Background: The adoption of extended criteria for donors remains the best strategy to widen the pool of available liver graft against the chronic shortage of donors. Benchmarking in liver transplantation (LT) offers the unprecedented opportunity to compare clinical outcome measures to a set of validated reference values. We aimed to evaluate the impact of marginal grafts usage in a cohort of low-risk benchmark cases from an area with a very low rate of deceased donation.
Methods: A cohort of low-risk benchmark cases was identified from all adult patients who underwent LT at our center. Among these patients, those transplanted with a graft from an extended-criteria donor (ECD) were identified. Benchmark metrics (length of hospital and intensive care unit stay, incidences of mortality, graft loss, and postoperative complication) were compared with benchmark cutoffs and between the 2 groups.
Results: Two hundred forty-five patients satisfied the inclusion criteria, 146 (60%) of whom received an organ from an ECD. Overall, all benchmark metrics where within the cutoffs limits, except for graft loss (14% vs 11%) and mortality (10% vs 9% 1 year after LT). The ECD group was associated with more grade III complications (60% vs 45%, P = .031), graft loss (18% vs 8%, P = .038), and mortality (14% vs 4%, P = .009). Hepatocellular carcinoma diagnosis was found to be associated with less mortality (odds ratio = 0.42, P = .048).
Conclusion: While ECD graft usage is associated with slightly worse prognosis, our experience suggests that their use can be considered safe, especially when matched on hepatocellular carcinoma recipients.
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http://dx.doi.org/10.1016/j.transproceed.2020.02.050 | DOI Listing |
Nature
January 2025
Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
Missense variants that change the amino acid sequences of proteins cause one-third of human genetic diseases. Tens of millions of missense variants exist in the current human population, and the vast majority of these have unknown functional consequences. Here we present a large-scale experimental analysis of human missense variants across many different proteins.
View Article and Find Full Text PDFNat Commun
January 2025
Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA.
The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To enable technology developers along with research and clinical laboratories to evaluate variant detection on male sex chromosomes X and Y, we create a small variant benchmark set with 111,725 variants for the Genome in a Bottle HG002 reference material. We develop an active evaluation approach to demonstrate the benchmark set reliably identifies errors in challenging genomic regions and across short and long read callsets.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
BioEngineering Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.
Cross-species single-cell RNA-seq data hold immense potential for unraveling cell type evolution and transferring knowledge between well-explored and less-studied species. However, challenges arise from interspecific genetic variation, batch effects stemming from experimental discrepancies and inherent individual biological differences. Here, we benchmarked nine data-integration methods across 20 species, encompassing 4.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Computer and Electronic Information, Guangxi University, University Road, Nanning, 530004, Guangxi, China. Electronic address:
Vision-language navigation (VLN) is a challenging task that requires agents to capture the correlation between different modalities from redundant information according to instructions, and then make sequential decisions on visual scenes and text instructions in the action space. Recent research has focused on extracting visual features and enhancing text knowledge, ignoring the potential bias in multi-modal data and the problem of spurious correlations between vision and text. Therefore, this paper studies the relationship structure between multi-modal data from the perspective of causality and weakens the potential correlation between different modalities through cross-modal causality reasoning.
View Article and Find Full Text PDFFront Bioeng Biotechnol
December 2024
School of Information Engineering, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Introduction: Accurate image segmentation is crucial in medical imaging for quantifying diseases, assessing prognosis, and evaluating treatment outcomes. However, existing methods often fall short in integrating global and local features in a meaningful way, failing to give sufficient attention to abnormal regions and boundary details in medical images. These limitations hinder the effectiveness of segmentation techniques in clinical settings.
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