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Establishment and validation of a predictive model for lower extremity deep vein thrombosis in patients with traumatic pelvic fractures

  • 0Department of Emergency Medicine, The Sixth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200233, China.
Thrombosis Journal +

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November 10, 2024

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November 10, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new DVT risk nomogram score (DRNS) model helps identify high-risk patients with traumatic pelvic fractures (TPF). This tool guides personalized low molecular weight heparin (LMWH) prevention strategies for deep vein thrombosis (DVT).

Area Of Science

  • Orthopedic Surgery
  • Vascular Surgery
  • Trauma Surgery

Background

  • Traumatic pelvic fracture (TPF) patients face a high risk of deep vein thrombosis (DVT).
  • Current guidelines lack standardized methods for identifying high-risk DVT patients with TPF and optimizing anticoagulant therapy.
  • Accurate risk stratification is crucial for effective DVT prevention in this population.

Purpose Of The Study

  • To develop a DVT risk nomogram score (DRNS) model for TPF patients.
  • To evaluate the clinical utility of the DRNS model in guiding low molecular weight heparin (LMWH) prophylaxis for DVT prevention.
  • To establish a data-driven approach for personalized DVT prevention in TPF patients.

Main Methods

  • An observational study was conducted to screen independent risk factors for lower extremity DVT.
  • Lasso regression and logistic regression analyses were employed to identify significant risk factors.
  • A DVT risk nomogram score (DRNS) model was constructed based on the identified independent risk factors.

Main Results

  • Independent DVT risk factors identified include combined femoral fractures, age ≥ 40 years, BMI ≥ 24 kg/m², ISS score, fibrinogen concentration, and minimum ionized calcium levels within 48 hours.
  • An optimal DRNS cutoff value of 78.5 was determined.
  • In high-risk patients (DRNS ≥ 78.5), LMWH once daily (qd) resulted in significantly higher DVT progression incidence compared to LMWH every 12 hours (q12h) (P = 0.002). No significant difference was observed in low-risk patients (P = 0.323).

Conclusions

  • The developed DRNS model effectively stratifies DVT risk in TPF patients.
  • The DRNS model facilitates the creation of more precise DVT drug prevention plans for clinicians.
  • This tool aids in optimizing LMWH prophylaxis strategies based on individual patient risk profiles.

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