Which Risk Score Best Predicts Bleeding With Warfarin in Atrial Fibrillation?

It has been estimated that 2.2 million people in the United States and 4.5 million people in the European Union suffer from atrial fibrillation (AF).(1) The prevalence of AF is rapidly increasing as the population ages, with a rate of approximately 8% in individuals older than 80 years of age.(2) Thromboembolism, primarily ischemic stroke, is the most feared and devastating complication of AF.(3-7)

Vitamin K antagonists (VKAs), such as warfarin, have been the standard anticoagulant prescribed for prevention of stroke in patients with AF for over 55 years old. However warfarin has a number of limitations including slow onset of action, multiple food and drug interactions, genetic variability in metabolism, and frequent monitoring of international normalized ratio (INR) due to limited therapeutic index that complicate therapy.(8-12) It is estimated that less than half of warfarin-ligible AF patients are ultimately treated,13-15) and one of the main reasons cited by physicians and patients is the fear of iatrogenic bleeding.(16, 17)

The CHADS2 is a widely used and accepted clinical risk score for evaluating thromboembolic risk in patients with AF.(18) However, for individual patients we must balance the benefit of anticoagulation with the potential risk of serious bleeding. Various clinical factors have been associated with incremental bleeding risk. Numerous bleeding risk assessment strategies have been proposed but complicated scoring systems, varying predictive values and lack of consensus have limited their widespread adoption. We will review three current clinical prediction rules for bleeding in AF that have been developed.

HEMORR2HAGES

HEMORR(underscore 2)HAGESThe HEMORR2HAGES risk score was developed from 3 prior clinical prediction rules and a systematic literature review and validated in 3791 AF patients in a combined Medicare inpatient administrative dataset from 7 states.(19) The score assigns 2 points for a prior bleed and 1 point for each Hepatic or renal disease, Ethanol abuse, Malignancy, Older age (age >75 years), Reduced platelet count or function, Hypertension (uncontrolled), Anemia, Genetic factors, Excessive fall risk and Stroke. Patients can be categorized into low, intermediate and high bleeding risk according to scores of 0-1, 2-3 and ≥4, respectively. In patients prescribed warfarin, HEMORR2HAGES had a greater predictive accuracy (c-statistic 0.67) than older bleed prediction schemes. The rate of bleeding in patients prescribed warfarin was ≥10% in the highest risk category (≥4), although only 25% of the bleeds occurred in this group. The score performed similarly in subjects prescribed aspirin (c-statistic 0.72) or no antithrombotic therapy (c-statistic 0.66).

HAS-BLED

HAS-BLED Information GraphicThe HAS-BLED score was derived from 3,978 patients in the EURO Heart Survey on AF.(20) The score assigns points for Hypertension (one point for uncontrolled, >160 mm Hg systolic), Abnormal renal/liver function (one point each for presence of renal or liver impairment), Stroke (one point for pervious history, particularly lacunar), Bleeding history of predisposition (anemia) (one point), Labile INR (one point for time in therapeutic range < 60%), Elderly (one point for >65 years), Drugs/alcohol concomitantly (one point for antiplatelet or nonsteroidal anti-inflammatory drugs and one point for alcohol excess). The predictive accuracy in the overall population was good in the overall population (c-statistic 0.72) and was consistent across subgroups. The score performed particularly well in patients receiving antiplatelet agents (C statistic 0.91) or no antithrombotic therapy (c-statistic 0.85). Further validation was performed in the SPORTIF II clinical trials.(21) C-statistics for prediction of a major bleeding were similar in the entire cohort (0.66) and in those patients assigned to warfarin (0.67) and were marginally better than the other schemas evaluated, including HEMORR2HAGES. Based on the HAS-BLED score, 20.4% of patients were low risk (score=0), 60.9% moderate risk (score 1-3) and 18.7% high risk (score >3) with corresponding major bleeding rates of 0.9%, 3.7% and 6.7% respectively. However, only 10.7% of bleeds occurred in the high risk category. In an unselected nationwide cohort (Denmark) of hospitalized patients with AF, HAS-BLED performed similarly to HEMORR2HAGES in predicting bleeding risk.(22)

HAS-BLED was recently included in the European Society of Cardiology guidelines on treatment of patients with AF,(23) as well as the Canadian Cardiovascular Society AF guidelines.(24)

