Articles: sepsis.
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Every hospital admission is associated with healthcare costs and a risk of adverse events. The need to identify patients who do not require hospitalization has emerged with the profound increase in hospitalization rates due to infectious diseases during the last decades, especially during the COVID-19 pandemic. This study aimed to identify predictors of safe early discharge (SED) in patients presenting to the emergency department (ED) with a suspected infection meeting the Systemic Inflammatory Response Syndrome (SIRS) criteria. ⋯ We developed and validated a model to identify patients with an infection at the ED who can be safely discharged early.
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Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The adoption of the Phoenix sepsis criteria eliminated the Systemic Inflammatory Response Syndrome criteria from the definition of pediatric sepsis. The objective of this study is to derive and validate machine learning models predicting in-hospital mortality for children with suspected or confirmed infection or who met the Phoenix sepsis criteria for sepsis and septic shock. ⋯ For children with Phoenix sepsis and Phoenix septic shock, the multivariable logistic regression, light gradient boosting machine, random forest, eXtreme Gradient Boosting, support vector machine, multilayer perceptron, and decision tree models predicting in-hospital mortality had AUPRCs of 0.48-0.65 (95% CI range: 0.42-0.66), 0.50-0.70 (95% CI range: 0.44-0.70), 0.52-0.70 (95% CI range: 0.47-0.71), 0.50-0.70 (95% CI range: 0.44-0.70), 0.49-0.67 (95% CI range: 0.43-0.68), 0.49-0.66 (95% CI range: 0.45-0.67), and 0.30-0.38 (95% CI range: 0.28-0.40) and AUROCs of 0.82-0.88 (95% CI range: 0.82-0.90), 0.84-0.88 (95% CI range: 0.84-0.90), 0.81-0.88 (95% CI range: 0.81-0.90), 0.84-0.88 (95% CI range: 0.83-0.90), 0.82-0.87 (95% CI range: 0.82-0.90), 0.80-0.86 (95% CI range: 0.79-0.89), and 0.76-0.82 (95% CI range: 0.75-0.85), respectively. Conclusion: Among children with Phoenix sepsis admitted to a PICU, the random forest model had the best AUPRC for in-hospital mortality compared to the light gradient boosting machine, eXtreme Gradient Boosting, logistic regression, multilayer perceptron, support vector machine, and decision tree models or a Phoenix Sepsis Score ≥ 2. These findings suggest that machine learning methods to predict in-hospital mortality in children with suspected infection predict mortality in a PICU setting with more accuracy than application of the Phoenix sepsis criteria.
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The occurrence of sepsis-associated acute kidney injury (SA-AKI) predicts a worse prognosis. We aimed to assess the impact of acetaminophen use on short-term mortality in patients with SA-AKI. A total of 6563 patients diagnosed with SA-AKI from the 2008 to 2019 Medical Information Mart for Intensive Care IV (MIMIC-IV) database were enrolled in this retrospective cohort study. ⋯ The PSM analysis demonstrated that acetaminophen use was still related to a reduced risk of 30-day mortality and in-hospital mortality. Subgroup analysis showed that the relationships between acetaminophen and 30-day mortality and in-hospital mortality were consistent across subgroups (p < 0.05). The use of acetaminophen has an association with lower short-term mortality in patients with SA-AKI.
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Sepsis results from a dysregulated host immune response to infection and is responsible for ~11 million deaths each year. In the laboratory, many aspects of sepsis can be replicated using a cecal ligation and puncture model, which is considered the most clinically relevant rodent model of sepsis. ⋯ Treatment of mice with 10 μg of a synthetic 68-amino acid peptide derived from an immunomodulatory molecule secreted by a parasitic worm of humans and livestock, F. hepatica , termed F. hepatica helminth defense molecule, potently suppressed the systemic inflammatory profile, protected mice against acute kidney injury, and improved survival between 48 and 72 h after procedure. These results suggest that the anti-inflammatory parasite-derived F. hepatica helminth defense molecule peptide has potential as a biotherapeutic treatment for sepsis.
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Background: Growing evidence has found the critical role of circular RNAs (circRNAs) in sepsis-induced acute kidney injury (S-AKI). CircTMCO3 has been found to be involved in tumor microenvironment changes of ovarian cancer. This study aimed to explore whether circTMCO3 functions in S-AKI, and if so, to elucidate the molecular mechanism. ⋯ ZEB2 was identified to be a target of miR-218-5p; its downregulation not only reversed the impacts of miR-218-5p inhibitor on S-AKI, but also mitigated the effects mediated by circTMCO3 upregulation in vitro. Conclusions: CircTMCO3 protects against S-AKI by regulating miR-218-5p/ZEB2 axis, thereby mediating antiapoptotic, antioxidant, and anti-inflammatory activities. This indicates that increasing circTMCO3 expression might be a future therapeutic method for S-AKI.