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Risk score to predict the outcome of patients with cerebral vein and dural sinus thrombosis

José M Ferro1, Helena Bacelar-Nicolau, Teresa Rodrigues

  • 1Department of Neurosciences-Neurology, Hospital Santa Maria, University of Lisbon, Lisbon, Portugal. jmferro@fm.ul.pt

Cerebrovascular Diseases (Basel, Switzerland)
|May 8, 2009
PubMed

Insights

A new risk score aids in predicting outcomes for cerebral vein and dural sinus thrombosis (CVT) patients. This tool helps identify high-risk individuals while avoiding unnecessary interventions for low-risk cases.

Area of Science:

  • Neurology
  • Vascular Medicine
  • Clinical Epidemiology

Background:

  • Cerebral vein and dural sinus thrombosis (CVT) affects approximately 15% of patients, leading to death or disability.
  • Effective risk stratification is crucial for managing CVT patients.

Purpose of the Study:

  • To develop and validate a predictive model and risk score for determining outcomes in CVT patients.
  • To identify key factors associated with poor prognosis in CVT.

Main Methods:

  • A Cox proportional hazards regression model was developed using the International Study on Cerebral Vein and Dural Sinus Thrombosis (ISCVT) dataset (624 patients).
  • A risk score was derived from the model's hazard ratios and validated in two independent cohorts (VENOPORT and ISCVT extension).
  • Model performance was assessed using sensitivity, specificity, c-statistics, and overall efficiency at 6 months.

Main Results:

  • The predictive model identified malignancy, coma, deep venous system thrombosis, mental status disturbance, male gender, and intracranial hemorrhage as significant predictors.
  • The derived CVT risk score demonstrated high overall efficiency (84-90%) in predicting outcomes across derivation and validation samples.
  • While sensitivity was high (96.1%), the specificity of the risk score was low (13.6%).

Conclusions:

  • The developed CVT risk score offers a valuable tool for classifying patient outcomes with good accuracy.
  • The score's low specificity suggests caution in its use for definitively ruling out high risk.
  • It can assist clinicians in identifying high-risk CVT patients for closer monitoring and potentially avoiding interventions in low-risk individuals.
Abstract

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