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

Author

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

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

Suggested Citation

  • João Antonio de Queiroz Oliveira & Antonio Luiz Pinho Ribeiro & Daniel Dias Ribeiro & Vandack Nobre & Manoel Otávio da Costa Rocha & Maria Auxiliadora Parreiras Martins, 2018. "Predictive ability of scores for bleeding risk in heart disease outpatients on warfarin in Brazil," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
  • Handle: RePEc:plo:pone00:0205970
    DOI: 10.1371/journal.pone.0205970
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