Background: Despite providing survival benefit, increased risk for infectious disease (IRD) kidney offers are declined at 1.5 times the rate of non-IRD kidneys. Elucidating sources of variation in IRD kidney offer acceptance may highlight opportunities to expand use of these life-saving organs.
Methods: To explore center-level variation in offer acceptance, we studied 6765 transplanted IRD kidneys offered to 187 transplant centers between 2009 and 2017 using Scientific Registry of Transplant Recipients data. We used multilevel logistic regression to determine characteristics associated with offer acceptance and to calculate the median odds ratio (MOR) of acceptance (higher MOR indicates greater heterogeneity).
Results: Higher quality kidneys (per 10 units kidney donor profile index; adjusted odds ratio [aOR], 0.94; 95% confidence interval [CI], 0.92-0.95), higher yearly volume (per 10 deceased donor kidney transplants; aOR, 1.08, 95% CI, 1.06-1.10), smaller waitlist size (per 100 candidates; aOR, 0.97; 95% CI, 0.95-0.98), and fewer transplant centers in the donor service area (per center; aOR, 0.88; 95% CI, 0.85-0.91) were associated with greater odds of IRD acceptance. Adjusting for donor and center characteristics, we found wide heterogeneity in IRD offer acceptance (MOR, 1.96). In other words, if listed at a center with more aggressive acceptance practices, a candidate could be 2 times more likely to have an IRD kidney offer accepted.
Conclusions: Wide national variation in IRD kidney offer acceptance limits access to life-saving kidneys for many transplant candidates.
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http://dx.doi.org/10.1097/TP.0000000000002631 | DOI Listing |
Brief Bioinform
November 2024
School of Engineering, Westlake University, No. 600 Dunyu Road, 310030 Zhejiang, P.R. China.
Single-cell RNA sequencing (scRNA-seq) offers remarkable insights into cellular development and differentiation by capturing the gene expression profiles of individual cells. The role of dimensionality reduction and visualization in the interpretation of scRNA-seq data has gained widely acceptance. However, current methods face several challenges, including incomplete structure-preserving strategies and high distortion in embeddings, which fail to effectively model complex cell trajectories with multiple branches.
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January 2025
Construction Engineering and Utilities Department, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.
Effective construction waste (CW) management, mainly concrete, brick, and steel, is a critical challenge due to its significant environmental and economic impacts. This study addresses this challenge by proposing multiple linear regression models to predict waste generation in residential buildings within the Egyptian construction industry, considering the influence of factors such as building design and site management features. Using data from 25 case studies, the models demonstrated high predictive accuracy, with adjusted R² values of 0.
View Article and Find Full Text PDFZ Evid Fortbild Qual Gesundhwes
January 2025
Department of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH), Bremen, Germany; Faculty of Human and Health Sciences, University of Bremen, Bremen, Germany.
Introduction: The increasing digitalization of the healthcare system makes it possible to provide medical services using digital technologies without direct patient-provider contact. This study aimed to investigate 1) the use and acceptance of video consultation and 2) factors associated with the use of video consultation.
Methods: A cross-sectional online survey was conducted in February 2023.
Food Chem
January 2025
School of Public Health, Hebei Key Laboratory of Occupational Health and Safety for Coal Industry, North China University of Science and Technology, Tangshan 063210, Hebei, China. Electronic address:
Effective and convenient QuEChERS of lipophilic pesticides with wide pK range from strongly pigment-rich food samples remains a great challenge. Here, a ZIF-67 derived magnetic nanoporous carbon (Co@MPC) was firstly proposed for modified QuEChERS of carbamate pesticides (pK 4.3-12.
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January 2025
Kumoh National Institute of Technology, IT convergence engineering, Gumi 39177, Republic of Korea; Kumoh National Institute of Technology, Medical IT convergence engineering, Gumi 39253, Republic of Korea; Meta Heart Inc., Gumi 39253, Republic of Korea. Electronic address:
Background And Objective: Using electrophysiological simulations and machine learning to predict drug proarrhythmia risk has gained popularity due to its effectiveness. The leading in silico drug assessment system mainly uses a single biomarker (qNet) to predict proarrhythmia risk, offering good performance and straightforward interpretation. Other advanced classifiers incorporating additional physiological biomarkers provide better predictive capabilities but are less intuitive.
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