Sepsis is now the leading cause of death in the non-cardiovascular intensive care unit (ICU). Recent research suggests that sepsis is likely to be due to an interaction between genetic and environmental factors. Genetic mutations of toll-like receptor 4 (TLR4) and cluster of differentiation 14 (CD14) genes are involved in the immune and (or) inflammatory response. These may contribute to the susceptibility to sepsis in patients. This study was designed to evaluate whether the TLR4 and cluster CD14 gene polymorphisms are associated with susceptibility to sepsis. The single nucleotide polymorphisms (SNPs) of TLR4 (rs10759932, rs11536889, rs7873784, rs12377632, rs1927907, rs1153879) and CD14 (rs2569190 and rs2563298) in patients with sepsis and control subjects in the Guangxi Province were analyzed by using the polymerase chain reaction-single base extension (PCR-SBE) and DNA sequencing methods. The rs11536889 polymorphism in TLR4 and rs2563298 polymorphism in CD14 were significantly associated with the risk of sepsis when compared to the control group. The frequencies of rs11536889 and rs2563298 polymorphisms in the group with sepsis were higher than that in the control group (OR = 1.430, 95% CI, 1.032-1.981, P<0.05; OR = 2.454, 95% CI, 1.458-4.130, P<0.05, respectively). Followed up haplotype analysis suggested that there were two haplotypes in which increased risk factors for sepsis were indicated. The rs11536889 polymorphism in TLR4 and rs2563298 polymorphism in CD14, and two haplotypes were associated with increased susceptibility to sepsis.

Background: Research on extracorporeal membrane oxygenation (ECMO)-assisted support for pulmonary embolism (PE) has been increasing, yet no systematic bibliometric analysis has been conducted. This study evaluates global research trends in this field by analyzing countries, institutions, authors, journals, references, and keywords.Methods: Relevant articles and reviews published up to August 15, 2023, were retrieved from the Web of Science Core Collection (WOSCC). VOSviewer and CiteSpace software were used for bibliometric analysis of collected data.Results: Publications on ECMO-assisted support for PE surged from 2015 to 2023, comprising 82.7% (306/370) of total studies. The United States, Germany, and China contributed 62.97% (233/370) of the research. Perfusion-UK had the most publications, while Journal of the American College of Cardiology was the most cited journal. The University of Maryland, Massachusetts General Hospital, and Harvard Medical School were the leading institutions. Chetan Pasrija published the highest number of papers, while Konstantinidis SV was the most co-cited author. Research hot spots include: (1) ECMO management and survival rates, (2) combined treatments with thrombolysis or surgical thrombectomy, (3) anticoagulation and clot formation, and (4) ECMO support in COVID-19.Conclusion: This study aims to increase awareness of research hot spots on ECMO-assisted support for PE by determining the collaboration and impact of authors, countries, institutions, and journals. In addition, it comprehensively reviews research trends on ECMO regarding PE. It also provides a reference for potential collaborators, institutions, and future research prospects.

Background: Sepsis frequently results in complications such as acute respiratory distress syndrome (ARDS) and cardiomyopathy. This study aims to identify common diagnostic markers and elucidate the underlying mechanisms of these sepsis-induced complications. Methods: We obtained datasets related to ARDS and sepsis-induced cardiomyopathy (SIC) from the GEO database and applied weighted gene co-expression network analysis (WGCNA) to identify differentially expressed genes (DEGs), which were integrated with key module genes. Feature genes were selected using support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF) algorithms. An artificial neural network (ANN) model was constructed and its diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Machine learning algorithms effectively identified key hub genes associated with sepsis-induced ARDS and cardiomyopathy, with their robustness validated through ROC analysis. A cellular model of sepsis-induced lung injury was employed to examine hub gene expression. Additionally, we investigated inflammation and immune responses by characterizing immune landscapes using CIBERSORT and performing correlation analyses among feature genes, immune infiltration, and clinical characteristics. Finally, potential small-molecule compounds were identified from the PubChem database. Results: Five key genes—LCN2, AIF1L, STAT3, SOCS3 and SDHD—were identified. SOCS3 showed strong diagnostic potential with gene set enrichment analysis (GSEA) highlighting its role in biological processes and immune responses. SOCS3 expression correlated strongly with immune cells. Dexamethasone, resveratrol and curcumin were identified as potential SOCS3-targeting drugs. Conclusion: Five genes were identified as diagnostic biomarkers for sepsis-induced ARDS and cardiomyopathy, with SOCS3 serving as a key hub gene and potential therapeutic target.

