Risk Of Recurrence After Withdrawal Of Anticoagulation In Patients With Unprovoked Venous Thromboembolism: External Validation Of The Vienna Nomogram And The Dash Prediction Score. / Riesgo de recurrencia tras retirada de la anticoagulación en pacientes con enfermedad tromboembólica venosa no provocada: validación externa del nomograma de Viena y del modelo predictivo DASH.

INTRODUCTION: Scales for predicting venous thromboembolism (VTE) recurrence are useful for deciding the duration of the anticoagulant treatment. Although there are several scales, the most appropriate for our setting has not been identified. For this reason, we aimed to validate the DASH prediction score and the Vienna nomogram at 12 months. METHODS: This was a retrospective study of unselected consecutive VTE patients seen between 2006 and 2014. We compared the ability of the DASH score and the Vienna nomogram to predict recurrences of VTE. The validation was performed by stratifying patients as low-risk or high-risk, according to each scale (discrimination) and comparing the observed recurrence with the expected rate (calibration). RESULTS: Of 353 patients evaluated, 195 were analyzed, with an average age of 53.5 ± 19 years. There were 21 recurrences in 1 year (10.8%, 95% CI: 6.8%-16%). According to the DASH score, 42% were classified as low risk, and the rate of VTE recurrence in this group was 4.9% (95% CI: 1.3%-12%) vs. the high-risk group that was 15% (95% CI: 9%-23%) (p <.05). According to the Vienna nomogram, 30% were classified as low risk, and the rate of VTE recurrence in the low risk group vs. the high risk group was 4.2% (95% CI:0.5%-14%) vs. 16.2% (95% CI: 9.9%-24.4%) (p <.05). CONCLUSIONS: Our study validates the DASH score and the Vienna nomogram in our population. The DASH prediction score may be the most advisable, both because of its simplicity and its ability to identify more low-risk patients than the Vienna nomogram (42% vs. 30%).

Rivaroxaban for the treatment of venous thromboembolism. A "real-life" perspective in 103 patients.

INTRODUCTION: Randomized clinical trials have demonstrated non-inferiority of rivaroxaban compared with vitamin K antagonists (VKAs) in the treatment of venous thromboembolism (VTE). Our objective was to analyze in real life, tolerance, recurrence, bleeding and adverse events of rivaroxaban in patients with acute symptomatic VTE. MATERIAL AND METHODS: Open follow-up study of a cohort of patients aged 18 and over diagnosed with deep vein thrombosis (DVT) and/or pulmonary embolism (PE) treated with rivaroxaban from December 2011 to January 2014. RESULTS: The total number of patients treated with rivaroxaban was 103. The mean age was 58+/-17 years. The most frequent co-morbidities were: hypertension (30.0%), dyslipidemia (23.3%) and respiratory disease (25.2%). The type of thromboembolic event treated was: DVT (64.1%), PE (18.4%), DVT+PE (17.5%). Of the rivaroxaban-treated patients, 30% did so from the initial anticoagulant therapy and the other 70% in long-term or extended anticoagulant therapy. The median time of treatment with rivaroxaban was 6 months [corrected]. There was one recurrence and no deaths occurred. Six patients had bleeding, one of which was severe. CONCLUSIONS: Rivaroxaban provides a therapeutic alternative in a group of patients with VTE with advantages over VKAs, because of the convenience in dosing, lack of requirements for periodic monitoring and limited interaction with other drugs.

[Predictive Khorana's model in patients with venous thromboembolic disease and cancer]. / La escala predictiva de Khorana en pacientes con enfermedad tromboembólica venosa y cáncer.

BACKGROUND AND OBJECTIVE: The predictive Khorana's model was developed to score the thromboembolic disease risk in cancer patients on chemotherapy and to identify which patients would benefit from thromboprophylaxis. We analized the results and applied the predictive Khorana's model in patients with cancer and who were diagnosed with deep vein thrombosis. MATERIAL AND METHODS: Retrospective analysis of prognostic characteristics of Khorana's model in 122 patients based on a prospective analysis. RESULTS: Seventy-nine percent of the total were in the low and intermediate risk category and 21% had high risk according to the Khorana's predictive model. This model had a sensitivity and prognostic precision of 20.8% (95% confidence interval [95% CI]: 14.6-28.7) and a false negatives proportion of 79.2% (95% CI: 1.3-85.4). CONCLUSIONS: Application of this model in our patients would not be enough as the unique tool to identify cancer patients who should receive tromboprophylaxis. The use of both biomarkers and clinical models seems to be the best cost-effective strategy for this purpose. Future, randomized, prospective, placebo-controlled studies are needed for find better treatment strategies in cancer patients.