Individualised prediction of major bleeding in patients with atrial fibrillation treated with anticoagulation
Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients. To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the impor...
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| Vydáno v: | PloS one Ročník 19; číslo 11; s. e0312294 |
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Public Library of Science
14.11.2024
Public Library of Science (PLoS) |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients.
To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors.
A nationwide register-based cohort study.
Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis.
The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration.
Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6).
We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. |
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| AbstractList | Background Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients. Aim To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors. Design A nationwide register-based cohort study. Participants Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis. Method The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration. Results Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6). Conclusion We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients. To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors. A nationwide register-based cohort study. Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis. The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration. Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6). We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. Background Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients. Aim To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors. Design A nationwide register-based cohort study. Participants Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis. Method The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration. Results Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6). Conclusion We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients.BACKGROUNDAnticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients.To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors.AIMTo predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors.A nationwide register-based cohort study.DESIGNA nationwide register-based cohort study.Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis.PARTICIPANTSDanish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis.The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration.METHODThe individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration.Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6).RESULTSAmong 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6).We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling.CONCLUSIONWe propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. BackgroundAnticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients.AimTo predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors.DesignA nationwide register-based cohort study.ParticipantsDanish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis.MethodThe individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration.ResultsAmong 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6).ConclusionWe propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients. To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors. A nationwide register-based cohort study. Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis. The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration. Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6). We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling. |
| Audience | Academic |
| Author | J.-Y. Lee, Christina Ozenne, Brice Phelps, Matthew Toft-Petersen, Anne Pernille Gerds, Thomas Alexander Torp-Pedersen, Christian |
| AuthorAffiliation | 2 The Danish Heart Foundation, Copenhagen, Denmark 5 Department of Biostatistics, University of Copenhagen, Copenhagen, Denmark Qatar University, QATAR 1 Department of Cardiology and Clinical Research, Nordsjællands Hospital, University of Copenhagen, Hillerød, Denmark 4 Neurobiology Research Unit and BrainDrugs, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark 3 Department of Public Health, Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark |
| AuthorAffiliation_xml | – name: 1 Department of Cardiology and Clinical Research, Nordsjællands Hospital, University of Copenhagen, Hillerød, Denmark – name: 2 The Danish Heart Foundation, Copenhagen, Denmark – name: 4 Neurobiology Research Unit and BrainDrugs, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark – name: 5 Department of Biostatistics, University of Copenhagen, Copenhagen, Denmark – name: 3 Department of Public Health, Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark – name: Qatar University, QATAR |
| Author_xml | – sequence: 1 givenname: Anne Pernille orcidid: 0000-0001-6029-255X surname: Toft-Petersen fullname: Toft-Petersen, Anne Pernille – sequence: 2 givenname: Christina surname: J.-Y. Lee fullname: J.-Y. Lee, Christina – sequence: 3 givenname: Matthew surname: Phelps fullname: Phelps, Matthew – sequence: 4 givenname: Brice surname: Ozenne fullname: Ozenne, Brice – sequence: 5 givenname: Thomas Alexander surname: Gerds fullname: Gerds, Thomas Alexander – sequence: 6 givenname: Christian orcidid: 0000-0003-2892-6131 surname: Torp-Pedersen fullname: Torp-Pedersen, Christian |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39541367$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_7759_cureus_82475 |
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| Copyright | Copyright: © 2024 Toft-Petersen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2024 Public Library of Science 2024 Toft-Petersen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2024 Toft-Petersen et al 2024 Toft-Petersen et al 2024 Toft-Petersen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: CTP is supported by grants from Novo Nordic and Bayer. All other authors declared no conflict of interest. There was no funding for the study. |
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| Snippet | Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for... Background Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the... BackgroundAnticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute... Background Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the... |
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| SubjectTerms | Age Aged Aged, 80 and over Alcohol abuse Analysis Anticoagulants Anticoagulants (Medicine) Anticoagulants - adverse effects Anticoagulants - therapeutic use Atrial fibrillation Atrial Fibrillation - complications Atrial Fibrillation - drug therapy Bleeding Cabs Calibration Cardiac arrhythmia Care and treatment Causes of Cohort Studies Complications and side effects Denmark - epidemiology Design factors Diagnosis Female Fibrillation Hemorrhage Hemorrhage - chemically induced Humans Hypertension Logistic Models Male Medicine and Health Sciences Middle Aged Patient outcomes Patients People and Places Prediction models Predictions Prescriptions Registries Regression analysis Regression models Risk Assessment Risk Factors Stroke |
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| Title | Individualised prediction of major bleeding in patients with atrial fibrillation treated with anticoagulation |
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