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Do baseline characteristics account for geographical variations in event rates in patients with newly diagnosed atrial fibrillation? The GARFIELD-AF registry

Session Antithrombotic therapy in atrial fibrillation 1

Speaker Keith Fox

Event : ESC Congress 2016

  • Topic : arrhythmias and device therapy
  • Sub-topic : Atrial Fibrillation
  • Session type : Moderated Posters

Authors : KAA Fox (Edinburgh,GB), G Accetta (London,GB), H Darius (Berlin,DE), S Goto (Kanagawa,JP), G Kayani (London,GB), Y Koretsune (Osaka,JP), S Oh (Seoul,KR), A Parkhomenko (Kiev,UA), JPS Sawhney (New Delhi,IN), J Stepinska (Warsaw,PL), AK Kakkar (London,GB)

Authors:
K.A.A. Fox1 , G. Accetta2 , H. Darius3 , S. Goto4 , G. Kayani2 , Y. Koretsune5 , S. Oh6 , A. Parkhomenko7 , J.P.S. Sawhney8 , J. Stepinska9 , A.K. Kakkar2 , 1University of Edinburgh, Centre for Cardiovascular Science - Edinburgh - United Kingdom , 2Thrombosis Research Institute - London - United Kingdom , 3Vivantes Neukoelln Medical Centre - Berlin - Germany , 4Tokai University School of Medicine - Kanagawa - Japan , 5Osaka National Hospital - Osaka - Japan , 6Seoul National University Hospital - Seoul - Korea Republic of , 7NSC Institute of Cardiology M.D. Strazhesko - Kiev - Ukraine , 8Sir Ganga Ram Hospital - New Delhi - India , 9Institute of Cardiology - Warsaw - Poland ,

On behalf: The GARFIELD-AF investigators

Topic(s):
Atrial fibrillation (AF)

Citation:
European Heart Journal ( 2016 ) 37 ( Abstract Supplement ), 810

Purpose: To define geographical variations in all-cause mortality, stroke/systemic embolism [SE] and major bleeding in patients with newly diagnosed nonvalvular atrial fibrillation (NVAF) and to determine if this variation is accounted for by baseline risk factors.

Methods: Baseline characteristics and 1-year event rates were analysed for 28,624 patients enrolled in Mar-2010 to Oct-2014 in 32 countries. We fitted a two-level mixed Weibull model on patients' time-to-event nested for each country. A random intercept for each country was specified and adjusted for variables defined in the figure. To identify country effects greater or less than the mean global event rate, empirical Bayes means of the posterior distribution of the random coefficients were estimated.

Results: Unadjusted rates of stroke/SE averaged 1.37 per 100 patient-years and crude mortality differed by country by approx. 23-fold (0.5–11.4). There were significant differences in baseline characteristics (Table). However, having adjusted for key variables, the geographic variation in stroke/SE, mortality and major bleeding remained significant (p<0.0001 likelihood ratio test comparing the models with the one-level Weibull regression; Fig). Despite risk adjustment we observed lower mortality in Eastern Asia (Japan and Korea) and higher in countries including India and South Africa. Variations in adjusted rates of stroke/SE and bleeding remained and, unexpectedly, these were not concordant with mortality rates for respective countries (Fig).

Conclusion: Following the diagnosis of AF marked variations in outcomes exist, and persist even after adjusting for baseline risk. Additional factors including practice patterns may account for substantial differences in the rates of stroke/SE and major bleeding

Variation in baseline characteristics
Baseline characteristicsMedian1st quartile3rd quartileMinMax
Women (%)44.541.646.533.353.3
Age at diagnosis (y)69.867.271.660.974.5
Current smoker (%)9.67.312.43.815.9
Congestive heart failure (%)16.213.620.56.266.1
History of hypertension (%)76.470.984.764.392.6
Moderate-to-severe CKD (%)10.65.813.80.927.8
Coronary artery disease (%)17.512.724.29.062.4
Diabetes mellitus (%)21.316.727.013.249.2
History of bleeding (%)2.71.93.60.96.9
History of stroke (%)7.35.48.62.818.8

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