Shock : molecular, cellular, and systemic pathobiological aspects and therapeutic approaches : the official journal the Shock Society, the European Shock Society, the Brazilian Shock Society, the International Federation of Shock Societies
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Background: Acute kidney injury (AKI) is a prevalent and serious complication among patients with sepsis-associated acute respiratory distress syndrome (ARDS). Prompt and accurate prediction of AKI has an important role in timely intervention, ultimately improving the patients' survival rate. This study aimed to establish machine learning models to predict AKI via thorough analysis of data derived from electronic medical records. ⋯ In addition, a novel shiny application based on the XGBoost model was established to predict the probability of developing AKI among patients with sepsis-associated ARDS. Conclusions: Machine learning models could be used for predicting AKI in patients with sepsis-associated ARDS. Accordingly, a user-friendly shiny application based on the XGBoost model with reliable predictive performance was released online to predict the probability of developing AKI among patients with sepsis-associated ARDS.
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Observational Study
Identification of Subphenotypes of Sepsis-Associated Liver Dysfunction Using Cluster Analysis.
Objectives: We attempted to identify and validate the subphenotypes of sepsis-associated liver dysfunction (SALD) using routine clinical information. Design: This article is a retrospective observational cohort study. Setting: We used the Medical Information Mart for Intensive Care IV database and the eICU Collaborative Research Database. ⋯ In addition, we were surprised to find that GGT levels in subphenotype δ were significantly higher than in other subphenotypes, showing a different pattern from bilirubin. Conclusions: We identified four subphenotypes of SALD that presented with different clinical features and outcomes. These results can provide a valuable reference for understanding the clinical characteristics and associated outcomes to improve the management of patients with SALD in the ICU.
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Background: Cardiac arrest (CA) is one of the leading causes of death worldwide. Endoplasmic reticulum (ER) stress and ferroptosis are proven pathological mechanisms implicated in neuronal damage. Baicalein, a ferroptosis Inhibitor, improved outcomes after traumatic brain injury. ⋯ Conclusion: Ferroptosis and ER stress are both involved in brain injury after ROSC. Baicalein alleviates brain injury via suppressing the ferroptosis and ER stress, and reduces ROS partly through inhibiting ER stress. Baicalein is a potential drug to relieve brain injury after ROSC.
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Introduction: Septic patients with atrial fibrillation (AF) are common in the intensive care unit accompanied by high mortality. The early prediction of prognosis of these patients is critical for clinical intervention. This study aimed to develop a model by using machine learning (ML) algorithms to predict the risk of 28-day mortality in septic patients with AF. ⋯ Conclusion: We established the first ML model for predicting the 28-day mortality of septic patients with AF. Compared with conventional scoring systems, the AdaBoost model performed moderately. The model established will have the potential to improve the level of clinical practice.
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Traumatic brain injury (TBI) is a kind of disease with high morbidity, mortality, and disability, and its pathogenesis is still unclear. Research shows that nucleotide-binding oligomerization domain-like receptor containing pyrin domain 3 (NLRP3) activation in neurons and astrocytes is involved in neuroinflammatory cascades after TBI. What is more, polydatin (PD) has been shown to have a protective effect on TBI-induced neuroinflammation, but the mechanisms remain unclear. ⋯ More importantly, PD could inhibit the level of SOD2 Ac-K122, NLRP3, and cleaved caspase-1 and promote the expression of SOD2 after TBI both in vivo and in vitro. Polydatin also inhibited mtROS accumulation and MMP collapse after stretching injury. These results indicated that PD inhibited SOD2 acetylation to alleviate NLRP3 inflammasome activation, thus acting a protective role against TBI neuroinflammation.