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Improved Risk Assessment for Low-risk Atrial Fibrillation Patients

Discover the superior performance of a novel machine-learning tool in identifying atrial fibrillation patients with low thromboembolic risk who are poorly characterized by existing risk scores.

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Improved Risk Assessment for Low-risk Atrial Fibrillation Patients

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  1. Identifying patients with atrial fibrillation and "truly low" thromboembolic risk who are poorly characterized by CHA2DS2-VASc: Superior performance of a novel machine-learning tool in GARFIELD-AF Keith A.A. Fox, Joseph E. Lucas, Karen S. Pieper, Jean-Pierre Bassand, A. John Camm, David A. Fitzmaurice, Werner Hacke, Gloria Kayani, Ali Oto, Ajay K. Kakkar for the GARFIELD-AF Investigators

  2. Background and Context • The role of anticoagulation for patients with AF and ≥ 1 risk factor for stroke/systemic embolism is defined by trial evidence and guidelines • Between 2010-2011 and 2014-2015, anticoagulation usage rose from 57% to 71% of patients with AF • However, the balance of risk and benefit is poorly defined for “low risk’ AF • Camm AJ et al. Heart 2016 (in press)

  3. How are low and high risk AF patients managed in practice? • Contrary to international guideline recommendations, • 28% high-risk patients (CHA2DS2-VASc ≥2) are not anticoagulated • 51% of very low-risk patients (CHA2DS2-VASc 0) are anticoagulated CHA2DS2-VASc 0 1 ≥2 Factors beyond those in current risk scores appear to influence prescribing decisions on anticoagulation, including risk of bleed • Camm AJ et al. Heart 2016 (in press)

  4. Purpose: To provide accurate estimates of risk as the basis of decisions on prescribing or withholding anticoagulation Aim: To derive and validate a more accurate and user-friendly method of stratifying patients according to risks of death, stroke and bleeding

  5. Statistical Methods: The GARFIELD Score A “machine learning” approach to risk modelling • Coalescent regression avoids theneed to specify levels of relatedness in the statistical model, it allows joint modeling of all outcomes. • Models were based on 38984 patients in GARFIELD 2010 to 2015 for: • all-cause mortality, • ischaemic stroke/thromboembolism, and • haemorrhagic stroke/major bleed that occurred within 1-year of enrolment into GARFIELD­AF. • Also, a simplified model was also derived to facilitate web applications • The performance of both models were compared with CHA2DS2-VASc in all patients and those with a low risk of stroke • External validation was undertaken using an independent contemporary registry ORBIT-AF

  6. Number of events in low- and higher-risk patients at 1 year Number of events determined using one year Kaplan-Meier rates • Low risk patients (defined as CHA2DS2-VASc 0 or 1 for men and 1 or 2 for women) represent 20.2% of overall cohort • Total number of patients: 38,984 enrolled between March 2010 and July 2015

  7. GARFIELD Score performance characteristics in all patients Ischaemic stroke / Systemic embolism Haemorrhagic stroke / Major bleed All-cause mortality C statistic: 0.78 C statistic: 0.63 C statistic: 0.67

  8. Comparison of GARFIELD Score with CHA2DS2-VASc in all patients

  9. Comparison of GARFIELD Score with CHA2DS2-VASc in low-risk patientsCHA2DS2-VASc 0 or 1 for men and 1 or 2 for women

  10. Performance of the new simplified GARFIELD Score in patients enrolled in GARFIELD-AF and ORBIT-I *C statistic for HAS-BLED is 0.64 (95% CI 0.59, 0.68) 1. Evaluation of a subset of patients who were prescribed oral anticoagulants in countries where at least 1% bleeding rate was recorded

  11. Conclusions • Performance of GARFIELD Score was superior to CHA2DS2-VASc in predicting ischaemic stroke or major bleed in all patients, and those with a low­ risk of stroke • This integrated risk tool has the potential for incorporation in routine electronic systems

  12. Next steps • A simplified GARFIELD Score, validated using data from ORBIT-AF, is being developed, with web-based and mobile device applications* • The GARFIELD Score may help physicians assess the appropriateness of anticoagulation in low-risk patients *http://colab-sbx-322.oit.duke.edu:3338/

  13. BLEEDING SCORE 20% Risk of major bleed in 1 year

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