Coagulation disorders constitute a core pathological event in sepsis, and the progression of sepsis-induced coagulopathy (SIC) to disseminated intravascular coagulation (DIC) is a major driver of multi-organ failure and death in septic patients. With deepening understanding of disease pathogenesis, the diagnosis and treatment model of SIC has gradually shifted from controlling bleeding risk-oriented supportive therapy for primary diseases towards a new precision anticoagulation model centering on excessive coagulation activation and emphasizing individualized intervention. Current routine coagulation indicators and scoring systems widely used in clinical practice are mostly static and outdated assessment tools, which fail to reflect the dynamic progression and pathological heterogeneity of the disease. These tools also present prominent limitations such as insufficient early identification and limited accuracy in SIC classification. Novel biomarkers, point-of-care testing for functional coagulation, and artificial intelligence-powered early warning models provide new modalities for early warning, dynamic monitoring and precise classification of SIC. In terms of treatment, the limitations of conventional anticoagulation have become increasingly prominent, and targeted intervention strategies focusing on stratified anticoagulation, endothelial protection and immunothrombosis regulation are progressively emerging as research hotspots, with a variety of novel therapeutic modalities demonstrating potential clinical value. Future efforts should further improve the molecular phenotyping and precise diagnosis and treatment system of SIC. Early identification, dynamic evaluation and individualized intervention are expested to improve the clinical outcomes of SIC patients.
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Open Access
Expert Review
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Open Access
Clinical Medicine
Issue
The pathogenesis of sepsis is complex, and current biomarkers have limitations in clinical application. This study aims to explore the causal relationship between lysosomal acid phosphatase（LAP）and the occurrence of sepsis, and to analyze LAP-related biological functions through transcriptomics, thereby providing new insights into the pathogenesis and candidate biomarkers of sepsis.
Based on the genome-wide association data from IEU Open GWAS database, two-sample Mendelian randomization（MR）analysis was used to explore the potential causal association between LAP and sepsis. Single nucleotide polymorphisms（SNPs）significantly associated with LAP levels were selected as instrumental variables (P<1.0×10-5, linkage disequilibrium coefficient r2 <0.001, kb >10000). The main analysis of MR were inverse variance-weighted（IVW）, weighted median and MR-Egger. Cochran's Q test was used to assess heterogeneity, MR-Egger intercept test was used to examine horizontal pleiotropy, and funnel plots and leave-one-out analysis were used to evaluate the reliability and stability of the results. Additionally, transcriptome sequencing data of patients with sepsis（GSE185263）were used to explore the underlying mechanisms by which LAP may be involved in the development of sepsis.
A total of 26 SNPs were selected as instrumental variables. The IVW fixed-effects model showed that elevated LAP increased the risk of sepsis occurrence（OR=1.047, 95%CI 1.007 to 1.090, P=0.019）, and the results of MR-Egger and Weighted Median were consistent with IVW. Cochran's Q test showed no significant heterogeneity among the SNPs（P=0.330）, and the leave-one-out analysis indicated robust results. Transcriptomic data analysis showed that ACP2, the gene encoding LAP, was upregulated in sepsis patients. Gene set enrichment analysis（GSEA）revealed that the elevated expression of LAP ACP2 may be associated with activation of JAK-STAT3 pathway and complement system.
Elevated LAP increases the risk of sepsis, potentially through LAP-mediated activation of the JAK-STAT3 pathway and complement pathway leading to increased inflammatory response. This finding provides new insights and theoretical basis for research on the pathogenesis and candidate biomarkers of sepsis.
To explore the effect of change in body mass on mortality during hospitalization in intensive care unit（ICU）.
A multicenter and retrospective cohort study was conducted on patients who were firstly hospitalized in ICU and whose length of ICU stay were over 24 h, with data extracted from the eICU Collaborative Research Database. Univariate and multivariate logistic regression models were used to explore the relationship between body mass change and mortality in ICU patients. Interaction analysis was performed between body mass change and related covariates. Based on the results of interaction analysis and clinical practice, the association between body mass change and mortality was analyzed in subgroups stratified by age, Acute Physiology and Chronic Health Evaluation（APACHE）Ⅳ score, length of ICU stay and baseline BMI at ICU admission.
A total of 34 311 ICU patients were included, among which 55.1% were male, the white race accounted for 82.4% and 51.3% were ≥65 years old. Compared with those with decreased body mass, patients with increased body mass had higher rates of renal failure（1 938 cases, 11.1%）, liver failure（106 cases, 0.6%）, sepsis（2 442 cases, 14.0%）, longer ICU stay, longer hospital stay and higher APACHEⅣ scores. The multivariate logistic regression model showed the in-hospital and ICU mortality in patients with body mass gain were 1.25 times（95%CI: 1.16~1.36, P<0.001）and 1.36 times（95%CI: 1.22~1.50, P<0.001）higher than those with body mass decreased respectively. This difference is more significant in patients with higher APACHEⅣ score and the longer ICU stay. The different age subgroup or different baseline BMI levels exerted no effect on the results mentioned.
The change in body mass is the independent risk factor of the in-hospital and ICU motality.
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