Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
August 17, 2025Open Access

Development and Validation of a Prediction Model for Venous Thromboembolic Events Following Hematoma Evacuation in Patients with Spontaneous Intracerebral Hemorrhage

View Full Paper
Ask AI
Bookmark
Share

Authors

YBYun BaiXGXiaozhong GuoDLDa Li

Discussion

Loading...

Member takes

Overview

Retrospective analysis developed a prediction model for VTE risk in sICH patients, indicating potential for improved outcomes.

Key Points

  • The developed prediction model accurately estimates VTE risk in patients following hematoma evacuation.
  • In a cohort of 456 patients, the nomogram's C-index reached 0.902, demonstrating strong prediction accuracy.
  • A multivariate logistic regression established independent predictors of VTE at 30 days after surgery, enhancing clinical decision-making.
  • The model's clinical utility was supported by decision curve analysis, ensuring relevance for real-world application.

Cite This Study

Bai et al. (2025) studied this question.

synapsesocial.com/papers/68af570dad7bf08b1eadde62https://doi.org/10.21203/rs.3.rs-7248406/v1
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Development and validation of a predictive model for postoperative functional recovery in patients with spontaneous intracerebral hemorrhage2025
  2. 2Development of an Efficient Nomogram for Prediction of Early Deep Vein Thrombosis Following Intracerebral Hemorrhage2024
  3. 3Predictive Value of Cardiac Biomarkers Combined with Clinical, Radiological Factors for Venous Thromboembolism in Patients with Spontaneous Intracerebral Hemorrhage2025
  4. 4Development and Validation of a Clinical Prediction Model for Venous Thromboembolism Following Neurosurgery: A 6-Year, Multicenter, Retrospective and Prospective Diagnostic Cohort Study2023 · 9 citations
  5. 5Construction and validation of a risk prediction model for postoperative urinary tract infection in intracranial hemorrhage patients2025