It is critical to find fast and robust biomarkers for sepsis to reduce the patient's risk for morbidity and mortality. In this work, we compared serum protein expression levels of regenerating islet-derived protein 3 gamma (REG3A) between patients with sepsis and healthy controls and found that serum REG3A protein was significantly elevated in patients with sepsis. In addition, expression level of serum REG3A protein was markedly correlated with the Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, and C-reactive protein levels of patients with sepsis. Serum REG3A protein expression level was also confirmed to have good diagnostic value to differentiate patients with sepsis from healthy controls. Finally, serum REG3A protein expression level was found to have good prognostic value to predict the 28-day survival rate of patients with sepsis. In conclusion, our work indicated that serum REG3A may be a novel biomarker for sepsis.
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http://dx.doi.org/10.1016/j.amjcard.2022.11.036 | DOI Listing |
Mol Oncol
January 2025
Department of Gastrointestinal Cancer Translational Research, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China.
Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide, with gastrectomy being the primary treatment option. Sepsis, a systemic inflammatory response to infection, may influence tumor growth by creating an immunosuppressive environment conducive to cancer cell proliferation and metastasis. Here, the effect of abdominal infection on tumor growth and metastasis was investigated through the implementation of a peritoneal metastasis model and a subcutaneous tumor model.
View Article and Find Full Text PDFClin Transl Sci
January 2025
Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
This study aimed to develop and validate a nomogram based on lymphocyte subtyping and clinical factors for the early and rapid prediction of Intra-abdominal candidiasis (IAC) in septic patients. A prospective cohort study of 633 consecutive patients diagnosed with sepsis and intra-abdominal infection (IAI) was performed. We assessed the clinical characteristics and lymphocyte subsets at the onset of IAI.
View Article and Find Full Text PDFZoonoses Public Health
January 2025
Infectious Diseases Branch, Division of Communicable Disease Control, Center for Infectious Diseases, California Department of Public Health, Sacramento, California, USA.
Introduction: Capnocytophaga is a genus of bacteria that are commensal to the oral microbiome of humans and some animals. Some Capnocytophaga species are found in the human oral cavity and rarely cause disease in people; the species found in animals are zoönotic and can be transmitted to people via saliva. This study describes the clinical and epidemiologic features of patients from whom Capnocytophaga spp.
View Article and Find Full Text PDFRev Panam Salud Publica
January 2025
Infectious Diseases Unit Hospital Carlos G. Durand Buenos Aires Argentina Infectious Diseases Unit, Hospital Carlos G. Durand, Buenos Aires, Argentina.
Objective: To conduct a point prevalence survey (PPS) of antibiotic use in the main pediatric tertiary-level hospital in Panama City to establish antibiotic prevalence and identify key areas for addressing antimicrobial resistance.
Methods: This point prevalence survey (PPS) conducted in a tertiary-level hospital in Panama followed the Pan American Health Organization's adaptation of the methodology proposed by the World Health Organization for PPSs on antibiotic use. Information obtained included patients' demographic characteristics, antimicrobial prescriptions, indication for antimicrobial use, and prescription's adherence to guidelines.
Front Med (Lausanne)
January 2025
Hepatobiliary Pancreatic Surgery Department, Huadu District People's Hospital of Guangzhou, Guangzhou, China.
Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population. This study compared the performance of traditional logistic regression and machine learning models in predicting adult sepsis mortality.
Objective: To develop an optimum model for predicting the mortality of adult sepsis patients based on comparing traditional logistic regression and machine learning methodology.
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