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is increasingly being employed to treat patients with refractory septic shock. Despite its growing use, there is a notable absence of prognostic assessment tools specifically designed for septic shock patients who have received VA-ECMO therapy. The aim of this study is to develop and validate a prognostic model for patients with refractory septic shock undergoing VA-ECMO, and to identify those who may derive the greatest benefit from this treatment. This single-center, retrospective cohort study was conducted at a comprehensive intensive care unit in China. Adult patients with refractory septic shock who received VA-ECMO treatment were included. Two hundred consecutive patients were randomly divided into training and validation cohorts in a 7:3 ratio. Least absolute shrinkage and selection operator regression analysis was employed to select relevant variables for the logistic regression model, and its performance was tested in both training and validation cohorts based on discrimination, calibration, and net benefit. Between January 2019 and September 2024, 293 patients were screened, 200 of whom were eligible and were divided into development ( n = 140) and validation ( n = 60) cohorts. The 28-day survival rate was 23.0%, and median duration of ECMO run was 6.0 days (IQR 2.0–8.0). Age, APACHE II score at ICU admission, immunosuppression status, hypertension, IL-6, and APTT measured within 6 h before ECMO initiation were the six predictors included in the nomograms. The nomogram demonstrated strong discriminative power in the training cohort (area under the curve [AUC]: 0.873, 95% CI 0.812–0.929), as well as in the validation cohort (area under the curve [AUC]: 0.818 (95% CI 0.687–0.920). The model's reliability in predicting outcomes was evident from the high consistency between predicted probabilities and observed proportions during calibration. Decision curve analysis indicated that the model's clinical benefit was advantageous. The novel validated nomogram is designed to predict outcomes after VA-ECMO treatment in individuals with refractory septic shock. It can support physicians in performing precise mortality risk evaluations and making more informed decisions regarding the application of VA-ECMO treatment.

While previous studies have investigated the pathophysiology, epidemiology, and risk factors of invasive pulmonary aspergillosis (IPA), research trends and hotspots on this topic remain relatively unexplored. This study aims to develop a visual knowledge map using bibliometric analysis to identify research hotspots and predict future trends in IPA research. A systematic search was conducted on the Web of Science Core Collection for articles published between January 1, 2000, and March 31, 2024. Tools such as CiteSpace and VOSviewer were used to analyze annual publication trends, contributions by countries, institutions, journals, authors, and references, as well as key research areas to identify current hotspots and future directions. A total of 4058 articles were included, representing contributions from 3409 institutions across 749 journals and 214 countries or regions. The United States published the most articles (1312) and emerged as the most influential country in this field. Medical Mycology published the highest number of articles (206), while Clinical Infectious Diseases was the most cited journal (27,450 citations). Keyword clustering revealed 4 major themes: diagnostics (e.g., galactomannan assays), clinical management (e.g., antifungal therapy), at-risk populations (e.g., transplant recipients), and emerging trends (e.g., COVID-19-associated IPA). Temporal analysis identified 3 distinct research phases: early phase (2000–2007): focus on bone marrow transplantation and diagnostic methods. mid-phase (2008–2018): emphasis on clinical guidelines and epidemiological studies. Recent phase (2019–2024): shift toward COVID-19-associated IPA and its impacts. By applying bibliometric methods to analyze IPA research, this study identifies key authors, countries, institutions, and journals in terms of collaboration and influence. It enhances the understanding of research hotspots in the field and provides insights into potential future collaborations and research directions.