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Aim: To assess the performance of proposed scores specific for acute-on-chronic liver failure in predicting short-term mortality among patients with alcoholic hepatitis.
Methods: We retrospectively collected data from 264 patients with clinically diagnosed alcoholic hepatitis from January to December 2013 at 21 academic hospitals in Korea. The performance for predicting short-term mortality was calculated for Chronic Liver Failure-Sequential Organ Failure Assessment (CLIF-SOFA), CLIF Consortium Organ Failure score (CLIF-C OFs), Maddrey's discriminant function (DF), age, bilirubin, international normalized ratio and creatinine score (ABIC), Glasgow Alcoholic Hepatitis Score (GAHS), model for end-stage liver disease (MELD), and MELD-Na.
Results: Of 264 patients, 32 (12%) patients died within 28 d. The area under receiver operating characteristic curve of CLIF-SOFA, CLIF-C OFs, DF, ABIC, GAHS, MELD, and MELD-Na was 0.86 (0.81-0.90), 0.89 (0.84-0.92), 0.79 (0.74-0.84), 0.78 (0.72-0.83), 0.81 (0.76-0.86), 0.83 (0.78-0.88), and 0.83 (0.78-0.88), respectively, for 28-d mortality. The performance of CLIF-SOFA had no statistically significant differences for 28-d mortality. The performance of CLIF-C OFs was superior to that of DF, ABIC, and GAHS, while comparable to that of MELD and MELD-Na in predicting 28-d mortality. A CLIF-SOFA score of 8 had 78.1% sensitivity and 79.7% specificity, and CLIF-C OFs of 10 had 68.8% sensitivity and 91.4% specificity for predicting 28-d mortality.
Conclusion: CLIF-SOFA and CLIF-C OF scores performed well, with comparable predictive ability for short-term mortality compared to the commonly used scoring systems in patients with alcoholic hepatitis.
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http://dx.doi.org/10.3748/wjg.v22.i41.9205 | DOI Listing |
J Hazard Mater
September 2025
Chemometrics and Molecular Modeling Laboratory, Department of Chemistry and Physics, Kean University,1000 Morris Avenue, Union, NJ 07083, USA. Electronic address:
The Toxic Substances Control Act (TSCA) mandates the U.S. EPA to monitor all chemicals used in the country, over 86,000 to date, posing a major challenge for comprehensive toxicity testing.
View Article and Find Full Text PDFJ Nutr
September 2025
School of Medicine and Allied Health Sciences, University of The Gambia, Banjul, The Gambia; Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250
Background: Red and processed meat consumption is extensively linked to chronic disease risk in observational studies, with robust meta-analyses demonstrating significant positive associations for colorectal, breast, endometrial, and lung cancers, type 2 diabetes (T2DM), cardiovascular disease (CVD), and all-cause mortality. Dose-response relationships indicate elevated risks even at moderate intakes. Moreover, processed meats consistently show stronger detrimental effects than unprocessed red meats.
View Article and Find Full Text PDFAm J Med Sci
September 2025
The George Washington University School of Medicine and Health Sciences, Washington, DC.
Background: In transcatheter aortic valve replacement (TAVR), there is a notable "diabetes discrepancy", where worse/better/similar outcomes were all found for patients with diabetes mellitus (DM). Such divergent findings pose a challenge for clinicians to accurately assess the risks for DM patients undergoing TAVR. We hypothesized the presence of chronic complications could be linked to worse post-TAVR outcomes in DM patients.
View Article and Find Full Text PDFEnviron Int
September 2025
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
Sichuan Basin (SCB) is a critical region in China facing the dual pressures of air pollution and population aging. This study constructed high resolution (1 km) PM datasets for SCB using advanced machine learning approaches - Super Resolution Generative Adversarial Networks (SRGAN) and Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM). Evaluation results demonstrate good performance of the machine learning model (SRGAN: R = 0.
View Article and Find Full Text PDFRev Esp Anestesiol Reanim (Engl Ed)
September 2025
Department of Anaesthesia and Critical Care, Hospital Universitario Infanta Leonor, Madrid, Spain; Universidad Complutense de Madrid, Madrid, Spain; Spanish Perioperative Audit and Research Network, Zaragoza, Spain.
Introduction/objectives: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality. While Enhanced Recovery After Surgery (ERAS) programs optimize perioperative care, their effect on oncologic prognosis requires further validation. This study evaluates ERAS adherence and five-year survival through a post-hoc analysis of the POWER Study.
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