Literature DB >> 19420921

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

José M Ferro1, Helena Bacelar-Nicolau, Teresa Rodrigues, Leonor Bacelar-Nicolau, Patrícia Canhão, Isabelle Crassard, Marie-Germaine Bousser, Aurélio Pimenta Dutra, Ayrton Massaro, Marie-Anne Mackowiack-Cordiolani, Didier Leys, João Fontes, Jan Stam, Fernando Barinagarrementeria.   

Abstract

BACKGROUND: Around 15% of patients die or become dependent after cerebral vein and dural sinus thrombosis (CVT).
METHOD: We used the International Study on Cerebral Vein and Dural Sinus Thrombosis (ISCVT) sample (624 patients, with a median follow-up time of 478 days) to develop a Cox proportional hazards regression model to predict outcome, dichotomised by a modified Rankin Scale score >2. From the model hazard ratios, a risk score was derived and a cut-off point selected. The model and the score were tested in 2 validation samples: (1) the prospective Cerebral Venous Thrombosis Portuguese Collaborative Study Group (VENOPORT) sample with 91 patients; (2) a sample of 169 consecutive CVT patients admitted to 5 ISCVT centres after the end of the ISCVT recruitment period. Sensitivity, specificity, c statistics and overall efficiency to predict outcome at 6 months were calculated.
RESULTS: The model (hazard ratios: malignancy 4.53; coma 4.19; thrombosis of the deep venous system 3.03; mental status disturbance 2.18; male gender 1.60; intracranial haemorrhage 1.42) had overall efficiencies of 85.1, 84.4 and 90.0%, in the derivation sample and validation samples 1 and 2, respectively. Using the risk score (range from 0 to 9) with a cut-off of >or=3 points, overall efficiency was 85.4, 84.4 and 90.1% in the derivation sample and validation samples 1 and 2, respectively. Sensitivity and specificity in the combined samples were 96.1 and 13.6%, respectively.
CONCLUSIONS: The CVT risk score has a good estimated overall rate of correct classifications in both validation samples, but its specificity is low. It can be used to avoid unnecessary or dangerous interventions in low-risk patients, and may help to identify high-risk CVT patients. (c) 2009 S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2009        PMID: 19420921     DOI: 10.1159/000215942

Source DB:  PubMed          Journal:  Cerebrovasc Dis        ISSN: 1015-9770            Impact factor:   2.762


  24 in total

1.  A Classification Scheme for Assessing Recanalization and Collateral Formation following Cerebral Venous Thrombosis.

Authors:  Adnan I Qureshi
Journal:  J Vasc Interv Neurol       Date:  2010-01

2.  Diagnostic imaging in the management of patients with possible cerebral venous thrombosis: a cost-effectiveness analysis.

Authors:  Dennis M Hedderich; José M Ferro; Wolfgang G Kunz
Journal:  Neuroradiology       Date:  2019-07-10       Impact factor: 2.804

Review 3.  Cerebral Venous Thrombosis: an Update.

Authors:  José M Ferro; Diana Aguiar de Sousa
Journal:  Curr Neurol Neurosci Rep       Date:  2019-08-23       Impact factor: 5.081

4.  Serum neuron specific enolase may be a marker to predict the severity and outcome of cerebral venous thrombosis.

Authors:  Yanyu Hu; Ran Meng; Xuxiang Zhang; Linlin Guo; Sijie Li; Yan Wu; Jiangang Duan; Yuchuan Ding; Xunming Ji
Journal:  J Neurol       Date:  2017-11-11       Impact factor: 4.849

Review 5.  Cerebral venous thrombosis.

Authors:  Suzanne M Silvis; Diana Aguiar de Sousa; José M Ferro; Jonathan M Coutinho
Journal:  Nat Rev Neurol       Date:  2017-08-18       Impact factor: 42.937

6.  Do the Risk Factors Determine the Severity and Outcome of Cerebral Venous Sinus Thrombosis?

Authors:  Jayantee Kalita; Usha K Misra; Rajesh K Singh
Journal:  Transl Stroke Res       Date:  2018-01-10       Impact factor: 6.829

Review 7.  Cerebral venous and dural sinus thrombosis* : state-of-the-art imaging.

Authors:  Jennifer Linn; Hartmut Brückmann
Journal:  Clin Neuroradiol       Date:  2010-02-28       Impact factor: 3.649

8.  Risk of Pulmonary Embolism After Cerebral Venous Thrombosis.

Authors:  Ava L Liberman; Alexander E Merkler; Gino Gialdini; Steven R Messé; Michael P Lerario; Santosh B Murthy; Hooman Kamel; Babak B Navi
Journal:  Stroke       Date:  2017-02-22       Impact factor: 7.914

9.  Outcome Prediction in Cerebral Venous Thrombosis: The IN-REvASC Score.

Authors:  Piers Klein; Liqi Shu; Thanh N Nguyen; James E Siegler; Setareh Salehi Omran; Alexis N Simpkins; Mirjam Heldner; Adam de Havenon; Hugo J Aparicio; Mohamad Abdalkader; Marios Psychogios; Maria Cristina Vedovati; Maurizio Paciaroni; Rascha von Martial; David S Liebeskind; Diana Aguiar de Sousa; Jonathan M Coutinho; Shadi Yaghi
Journal:  J Stroke       Date:  2022-09-30       Impact factor: 8.632

Review 10.  Cerebral venous sinus thrombosis: update on diagnosis and management.

Authors:  José M Ferro; Patrícia Canhão
Journal:  Curr Cardiol Rep       Date:  2014-09       Impact factor: 2.931

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