Objective: To observe the effect of artificial liver support system (ALSS) after liver transplantation on the survival rate of severe hepatitis patients.
Methods: Patients with severe hepatitis with model for end stage liver disease (MELD) score above 35 were divided into two groups according to whether pre-transplantation ALSS was instituted (n=23) or not (n=41). Evaluation was performed on the day when the patient entered into the waiting list and 1 day pre-transplantation. Survival rates and survival curves were estimated with Kaplan-Meier method. Log-Rank test for trends was used when comparing curves.
Results: There was no significant difference between two groups when comparing the parameters including prothrombin time, fibrinogen, total bilirubin, blood ammonia, creatinine, MELD score on the day of entering into the waiting list (all P>0.05). After the therapy of ALSS, the parameters of ALSS group were significantly improved comparing to those of the control group (all P<0.01). MELD score of ALSS group on the day pre-transplant was decreased significantly comparing to that on the day entering into the waiting list (37.6+/-2.0 vs. 41.4+/-2.2, P<0.01), with the difference in MELD score (DeltaMELD) of -3.8. MELD score of control group on the day entering into the waiting list and 1 day pre-transplant was 40.6+/-1.7 and 41.0+/-1.6 respectively, with DeltaMELD of +0.4 ( P>0.05). The blood loss and operation time in ALSS group was significantly less than the control group [(4 070.0+/-688.1) ml vs. (4 905.9+/-1 142.1) ml, (9.4+/-1.1) hours vs. (10.5+/-1.0) hours, P<0.05 and P<0.01). Thirty days and 1 year survival rate of ALSS group was 91% and 82%, and that of control group was 76% and 59% respectively (P=0.044).
Conclusion: ALSS can improve the survival rate of patients with severe hepatitis undergoing liver transplantation through ameliorating physiological status, lessening blood loss during operation and operation time.
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Zhonghua Kou Qiang Yi Xue Za Zhi
January 2025
Department of Stomatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology & School of Stomatology, Tongji Medical College, Huazhong University of Science and Technology & Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration, Wuhan 430022, China.
To investigate the effects of artificial light at night on the growth of mandibles in mice and its regulatory mechanisms. A mouse model of artificial light at night (night light pollution group) and normal lighting (normal light group) was established by controlling light exposure time, with 4 mice in each group. Micro-CT was employed to analyze the differences in bone quantities of the mandibles between the two groups.
View Article and Find Full Text PDFJ Hepatol
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China. Electronic address:
Background & Aims: Accurate multi-classification is the prerequisite for reasonable management of focal liver lesions (FLLs). Ultrasound is the common image examination, but lacks accuracy. Contrast enhanced ultrasound (CEUS) offers better performance, but highly relies on experience.
View Article and Find Full Text PDFClin Gastroenterol Hepatol
January 2025
Department of Computer Science and Numerical Analysis, University of Córdoba, Córdoba, Spain. Campus Universitario de Rabanales, Albert Einstein Building. Ctra. N-IV, Km. 396. 14071, Córdoba, Spain; Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Córdoba, Spain. Av. Menéndez Pidal, s/n, Poniente Sur, 14004 Córdoba, Spain.
Background & Aims: We aimed to develop and validate an artificial intelligence score (GEMA-AI) to predict liver transplant (LT) waiting list outcomes using the same input variables contained in existing models.
Methods: Cohort study including adult LT candidates enlisted in the United Kingdom (2010-2020) for model training and internal validation, and in Australia (1998-2020) for external validation. GEMA-AI combined international normalized ratio, bilirubin, sodium, and the Royal Free Glomerular Filtration Rate in an explainable Artificial Neural Network.
Front Artif Intell
January 2025
National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
The rapid advancement of artificial intelligence (AI) has introduced transformative opportunities in oncology, enhancing the precision and efficiency of tumor diagnosis and treatment. This review examines recent advancements in AI applications across tumor imaging diagnostics, pathological analysis, and treatment optimization, with a particular focus on breast cancer, lung cancer, and liver cancer. By synthesizing findings from peer-reviewed studies published over the past decade, this paper analyzes the role of AI in enhancing diagnostic accuracy, streamlining therapeutic decision-making, and personalizing treatment strategies.
View Article and Find Full Text PDFFront Cell Infect Microbiol
January 2025
Department of Critical Care Medicine, Xinxiang Medical University, Henan Provincial People's Hospital, Zhengzhou, China.
Objective: Severe community-acquired pneumonia (sCAP) is one of the major diseases within the ICU. We hypothesize that subtyping sCAP based on simple inflammatory markers, organ dysfunction, and clinical metagenomics results is feasible.
Method: In this study, we retrospectively enrolled immunocompetent sCAP patients requiring invasive mechanical ventilation, who underwent clinical metagenomics from 17 medical centers.
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