Evaluation of Argatroban in Sepsis-Induced Coagulopathy: A Retrospective Study Based on MIMIC-IV Database

BackgroundSepsis-Induced Coagulopathy (SIC) is common complications of sepsis in intensive care unit (ICU) patients. It has a significant impact on the prognosis of patients with sepsis and is an important cause of death. However, there is no evidence for the use of Argatroban in SIC anticoagulant therapy.MethodA retrospective study was conducted based on data collected from patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. SIC patients were screened according to SIC scores formulated by the International Society of Thrombosis and Hemostasis. Propensity score matching was used to match patients who received Argatroban with patients who did not receive Argatroban. Cox regression analysis was used to explore the correlation between Argatroban and SIC prognosis, and the hazard ratio was calculated. Finally, Kaplan-Meier curve was used to compare the survival rate between the two groups.OutcomeAfter PSM, 108 patients who received Argatroban were matched with 108 patients who did not receive Argatroban. In terms of outcomes, Argatroban admission to ICU was associated with a higher risk of death 30 days after ICU admission for SIC patients (HR = 1.800; 95%CI: 1.064∼3.043; <i>P</i> = .043) correlation.ConclusionArgatroban is not recommended for anticoagulant therapy in SIC patients.

Authors

Institutions

Publication Details

Journal
Clinical and Applied Thrombosis/Hemostasis
Published
2025-10-01
DOI
https://doi.org/10.1177/10760296251326095
Primary Topic
Heparin-Induced Thrombocytopenia and Thrombosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of Argatroban in Sepsis-Induced Coagulopathy: A Retrospective Study Based on MIMIC-IV Database

Jiaqi Tang, Zhiwei Su, Hongke Zeng, Hongguang Ding
Clinical and Applied Thrombosis/Hemostasis
Heparin-Induced Thrombocytopenia and Thrombosis
article

Evaluation of Argatroban in Sepsis-Induced Coagulopathy: A Retrospective Study Based on MIMIC-IV Database

Jiaqi Tang, Zhiwei Su, Hongke Zeng, Hongguang Ding
article en

Abstract

BackgroundSepsis-Induced Coagulopathy (SIC) is common complications of sepsis in intensive care unit (ICU) patients. It has a significant impact on the prognosis of patients with sepsis and is an important cause of death. However, there is no evidence for the use of Argatroban in SIC anticoagulant therapy.MethodA retrospective study was conducted based on data collected from patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. SIC patients were screened according to SIC scores formulated by the International Society of Thrombosis and Hemostasis. Propensity score matching was used to match patients who received Argatroban with patients who did not receive Argatroban. Cox regression analysis was used to explore the correlation between Argatroban and SIC prognosis, and the hazard ratio was calculated. Finally, Kaplan-Meier curve was used to compare the survival rate between the two groups.OutcomeAfter PSM, 108 patients who received Argatroban were matched with 108 patients who did not receive Argatroban. In terms of outcomes, Argatroban admission to ICU was associated with a higher risk of death 30 days after ICU admission for SIC patients (HR = 1.800; 95%CI: 1.064∼3.043; <i>P</i> = .043) correlation.ConclusionArgatroban is not recommended for anticoagulant therapy in SIC patients.

Clinical and Applied Thrombosis/HemostasisVol. 31
Guangdong Academy of Medical Sciences (CN)
Openalex Percentile: Top 26%
Heparin-Induced Thrombocytopenia and Thrombosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.