Predictive ability of scores for bleeding risk in heart disease outpatients on warfarin in Brazil

João Antonio de Queiroz Oliveira, Antonio Luiz Pinho Ribeiro, Daniel Dias Ribeiro, Vandack Nobre, Manoel Otávio da Costa Rocha and Maria Auxiliadora Parreiras Martins

PLOS ONE, 2018, vol. 13, issue 10, 1-15

Abstract: Introduction: Bleeding is a common complication in patients taking warfarin. We sought to compare the performance of nine prediction models for bleeding risk in warfarin-treated Brazilian outpatients. Methods: The dataset was derived from a clinical trial conducted to evaluate the efficacy of an anticoagulation clinic at a public hospital in Brazil. Overall, 280 heart disease outpatients taking warfarin were enrolled. The prediction models OBRI, Kuijer et al., Kearon et al., HEMORR2HAGES, Shireman et al., RIETE, HAS-BLED, ATRIA and ORBIT were compared to evaluate the overall model performance by Nagelkerke’s R2 estimation, discriminative ability based on the concordance (c) statistic and calibration based on the Hosmer-Lemeshow goodness-of-fit statistic. The primary outcomes were the first episodes of major bleeding, clinically relevant non-major bleeding and non-major bleeding events within 12 months of follow-up. Results: Major bleeding occurred in 14 participants (5.0%), clinically relevant non-major bleeding in 29 (10.4%), non-major bleeding in 154 (55.0%) and no bleeding at all in 115 (41.1%). Most participants with major bleeding had their risk misclassified. All the models showed low overall performance (R2 0.6–9.3%) and poor discriminative ability for predicting major bleeding (c

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0205970

DOI: 10.1371/journal.pone.0205970

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