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Identifying the Risks of Anticoagulation in Patients with Substance Abuse

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ABSTRACT

BACKGROUND

Warfarin is effective in preventing thromboembolic events, but concerns exist regarding its use in patients with substance abuse.

OBJECTIVE

Identify which patients with substance abuse who receive warfarin are at risk for poor outcomes.

DESIGN

Retrospective cohort study. Diagnostic codes, lab values, and other factors were examined to identify risk of adverse outcomes.

PATIENTS

Veterans AffaiRs Study to Improve Anticoagulation (VARIA) database of 103,897 patients receiving warfarin across 100 sites.

MAIN MEASURES

Outcomes included percent time in therapeutic range (TTR), a measure of anticoagulation control, and major hemorrhagic events by ICD-9 codes.

RESULTS

Nonusers had a higher mean TTR (62 %) than those abusing alcohol (53 %), drugs (50 %), or both (44 %, p < 0.001). Among alcohol abusers, an increasing ratio of the serum hepatic transaminases aspartate aminotransferase/alanine aminotransferase (AST:ALT) correlated with inferior anticoagulation control; normal AST:ALT ≤ 1.5 predicted relatively modest decline in TTR (54 %, p < 0.001), while elevated ratios (AST:ALT 1.50–2.0 and > 2.0) predicted progressively poorer anticoagulation control (49 % and 44 %, p < 0.001 compared to nonusers). Age-adjusted hazard ratio for major hemorrhage was 1.93 in drug and 1.37 in alcohol abuse (p < 0.001 compared to nonusers), and remained significant after also controlling for anticoagulation control and other bleeding risk factors (1.69 p < 0.001 and 1.22 p = 0.003). Among alcohol abusers, elevated AST:ALT >2.0 corresponded to more than three times the hemorrhages (HR 3.02, p < 0.001 compared to nonusers), while a normal ratio AST:ALT ≤ 1.5 predicted a rate similar to nonusers (HR 1.19, p < 0.05).

CONCLUSIONS

Anticoagulation control is particularly poor in patients with substance abuse. Major hemorrhages are more common in both alcohol and drug users. Among alcohol abusers, the ratio of AST/ALT holds promise for identifying those at highest risk for adverse events.

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REFERENCES

  1. Compton WM, Thomas YF, Stinson FS, Grant BF. Prevalence, correlates, disability, and comorbidity of DSM-IV drug abuse and dependence in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry. 2007;64:566–76.

    Article  PubMed  Google Scholar 

  2. Hasin DS, Stinson FS, Ogburn E, Grant BF. Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry. 2007;64:830–42.

    Article  PubMed  Google Scholar 

  3. Ansell J, Hirsh J, Hylek E, Jacobson A, Crowther M, Palareti G. Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th edition). Chest. 2008;133:160S–98S.

    Article  PubMed  CAS  Google Scholar 

  4. Havrda DE, Mai T, Chonlahan J. Enhanced antithrombotic effect of warfarin associated with low-dose alcohol consumption. Pharmacotherapy. 2005;25:303–7.

    Article  PubMed  Google Scholar 

  5. Connolly SJ, Ezekowitz MD, Yusuf S, et al. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med. 2009;361:1139–51.

    Article  PubMed  CAS  Google Scholar 

  6. Granger CB, Alexander JH, McMurray JJ, et al. Apixaban versus warfarin in patients with atrial fibrillation. N Engl J Med. 365:981–92.

  7. Patel MR, Mahaffey KW, Garg J, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med. 2011;365:883–91.

    Article  PubMed  CAS  Google Scholar 

  8. Schulman S, Kearon C, Kakkar AK, et al. Dabigatran versus warfarin in the treatment of acute venous thromboembolism. N Engl J Med. 2009;361:2342–52.

    Article  PubMed  CAS  Google Scholar 

  9. Dawson DA, Saha TD, Grant BF. A multidimensional assessment of the validity and utility of alcohol use disorder severity as determined by item response theory models. Drug Alcohol Depend. 2010;107:31–8.