ATRIA

ATRIA information graphicThe ATRIA (Anticoagulation and Risk Factors in Atrial Fibrillation) score was derived from 13,559 adults with AF enrolled in Kaiser Permanente healthcare system in Northern California.(25) The patients were randomly divided into a split-sample derivation and validation cohort. Five independent variables were included in the final model: anemia (hemoglobin <13 g/dl in men and <12 g/dl in women) (3 points), severe renal disease (glomerular filtration rate <30 ml/min or dialysis dependent) (3points), age ≥75 years (2 points), prior bleeding (1 point) and hypertension (1 point). Collapsed into a 3-category risk score, major bleeding rates were 0.8% for low risk (0-3 points), 2.6% for intermediate risk (4 points) and 5.8% for high risk (≥5). The high risk category effectively concentrated bleeding events such that 42% of events occurred in 10.2% of cohort person-years. The low risk category accounted for 83% of follow-up and had an observed bleeding rate <1%. The c-statistic was 0.74 for the continuous score and 0.69 for the 3-category score, higher than in other risk scores assessed which included HEMORR2HAGES but not HAS-BLED.

Considerations

All of these scores are easier to use than their predecessors with most risk factors readily available from the medical history or routinely tested in AF patients being evaluated for anticoagulation – this is particularly true for HAS-BLED and ATRIA which contain fewer variables and do not include genetic testing. HAS-BLED has been validated in several cohorts and has begun to be incorporated into national and regional guidelines. It is important to note, however, that HAS-BLED incorporates labile INR, which is a characteristic post-initiation of warfarin. ATRIA performs particularly well in categorizing high risk patients such that a significant proportion of bleeding events occur in that group compared to much smaller percentages in the other scores. A limitation of ATRIA, acknowledged by the developers, is that the database from which score was derived did not contain information on blood pressure or concomitant medications known to increase bleeding risk with warfarin (antiplatelet and nonsteroidal anti-inflammatory medications). ATRIA is also awaiting validation in a second dataset.

Conclusions

These simple clinical prediction scores for bleeding are important tools for accurately assessing the risks and benefits of anticoagulation in patients with AF. With the new factor Xa and IIa inhibitors offering the potential of effective and potentially safer anticoagulation we will likely see a paradigm shift where anticoagulation is recommended to a broader population currently thought to be “low risk” for stroke. These scores will need to be validated and potentially modified for these agents in addition to warfarin. Before widespread adoption of any bleeding prediction rule, further prospective studies need to be performed.

