感染、炎症、修复2026，Vol.27Issue(3)：234-241,8.DOI:10.3969/j.issn.1672-8521.2026.03.005
基于轨迹模型的脓毒症相关凝血功能障碍新亚型及其肝素疗效异质性分析
Identification of novel subtypes of sepsis-associated coagulopathy and heterogeneity of heparin efficacy based on trajectory modeling
摘要
Abstract
Objective To establish a classification strategy for sepsis-associated coagulopathy and to explore the clinical characteristics of each subtype and their relationship with prognosis.Methods A retrospective analysis was conducted on 540 patients with sepsis admitted to the Emergency Intensive Care Unit of the First Affiliated Hospital of Wenzhou Medical University from September 2018 to December 2023.According to in-hospital mortality,patients were divided into a survival group(n=477)and a non-survival group(n=63).Four coagulation-related parameters—D-dimer,international normalized ratio(INR),fibrinogen,and platelet count were collected within 72 hours after admission,with measurements taken every 12 hours,totaling six time points.A group-based trajectory modeling(GBTM)was applied to construct models for coagulation indicators within 72 hours post-admission.Logistic regression analysis was used to analyze the correlation between coagulation subtypes and in-hospital mortality in septic patients.Furthermore,the correlation between heparin administration and in-hospital mortality was evaluated across different coagulation subtypes of septic patients.Results Six distinct coagulation subtypes were identified using group-based trajectory modeling.There was a statistically significant difference in age among the groups(P<0.05).The proportions of mechanical ventilation and hemodialysis in group 3 were significantly higher than those in other groups,with statistically significant differences(P<0.001).The rates of heparin use were low in group 2 and group 6,and highest group 3,with statistically significant differences(P<0.001).Statistically significant differences were observed in laboratory parameters among the groups(P<0.001).Multivariate logistic regression analysis demonstrated that in-hospital mortality was significantly higher in group 3 compared with group 2(P<0.001).Additionally,multivariate logistic regression analysis revealed that in group 3,characterized by extremely high D-dimer,elevated INR,normal fibrinogen,and extremely low platelet count,heparin use was significantly negatively correlated with in-hospital mortality(OR=0.011,95%CI:0.000-0.664,P<0.05).Conclusions Using group-based trajectory modeling,patients with sepsis can be classified into 6 subtypes based on D-dimer,INR,fibrinogen,and platelet count.Among them,Group 3,characterized by extremely high D-dimer,elevated INR,normal fibrinogen,and extremely low platelet count,exhibited the highest in-hospital mortality rate.Furthermore,heparin use in this subtype was associated with a reduced in-hospital mortality.关键词
脓毒症/凝血功能障碍/组轨迹分析/肝素Key words
sepsis/coagulopathy/group-based trajectory analysis/heparin引用本文复制引用
叶晶晶,赵光举,彭凯..基于轨迹模型的脓毒症相关凝血功能障碍新亚型及其肝素疗效异质性分析[J].感染、炎症、修复,2026,27(3):234-241,8.基金项目
国家自然科学基金(82272202),温州市高水平创新团队项目(2024R3002) （82272202）