    Article  PubMed  Google Scholar 

  10. Liangpunsakul S, Qi R, Crabb DW, Witzmann F. Relationship between alcohol drinking and aspartate aminotransferase:alanine aminotransferase (AST:ALT) ratio, mean corpuscular volume (MCV), gamma-glutamyl transpeptidase (GGT), and apolipoprotein A1 and B in the U.S. population. J Stud Alcohol Drugs. 2010;71:249–52.

    PubMed  Google Scholar 

  11. Rose AJ, Hylek EM, Ozonoff A, Ash AS, Reisman JI, Berlowitz DR. Patient characteristics associated with oral anticoagulation control: results of the Veterans AffaiRs Study to Improve Anticoagulation (VARIA). J Thromb Haemost. 2010;8:2182–91.

    Article  PubMed  CAS  Google Scholar 

  12. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998;158:1789–95.

    Article  PubMed  CAS  Google Scholar 

  13. Hannuksela ML, Liisanantti MK, Nissinen AE, Savolainen MJ. Biochemical markers of alcoholism. Clin Chem Lab Med. 2007;45:953–61.

    Article  PubMed  CAS  Google Scholar 

  14. Rosendaal FR, Cannegieter SC, van der Meer FJ, Briet E. A method to determine the optimal intensity of oral anticoagulant therapy. Thromb Haemost. 1993;69:236–9.

    PubMed  CAS  Google Scholar 

  15. Schulman S, Kearon C. Definition of major bleeding in clinical investigations of antihemostatic medicinal products in non-surgical patients. J Thromb Haemost. 2005;3:692–4.

    Article  PubMed  CAS  Google Scholar 

  16. Jasuja GK, Reisman JI, Miller DR, et al. Identifying Major Hemorrhage with Automated Data: Results of the Veterans Affairs Study to Improve Anticoagulation (VARIA). Thrombosis research. 2012.

  17. Lip GY, 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;57:173–80.

    Article  PubMed  CAS  Google Scholar 

  18. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130:461–70.

    Article  PubMed  CAS  Google Scholar 

  19. Bungard TJ, Ghali WA, Teo KK, McAlister FA, Tsuyuki RT. Why do patients with atrial fibrillation not receive warfarin? Arch Intern Med. 2000;160:41–6.

    Article  PubMed  CAS  Google Scholar 

  20. 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;161:2458–63.

    Article  PubMed  CAS  Google Scholar 

  21. Monette J, Gurwitz JH, Rochon PA, Avorn J. Physician attitudes concerning warfarin for stroke prevention in atrial fibrillation: results of a survey of long-term care practitioners. J Am Geriatr Soc. 1997;45:1060–5.

    PubMed  CAS  Google Scholar 

  22. Ogilvie IM, Newton N, Welner SA, Cowell W, Lip GY. Underuse of oral anticoagulants in atrial fibrillation: a systematic review. Am J Med. 2010;123:638–45 e4.

    Article  PubMed  CAS  Google Scholar 

  23. Baczek VL, Chen WT, Kluger J, Coleman CI. Predictors of warfarin use in atrial fibrillation in the United States: a systematic review and meta-analysis. BMC Fam Pract. 2012;13:5.

    Article  PubMed  Google Scholar 

  24. Chen WT, White CM, Phung OJ, et al. Are the risk factors listed in warfarin prescribing information associated with anticoagulation-related bleeding? A systematic literature review. Int J Clin Pract. 2011;65:749–63.

    Article  PubMed  CAS  Google Scholar 

  25. Schauer DP, Moomaw CJ, Wess M, Webb T, Eckman MH. Psychosocial risk factors for adverse outcomes in patients with nonvalvular atrial fibrillation receiving warfarin. J Gen Intern Med. 2005;20:1114–9.

    Article  PubMed  Google Scholar 

  26. Connolly SJ, Pogue J, Eikelboom J, et al. Benefit of oral anticoagulant over antiplatelet therapy in atrial fibrillation depends on the quality of international normalized ratio control achieved by centers and countries as measured by time in therapeutic range. Circulation. 2008;118:2029–37.

    Article  PubMed  CAS  Google Scholar 

  27. van Leeuwen Y, Rosendaal FR, Cannegieter SC. Prediction of hemorrhagic and thrombotic events in patients with mechanical heart valve prostheses treated with oral anticoagulants. J Thromb Haemost. 2008;6:451–6.

