The Importance of Recanalization in Intracranial Venous Thrombosis and Predictive Factors
DOI:
https://doi.org/10.24950/rspmi/9/2017Keywords:
Intracranial Thrombosis, Predictive Value of Tests, Prognosis, Treatment Outcome, Venous ThrombosisAbstract
Introduction: Cerebral venous thrombosis (CVT) is a rare disease that affects mainly young people. The importance of recanalization
is controversial but it is related to residual symptoms/ signs. This study aims to calculate the incidence of CVT, to evaluate
the importance of recanalization and to define its predictive factors.
Material and Methods: This is a retrospective observational study involving patients with CVT diagnosed between 2004 to 2014 in Braga Hospital. Functional assessment was based on the modified Rankin scale. Recanalization was defined as the
presence of venous flow in all vessels, including residual. A descriptive statistical analysis was conducted and used test t Student(
t), Mann-Whitney U(U), chi-square(χ2) or Fisher’s exact test a binary logistic regression was used for predictive model. It was
recognized statistical significance p < 0.05.
Results: The incidence of CVT was estimated at 1.82 cases per 100 000 person-years. The recanalization was associated with the functional evaluation at 6 (Fisher’s exact test, p < 0.001, φc =0.511) and 12 months (Fisher’s exact test, p = 0.001, φc =0.480), inability to six (Fisher’s exact test, p = 0.024,φ = 0.305) and 12 months (Fisher’s exact test, p = 0.023,φ = 0.305), and the residual symptoms/signals at 3 months (χ2(1) = 23.46, p < 0.001,φ = 0.605). The obtained regression model included the following predictive variables age, arterial hypertension, dyslipidemia, altered state of consciousness and new residual symptoms/signs. This was statistically significant (χ2(5) = 37.43, p < 0.001), with a sensitivity of 90.0% and specificity of 70.8%. New residual symptoms/signs is the best predictor of no recanalization (OR = 33.33).
Discussion and Conclusion: The recanalization has an important role in prognosis; it was possible to predict its occurrence based
on five variables.
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