Objective: This study aimed to evaluate the potential effect of hyperhomocysteinemia on multiple organ failure (MOF) in patients with acute pancreatitis (AP).
Method: In this cohort study, a total of 1880 AP patients were enrolled and divided into the hyperhomocysteinemia group (study group) and the control group based on serum homocysteine (HCY) levels. Clinical data including demographics, clinical outcomes, and characteristics were collected for analysis. Risk factors of MOF in AP patients were determined by univariate and multivariate logistic regression analyses.
Results: The hyperhomocysteinemia group showed higher multiple organ failure rates (31.83% vs 20.77%, < 0.001), compared with the control group. A positive correlation between homocysteine level and APACHE II score was obtained by Pearson correlation analysis ( = 0.420, < 0.001), compared with the control group. A positive correlation between homocysteine level and APACHE II score was obtained by Pearson correlation analysis ( < 0.001), compared with the control group. A positive correlation between homocysteine level and APACHE II score was obtained by Pearson correlation analysis (.
Conclusion: A high serum homocysteine level may be an independent risk factor of multiple organ failure in patients with acute pancreatitis.
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http://dx.doi.org/10.1155/2020/6960497 | DOI Listing |
Med Phys
January 2025
Center for Virtual Imaging Trial, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.
Background: This Special Report summarizes the 2022, AAPM grand challenge on Truth-based CT image reconstruction.
Purpose: To provide an objective framework for evaluating CT reconstruction methods using virtual imaging resources consisting of a library of simulated CT projection images of a population of human models with various diseases.
Methods: Two hundred unique anthropomorphic, computational models were created with varied diseases consisting of 67 emphysema, 67 lung lesions, and 66 liver lesions.
Heliyon
January 2025
Centre for Agricultural Genomics and Biotechnology, University of Debrecen, Debrecen, 4032, Hungary.
Heat stress has been proven to cause negative effects on livestock leading to lower productivity and economic value. Understanding how heat stress manifests within an animal's body is the first step in devising a heat stress mitigation strategy; transcriptomic studies are one of the methods used. Here, using a systematic literature review methodology, we examine the recent decade of transcriptomics' application to the study of livestock adaptation.
View Article and Find Full Text PDFWorld Allergy Organ J
January 2025
Institute of Life Science, Chongqing Medical University, Chongqing, China.
Background: Allergic rhinitis (AR) is a common chronic respiratory disease that can lead to the development of various other conditions. Although genetic risk loci associated with AR have been reported, the connections between these loci and AR comorbidities or other diseases remain unclear.
Methods: This study conducted a phenome-wide association study (PheWAS) using known AR risk loci to explore the impact of known AR risk variants on a broad spectrum of phenotypes.
Oncol Lett
March 2025
Gansu Province Key Laboratory of Environmental Oncology, Lanzhou University Second Hospital, Lanzhou, Gansu 730000, P.R. China.
The atypical expression of immune phenotypes in lymphoma is often associated with a poor prognosis and presents diagnostic challenges. The present study reports on a rare extranodal NK/T cell lymphoma. In addition to typical morphology and immunohistochemical characteristics, these tumors strongly express CD20 and CD30 and partially express CD15, which is associated with aggressive clinical behavior.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
Technology Park of Sardinia, Bioecopest Srl, SP 55 Km 8.400, Tramariglio, Alghero, SS, Italy.
Background: The increasing availability of sequenced genomes has enabled comparative analyses of various organisms. Numerous tools and online platforms have been developed for this purpose, facilitating the identification of unique features within selected organisms. However, choosing the most appropriate tools can be unclear during the initial stages of analysis, often requiring multiple attempts to match the specific characteristics of the data.
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