References

  1. Feinberg WM, Cornell ES, Nightingale SD, et al. Relationship between prothrombin activation fragment F1.2 and international normalized ratio in patients with atrial fibrillation. stroke prevention in atrial fibrillation investigators. Stroke. 1997; 28:1101-1106.
  2. Furberg CD, Psaty BM, Manolio TA, Gardin JM, Smith VE, Rautaharju PM. Prevalence of atrial fibrillation in elderly subjects (the cardiovascular health study). Am J Cardiol. 1994; 74:236-241.
  3. Fatkin D, Kelly RP, Feneley MP. Relations between left atrial appendage blood flow velocity, spontaneous echocardiographic contrast and thromboembolic risk in vivo. J Am Coll Cardiol. 1994; 23:961-969.
  4. Hwang JJ, Ko FN, Li YH, et al. Clinical implications and factors related to left atrial spontaneous echo contrast in chronic nonvalvular atrial fibrillation. Cardiology. 1994; 85:69-75.
  5. Pop GA, Meeder HJ, Roelandt JR, et al. Transthoracic echo/Doppler in the identification of patients with chronic non-valvular atrial fibrillation at risk for thromboembolic events. Eur Heart J. 1994; 15:1545-1551.
  6. Conway DS, Pearce LA, Chin BS, Hart RG, Lip GY. Plasma von willebrand factor and soluble p-selectin as indices of endothelial damage and platelet activation in 1321 patients with nonvalvular atrial fibrillation: Relationship to stroke risk factors. Circulation. 2002; 106:1962-1967.
  7. Conway DS, Pearce LA, Chin BS, Hart RG, Lip GY. Prognostic value of plasma von willebrand factor and soluble P-selectin as indices of endothelial damage and platelet activation in 994 patients with nonvalvular atrial fibrillation. Circulation. 2003; 107:3141-3145.
  8. Ansell J, Hirsh J, Poller L, Bussey H, Jacobson A, Hylek E. The pharmacology and management of the vitamin K antagonists: The seventh ACCP conference on antithrombotic and thrombolytic therapy. Chest. 2004; 126:204S-233S.
  9. Turpie AG. New oral anticoagulants in atrial fibrillation. Eur Heart J. 2008; 29:155-165.
  10. Aithal GP, Day CP, Kesteven PJ, Daly AK. Association of polymorphisms in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications. Lancet. 1999; 353:717-719.
  11. D'Andrea G, D'Ambrosio RL, Di Perna P, et al. A polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood. 2005; 105:645-649.
  12. Marin F, Gonzalez-Conejero R, Capranzano P, Bass TA, Roldan V, Angiolillo DJ. Pharmacogenetics in cardiovascular antithrombotic therapy. J Am Coll Cardiol. 2009; 54:1041-1057.
  13. Jones M, McEwan P, Morgan CL, Peters JR, Goodfellow J, Currie CJ. Evaluation of the pattern of treatment, level of anticoagulation control, and outcome of treatment with warfarin in patients with non-valvar atrial fibrillation: A record linkage study in a large british population. Heart. 2005; 91:472-477.
  14. McCormick D, Gurwitz JH, Goldberg RJ, et al. Prevalence and quality of warfarin use for patients with atrial fibrillation in the long-term care setting. Arch Intern Med. 2001; 161:2458-2463.
  15. Fang MC, Stafford RS, Ruskin JN, Singer DE. National trends in antiarrhythmic and antithrombotic medication use in atrial fibrillation. Arch Intern Med. 2004; 164:55-60.
  16. Bungard TJ, Ghali WA, McAlister FA, et al. The relative importance of barriers to the prescription of warfarin for nonvalvular atrial fibrillation. Can J Cardiol. 2003; 19:280-284.
  17. Gross CP, Vogel EW, Dhond AJ, et al. Factors influencing physicians' reported use of anticoagulation therapy in nonvalvular atrial fibrillation: A cross-sectional survey. Clin Ther. 2003; 25:1750-1764.
  18. Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: Results from the national registry of atrial fibrillation. JAMA. 2001; 285:2864-2870.
  19. Gage BF, Yan Y, Milligan PE, et al. Clinical classification schemes for predicting hemorrhage: Results from the national registry of atrial fibrillation (NRAF). Am Heart J. 2006; 151:713-719.
  20. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJ, Lip GY. A novel user-friendly score (HAS-BLED) to assess one-year risk of major bleeding in atrial fibrillation patients: The euro heart survey. Chest. 2010; 138:1093-100.
  21. Lip GYH, Frison L, Halperin JL, Lane DA. Comparative validation of a novel risk score for predicting bleeding risk in anticoagulated patients with atrial fibrillation: The HAS-BLED (hypertension, abnormal Renal/Liver function, stroke, bleeding history or predisposition, labile INR, elderly, Drugs/Alcohol concomitantly) score. J Am Coll Cardiol. 2011; 57:173-180.
  22. Olesen JB, Lip GY, Hansen PR, et al. Bleeding risk in 'real world' patients with atrial fibrillation: Comparison of two established bleeding prediction schemes in a nationwide cohort. J Thromb Haemost. 2011; 9:1460-1467.
  23. European Heart Rhythm Association, European Association for Cardio-Thoracic Surgery, Camm AJ, et al. Guidelines for the management of atrial fibrillation: The task force for the management of atrial fibrillation of the european society of cardiology (ESC). Eur Heart J. 2010; 31:2369-2429.
  24. Cairns JA, Connolly S, McMurtry S, Stephenson M, Talajic M, CCS Atrial Fibrillation Guidelines Committee. Canadian cardiovascular society atrial fibrillation guidelines 2010: Prevention of stroke and systemic thromboembolism in atrial fibrillation and flutter. Can J Cardiol. 2011; 27:74-90.
  25. Fang MC, Go AS, Chang Y, et al. A new risk scheme to predict warfarin-associated hemorrhage: The ATRIA (anticoagulation and risk factors in atrial fibrillation) study. J Am Coll Cardiol. 2011; 58:395-401.

Clinical Topics: Anticoagulation Management, Arrhythmias and Clinical EP, Dyslipidemia, Prevention, Anticoagulation Management and Atrial Fibrillation, Atrial Fibrillation/Supraventricular Arrhythmias, Lipid Metabolism, Novel Agents, Hypertension

Keywords: Atrial Fibrillation, California, Consensus, Denmark, European Union, Factor Xa, Hemorrhage, Hypertension, International Normalized Ratio, Risk Assessment, Stroke, Thromboembolism, United States, Warfarin


< Back to Listings