Background: Predicting multiple organ dysfunction (MOD) in the late phase of critical illnesses is essential. Cytokines are considered biomarkers that can predict clinical outcomes; however, their predictive value for late-phase MOD is unknown. This study aimed to identify the biomarker with the highest predictive value for late-phase MOD.
Methods: This observational study prospectively evaluated data on adult patients with systemic inflammatory response syndrome, those who presented to the emergency department or were admitted to intensive care units in five tertiary hospitals (n = 174). Seven blood biomarkers levels (interleukin-6 [IL-6], IL-8, IL-10, tumor-necrosis factor-α, white blood cells, C-reactive protein, and procalcitonin) were measured at three timepoints (days 0, 1, and 2). The area under the receiver operating characteristic curve (AUC) was analyzed to evaluate predictive values for MOD (primary outcome, MOD on day 7 [late-phase]; secondary outcome, MOD on day 3 [early-phase]).
Results: Of the measured 7 biomarkers, blood IL-6 levels on day 2 had the highest predictive value for MOD on day 7 using single timepoint data (AUC 0.825, 95% confidence interval [CI] 0.754-0.879). Using three timepoint biomarkers, blood IL-6 levels had the highest predictive value of MOD on day 7 (AUC 0.838, 95% CI 0.768-0.890). Blood IL-6 levels using three timepoint biomarkers had also the highest predictive value for MOD on day 3 (AUC 0.836, 95% CI 0.766-0.888).
Conclusion: Of the measured biomarkers, blood IL-6 levels had the highest predictive value for MOD on days 3 and 7. Blood IL-6 levels predict early- and late-phase MOD in critically ill patients.
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http://dx.doi.org/10.1097/SHK.0000000000001678 | DOI Listing |
Front Immunol
January 2025
Environmental Factors in Degenerative Diseases Research Group. Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain.
Introduction: The envelope proteins syncytin-1 and pHERV-W from the Human Endogenous Retroviral family 'W' (HERV-W) have been identified as potential risk factors in multiple sclerosis (MS). This study aims to evaluate both humoral and cell-mediated immune response to antigenic peptides derived from these proteins across different clinical forms and inflammatory phases of MS.
Methods: Indirect enzyme-linked immunosorbent assay (ELISA) was employed to measure immunoglobulin G (IgG) responses to syncytin-1 and pHERV-W peptides in MS patients.
Front Oncol
January 2025
Medical Imaging Center, The First Hospital of Kunming, Kunming, China.
Objective: The invasiveness of pituitary neuroendocrine tumor is an important basis for formulating individualized treatment plans and improving the prognosis of patients. Radiomics can predict invasiveness preoperatively. To investigate the value of multiparameter magnetic resonance imaging (mpMRI) radiomics in predicting pituitary neuroendocrine tumor invasion into the cavernous sinus (CS) before surgery.
View Article and Find Full Text PDFBiochem Res Int
January 2025
Department of Animal Nutrition, Veterinary College and Research Institute, Tamil Nadu Veterinary and Animal Sciences University, Chennai, Tamil Nadu, India.
Members of the genus are the conventional medicinal plants used in the therapeutic management of numerous ailments, especially for their antioxidant and pharmacological activities. The crude extract of was profiled using high-resolution GC-MS and LC-MS/MS techniques to determine possible bioactive compounds that are vital to the antioxidant activity. A total of 52 and 63 bioactive compounds have been detected in GC-MS chromatograms using different solvents (methanol and ethanol) in leaf extracts, representing the presence of certain bioactive compounds.
View Article and Find Full Text PDFFront Oral Health
January 2025
Department of Microbiology, Virology and Immunology, Poltava State Medical University, Poltava, Ukraine.
Unlabelled: Today, about 15.0% of odontogenic pathology is caused by (). The aim of the study was to predict the development of antimicrobial resistance of based on retrospective data.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Software Engineering, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Saudi Arabia.
The prediction of energy consumption in households is essential due to the reliance on electrical appliances for daily activities. Accurate assessment of energy demand is crucial for effective energy generation, preventing overloads and optimizing energy storage. Traditional techniques have limitations in accuracy and error rates, necessitating advancements in prediction techniques.
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