    Article  PubMed  Google Scholar 

  28. Veeger NJ, Piersma-Wichers M, Tijssen JG, Hillege HL, van der Meer J. Individual time within target range in patients treated with vitamin K antagonists: main determinant of quality of anticoagulation and predictor of clinical outcome. A retrospective study of 2300 consecutive patients with venous thromboembolism. Br J Haematol. 2005;128:513–9.

    Article  PubMed  Google Scholar 

  29. Wallentin L, Yusuf S, Ezekowitz MD, et al. Efficacy and safety of dabigatran compared with warfarin at different levels of international normalised ratio control for stroke prevention in atrial fibrillation: an analysis of the RE-LY trial. Lancet. 2010;376:975–83.

    Article  PubMed  CAS  Google Scholar 

  30. White HD, Gruber M, Feyzi J, et al. Comparison of outcomes among patients randomized to warfarin therapy according to anticoagulant control: results from SPORTIF III and V. Arch Intern Med. 2007;167:239–45.

    Article  PubMed  CAS  Google Scholar 

  31. Arnason T, Wells PS, van Walraven C, Forster AJ. Accuracy of coding for possible warfarin complications in hospital discharge abstracts. Thromb Res. 2006;118:253–62.

    Article  PubMed  CAS  Google Scholar 

  32. Tamariz L, Harkins T, Nair V. A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):154–62.

    Article  PubMed  Google Scholar 

  33. White RH, Garcia M, Sadeghi B, et al. Evaluation of the predictive value of ICD-9-CM coded administrative data for venous thromboembolism in the United States. Thromb Res. 2010;126:61–7.

    Article  PubMed  CAS  Google Scholar 

  34. Hastie TJ, Tibshirani RJ. Generalized additive models. New York: Chapman and Hall; 1990.

    Google Scholar 

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Acknowledgements

Contributors

No further contributors.

Funding

This study was supported by a grant from VA Health Services Research and Development (IIR-10-374). Dr. Rose is supported by a career development award from VA Health Services Research and Development (CDA-08-017). The sponsor had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or the preparation, review, and approval of the manuscript.

Disclaimer

The opinions expressed in this manuscript do not necessarily represent the official views of the Department of Veterans Affairs.

Guarantor

Dr. Rose is the guarantor of the entire manuscript.

Presentations

No prior presentations.

Conflict of Interest

The authors declare that they do not have any conflicts of interest.

Author information

Authors and Affiliations

  1. Center for Health Quality, Outcomes, and Economic Research, Bedford VA Medical Center, Bedford, MA, USA

    Donald R. Miller ScD, Arlene S. Ash PhD, Dan R. Berlowitz MD, MPH, Al Ozonoff PhD, Shibei Zhao MPH, Joel I. Reisman AB, Guneet K. Jasuja PhD & Adam J. Rose MD, MSc, FACP

  2. Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, 72 East Concord Street, Evans 124, Boston, MA, 02118, USA

    Lydia M. Efird MD, Arlene S. Ash PhD, Dan R. Berlowitz MD, MPH & Adam J. Rose MD, MSc, FACP

  3. Department of Health Policy and Management, Boston University School of Public Health, Boston, MA, USA

    Donald R. Miller ScD, Dan R. Berlowitz MD, MPH & Guneet K. Jasuja PhD

  4. Department of Quantitative Health Sciences, Division of Biostatistics and Health Services Research, University of Massachusetts School of Medicine, Worcester, MA, USA

    Arlene S. Ash PhD

  5. Biostatistics Section, Boston Children’s Hospital, Boston, MA, USA

    Al Ozonoff PhD

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  1. Lydia M. Efird MD
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Correspondence to Lydia M. Efird MD.

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Efird, L.M., Miller, D.R., Ash, A.S. et al. Identifying the Risks of Anticoagulation in Patients with Substance Abuse. J GEN INTERN MED 28, 1333–1339 (2013). https://doi.org/10.1007/s11606-013-2453-x

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  • DOI: https://doi.org/10.1007/s11606-013-2453-x

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