World journal of emergency medicine最新文献

BACKGROUND: Bloodstream infections (BSIs) caused by gram-positive cocci (GPC) and gram-negative bacilli (GNB) are major causes of sepsis. However, their distinct effects on host responses remain poorly characterized at the single-cell level. This study used single-cell transcriptomics to define pathogen-specific monocyte heterogeneity in BSIs to identify the mechanisms underlying clinical differences. METHODS: Single-cell RNA sequencing (scRNA-seq) was performed on peripheral blood mononuclear cells obtained from healthy volunteers, two patients with GNB-BSI sepsis, and two patients with GPC-BSI sepsis. Differential gene expression, particularly in monocytes, was analyzed. The key findings were validated with clinical characteristics and outcomes of 45 patients with GNB-BSI sepsis and 40 patients with GPC-BSI sepsis. The distinguishing performances of identified biomarkers were evaluated via receiver operating characteristic (ROC) curve. RESULTS: In pathogen-specific transcriptomes, 54 identified genes were significantly associated with GNB-BSI (upregulated genes enriched in inflammatory pathways and downregulated genes enriched in oxidative phosphorylation). Twenty-one identified genes were associated with GPC-BSI (downregulated genes associated with cell adhesion molecules and upregulated genes involved in PI3K-Akt signaling). Nineteen genes were common to both groups, with distinct pathogen sensitivities. Patients with GNB-BSI presented with significantly greater disease severity, systemic inflammation and lymphopenia than patients with GPC-BSI. Conversely, patients with GPC-BSI had higher S100A12 and globulin levels and platelet counts. The combination of S100A12^high and procalcitonin (PCT)^low discriminated GPC-BSI from GNB-BSI (area under the curve=0.882, sensitivity 75%, specificity 91%; cutoff value 0.56). CONCLUSION: ScRNA-seq reveals the heterogeneity of GPC-BSI and GNB-BSI. Compared with GPC-BSI, GNB-BSI causes severe inflammation and metabolic suppression, which are associated with poor outcomes. The S100A12^high+PCT^low combination may have potential to discriminate among the major causes of BSI.

BACKGROUND: Sepsis survivors experience poor long-term quality of life post-discharge. The aim of this study was to analyze the factors that impact the long-term quality of life of sepsis survivors and develop a clinical prediction model. METHODS: A total of 442 sepsis patients from the Emergency Intensive Care Unit of a tertiary hospital in Wenzhou were included. These patients were assigned to the training set or the validation set at a ratio of 7:3. The European Quality of Life 5 Dimensions 5 Level Version (EQ-5D-5L) questionnaire was used to evaluate the quality of life in sepsis survivors one year after discharge. Multivariate logistic regression analysis was used to identify predictors, which were then used to develop the prediction model and subsequently derive a scoring system. The model's effectiveness was assessed using an area under the receiver operating characteristic curve, calibration curves, and clinical decision analysis. RESULTS: Of the 442 patients included, 70 died one year after discharge, and 372 completed the questionnaire. A total of 46.6% of sepsis survivors have poor quality of life one year after discharge in the training set. Multivariate logistic regression revealed that age, platelet, serum albumin, serum urea, and C-reactive protein were independent risk factors for poor quality of life in sepsis survivors. The area under the curve of the scoring system was 0.777 (95% CI: 0.726-0.828). The calibration curves showed that it was well calibrated. Decision curve analysis indicated that the scoring system provided good clinical usefulness. The internal validation also demonstrated its effectiveness. CONCLUSION: The prediction model incorporating five risk factors may predict quality of life one year after discharge in sepsis survivors, which provides a measure to develop post-discharge rehabilitation and follow-up plans for this patient population.

BACKGROUND: Rapid identification of patients at risk of clinical deterioration (in-hospital mortality) in emergency settings is essential for timely and appropriate care. Existing prognostic scores, such as the Acute Physiology and Chronic Health Evaluation IV (APACHE IV), Simplified Acute Physiology Score 3 (SAPS 3), Sequential Organ Failure Assessment (SOFA), and National Early Warning Score 2 (NEWS 2), have limitations in emergency scenarios, particularly in resource-limited settings. We aimed to develop a simple and efficient tool tailored to the Brazilian healthcare system. METHODS: This retrospective, multicenter, cohort study analyzed data from 50,709 adult patients admitted to 12 hospitals in southern and southeastern Brazil between 2019 and 2020. The BRASIL score (Brazilian Risk Assessment Severity Index and Length of stay) was constructed using demographic and clinical variables available at admission. Logistic regression was used to determine the weight of each variable, and each variable was assigned a point value based on its β-coefficient and clinical relevance, with thresholds defined according to established medical cutoffs and statistical performance. The score's predictive accuracy was validated using the area under the receiver operating characteristic curve (AUC) with comparative analysis against NEWS 2. RESULTS: The BRASIL score, including age, sex, respiratory rate, heart rate, oxygen saturation, blood pressure, and body temperature, was derived through variables independently associated with in-hospital mortality in a multicenter cohort. The total score was stratified into three risk categories - low (0-3 points), moderate (4-7 points), and high (>7 points) - using observed inflection points in mortality distribution to optimize discrimination. This stratification demonstrated a stepwise increase in mortality rates across categories and the discriminatory performance, with an overall AUC of 0.743 (95% CI: 0.726-0.761). Compared to NEWS 2 (AUC 0.697, 95% CI: 0.683-0.711), the BRASIL score offered superior early risk identification, supporting timely clinical decision-making and resource allocation in the emergency setting. CONCLUSION: The BRASIL score is a novel tool for predicting in-hospital mortality in emergency departments. Its predictive performance and ease of use suggest that it has the potential to improve patient outcomes.

BACKGROUND: he central nervous system is a critical target of severe heatstroke, with oxidative stress and multi-organelle damage being the key pathogenic mechanisms. However, research on endogenous antioxidant defense remains limited. In this study, we aimed to characterize neuronal oxidative damage as a key heatstroke pathological mechanism and assess the neuroprotective effects of nuclear factor E2-related factor 2 (NRF2). METHODS: After developing in vivo and in vitro heatstroke models, we employed histological staining, cell viability and apoptosis assays, oxidative stress indicators determination, organelle ultrastructural observation, and molecular expression analysis to investigate the mechanisms of brain injury and changes in the NRF2 pathway following heatstroke. We pretreated mice and SH-SY5Y cells with tert-butylhydroquinone (TBHQ) to activate NRF2 expression. Furthermore, we utilized NRF2 knockout (KO) mice and NRF2 siRNA transfection to suppress NRF2 expression, thereby examining the effects of NRF2 both in vivo and in vitro. RESULTS: We found that heatstroke induced neuronal damage, elevated oxidative stress levels, and caused structural damage to both the mitochondria and the endoplasmic reticulum (ER). Notably, NRF2 activation was insufficient post-heatstroke. Pretreatment with TBHQ effectively activated the NRF2 signaling pathway and mitigated the resulting damage. In contrast, these injuries were exacerbated in NRF2 KO mice and SH-SY5Y cells transfected with NRF2 siRNA. CONCLUSION: This preliminary research shows that the NRF2 antioxidant signaling pathway exerts a protective effect against oxidative stress, mitigating both mitochondrial and ER structural damage in neuronal cells during heatstroke. Therefore, targeting the NRF2 pathway is a promising therapeutic strategy for heatstroke-induced neuronal injury.