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

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. The dataset was derived from a clinical trial conducted to evaluate the efficacy of an anticoagulation clinic at...

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Bibliographic Details
Published in:PloS one 2018-10, Vol.13 (10), p.e0205970-e0205970
Main Authors: Oliveira, João Antonio de Queiroz, Pinho Ribeiro, Antonio Luiz, Ribeiro, Daniel Dias, Nobre, Vandack, Rocha, Manoel Otávio da Costa, Martins, Maria Auxiliadora Parreiras
Format: Article
Language:English
Subjects:
Analysis
Anticoagulants
Atria
Biology and Life Sciences
Bleeding
Calibration
Cardiac arrhythmia
Cardiovascular disease
Care and treatment
Clinical trials
Complications and side effects
Coronary artery disease
Goodness of fit
Health risk assessment
Health risks
Heart
Heart diseases
Hemorrhage
Hospitals
Management
Mathematical models
Medicine and Health Sciences
Outcome and process assessment (Medical care)
Patients
People and places
Performance prediction
Physical Sciences
Prediction models
Public hospitals
Research and Analysis Methods
Risk factors
Social Sciences
Thromboembolism
Thrombosis
Warfarin
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Summary: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. 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. 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
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0205970