Evidence map›Paper›PMID 42898272›Full record

ArticleFrontiers in medicine2026

Investigating risk factors and developing a predictive model for venous thromboembolism in patients with sepsis.

Yu Han, Yage Shi, Liu Liu, Bingjie Ding, Mengjuan Li, Ao Xia, Jingyuan Liu, Juanjuan Song, Ao Xie, Dong Miao and 1 more

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Yu HanDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Yage ShiDepartment of Hematology, Huaihe Hospital of Henan University, Kaifeng, China.
Liu LiuDepartment of Hematology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Bingjie DingDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Mengjuan LiDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Ao XiaDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Jingyuan LiuDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Juanjuan SongDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Ao XieDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Dong MiaoDepartment of Hematology, Huaihe Hospital of Henan University, Kaifeng, China.
Hu ZhouDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with sepsis are at high risk for venous thromboembolism (VTE). However, existing assessment tools designed for general medical or surgical populations may inadequately capture the specific risk profile of septic patients. This study aimed to identify independent predictors of VTE in sepsis and develop a sepsis-specific prediction model. Methods: In this retrospective cohort study, adult patients with sepsis diagnosed at a single center (2015-2024) were enrolled. Candidate predictors and treatments were restricted to data available within the first 24 h of diagnosis. After exclusions, 157 VTE cases and 703 matched non-VTE controls formed the prediction cohort, which was split into training ( Results: Among 3,228 sepsis patients, 157 (4.86%) developed VTE. Multivariable analysis identified four independent predictors: surgery within 3 months, central venous catheterization within 24 h, history of VTE ≥1 year prior, and absence of early anticoagulant therapy (all Conclusions: A sepsis-specific nomogram incorporating recent surgery, early catheterization, previous VTE, and absence of early anticoagulation demonstrated good discrimination and calibration. It outperformed the Padua and Caprini tools in internal validation. External validation is required before clinical implementation.

Indexed as

deep vein thrombosisnomogramprediction modelrisk assessmentsepsisvenous thromboembolism

Identifiers

PMID42898272
PMCPMC13677700

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.