| Literature DB >> 32945982 |
Covadonga Gómez-Cuervo1, Agustina Rivas2, Adriana Visonà3, Nuria Ruiz-Giménez4, Ángeles Blanco-Molina5, Inmaculada Cañas6, José Portillo7, Patricia López-Miguel8, Katia Flores9, Manuel Monreal10.
Abstract
Old patients receiving anticoagulant therapy for venous thromboembolism (VTE) are at an increased risk for bleeding. We used data from the RIETE registry to assess the prognostic ability of the Comorbidity Charlson Index (CCI) to predict the risk for major bleeding in patients aged > 75 years receiving anticoagulation for VTE beyond the third month. We calculated the area under the receiver-operating characteristic curve (AUC), the category-based net reclassification index (NRI) and the net benefit (NB). We included 4303 patients with a median follow-up of 706 days (interquartile range [IQR] 462-1101). Of these, 147 (3%) developed major bleeding (27 died of bleeding). The AUC was 0.569 (95% CI 0.524-0.614). Patients with CCI ≤ 4 points were at a lower risk for adverse outcomes than those with CCI > 10 (major bleeding 0.81 (95% CI 0.53-1.19) vs. 2.21 (95% CI 1.18-3.79) per 100 patient-years; p < 0.05; all-cause death 1.9 (95% CI 1.45-2.44) vs. 15.67 (95% CI 12.63-19.22) per 100 patient-years; p < 0.05). A cut-off point of 4 points (CCI4) had a sensitivity of 82% (95% CI 75-89) and a specificity of 30% (95% CI 29-31) to predict major bleeding beyond the third month. CCI4 reclassification improved the NB of the RIETE bleeding score to predict bleeding beyond the third month (CCI4 NB 1.78% vs. RIETE NB 0.44%). Although the AUC of the CCI to predict major bleeding was modest, it could become an additional help to select patients aged > 75 years that obtain more benefit of extended anticoagulation, due to a lower risk for bleeding and better survival.Entities:
Keywords: Aged; Clinical decisions rules; Comorbidity; Hemorrhage; Venous thrombosis
Mesh:
Substances:
Year: 2020 PMID: 32945982 DOI: 10.1007/s11239-020-02274-6
Source DB: PubMed Journal: J Thromb Thrombolysis ISSN: 0929-5305 Impact factor: 2.300