidney Allocation
by Wenrui Wu, Huanxi Zhang, Jinghong Tan, Qian Fu, Jun Li, Chenglin Wu, Huiting Huang, Bowen Xu, Liuting Ling, Longshan Liu, Xiaojun Su and Changxi Wang
Diagnostics 2022, 12(12), 2983; https://doi.org/10.3390/diagnostics12122983 - 28 Nov 2022
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Abstract
(1) Calculated panel-reactive antibody (CPRA) is a measure of sensitization based on unacceptable antigens (UAs). Determination of UAs based on single-antigen bead assays at allele or antigen levels may be inappropriate. We aimed to introduce eplets for better assessment of sensitization; (2) 900 [...] Read more.
(1) Calculated panel-reactive antibody (CPRA) is a measure of sensitization based on unacceptable antigens (UAs). Determination of UAs based on single-antigen bead assays at allele or antigen levels may be inappropriate. We aimed to introduce eplets for better assessment of sensitization; (2) 900 recipients and 1427 donors were enrolled for candidate or donor pools, respectively. Eplets were from the HLA Epitope Registry. UAs were determined by anti-HLA antibodies identified using LIFECODES Single Antigen (LSA) kits. CPRA values were calculated using a simplified method of donor filtering; (3) HLA antigens containing all eplets of an HLA antigen in LSA kits (LSA antigen) were defined as eplet-predicted (EP) antigens, the reactivity of which could be predicted by that LSA antigen. High reactivity concordance was found between LSA and EP antigens. More HLA antigens were covered by EP antigens in the population than LSA antigens. CPRA values at the EP level were higher than at the allele level and lower than at the antigen level. The EP antigens facilitated UA determination for non-LSA antigens and avoided acute rejection; (4) UA determination using EP antigens can lead to more accurate assessment of sensitization, enabling a high probability of compatible organs and a low risk of adverse outcomes. Full article
(This article belongs to the Special Issue Diagnosis and Management of Acute Kidney Injury)
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17 pages, 6605 KiB  
Article
Predicting Progression of Kidney Injury Based on Elastography Ultrasound and Radiomics Signatures
by Minyan Zhu, Lumin Tang, Wenqi Yang, Yao Xu, Xiajing Che, Yin Zhou, Xinghua Shao, Wenyan Zhou, Minfang Zhang, Guanghan Li, Min Zheng, Qin Wang, Hongli Li and Shan Mou
Diagnostics 2022, 12(11), 2678; https://doi.org/10.3390/diagnostics12112678 - 03 Nov 2022
Cited by 2 | Viewed by 1905
Abstract
Background: Shear wave elastography ultrasound (SWE) is an emerging non-invasive candidate for assessing kidney stiffness. However, its prognostic value regarding kidney injury is unclear. Methods: A prospective cohort was created from kidney biopsy patients in our hospital from May 2019 to June 2020. [...] Read more.
Background: Shear wave elastography ultrasound (SWE) is an emerging non-invasive candidate for assessing kidney stiffness. However, its prognostic value regarding kidney injury is unclear. Methods: A prospective cohort was created from kidney biopsy patients in our hospital from May 2019 to June 2020. The primary outcome was the initiation of renal replacement therapy or death, while the secondary outcome was eGFR < 60 mL/min/1.73 m2. Ultrasound, biochemical, and biopsy examinations were performed on the same day. Radiomics signatures were extracted from the SWE images. Results: In total, 187 patients were included and followed up for 24.57 ± 5.52 months. The median SWE value of the left kidney cortex (L_C_median) is an independent risk factor for kidney prognosis for stage 3 or over (HR 0.890 (0.796–0.994), p < 0.05). The inclusion of 9 out of 2511 extracted radiomics signatures improved the prognostic performance of the Cox regression models containing the SWE and the traditional index (chi-square test, p < 0.001). The traditional Cox regression model had a c-index of 0.9051 (0.8460–0.9196), which was no worse than the machine learning models, Support Vector Machine (SVM), SurvivalTree, Random survival forest (RSF), Coxboost, and Deepsurv. Conclusions: SWE can predict kidney injury progression with an improved performance by radiomics and Cox regression modeling. Full article
(This article belongs to the Special Issue Diagnosis and Management of Acute Kidney Injury)
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14 pages, 1342 KiB  
Article
The Association of Organ Preservation Fluid Pathogens with Early Infection-Related Events after Kidney Transplantation
by Jianming Li, Xiaojun Su, Jianyi Li, Wenrui Wu, Chenglin Wu, Penghao Guo, Kang Liao, Qian Fu, Jun Li, Longshan Liu and Changxi Wang
Diagnostics 2022, 12(9), 2248; https://doi.org/10.3390/diagnostics12092248 - 18 Sep 2022
Cited by 4 | Viewed by 1615
Abstract
(1) Background: The need to elucidate the microbial patterns in preservation fluid and explore their relationship with early infection-related events post kidney transplant and investigate antimicrobial resistance and the effects of preemptive antibiotic therapy. (2) Methods: This retrospective study analyzed the clinical data [...] Read more.
(1) Background: The need to elucidate the microbial patterns in preservation fluid and explore their relationship with early infection-related events post kidney transplant and investigate antimicrobial resistance and the effects of preemptive antibiotic therapy. (2) Methods: This retrospective study analyzed the clinical data of 514 kidney transplant donors and 808 recipients from April 2015 to October 2020. Clinical data of donor and recipient characteristics, preservation fluid microbes, early infections (≤30 days), probable donor-derived infections (P-DDIs), antimicrobial resistance and preemptive antibiotic therapy was collected. (3) Results: The incidence of bloodstream (10.3% versus 5.2%, p = 0.006) and graft-site infections (9.7% versus 4.6%, p = 0.004) was significantly higher in recipients with culture-positive preservation fluid. In addition, recipients with ESKAPE pathogens or Candida species had a notably higher rate of bloodstream infections (14.1% versus 6.9%, p = 0.033) and graft-site infections (16.7% versus 3.5%, p < 0.01) than those with other positive pathogens. Preemptive antibiotic therapy decreased the bloodstream infection rate (11.8% versus 35.7%, p = 0.047) when preservation fluid was positive for ESKAPE pathogens. (4) Conclusions: Culture-positive preservation fluid has potential implications for kidney transplant recipients. ESKAPE pathogens or Candida species in preservation fluid as well as their antimicrobial resistance properties and non-preemptive antibiotic therapy could pose a risk of early infection-related events. Full article
(This article belongs to the Special Issue Diagnosis and Management of Acute Kidney Injury)
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