Accurate prediction of hemorrhage risk on warfarin is vital to the anticoagulation decision. Based on five easily available clinical variables, the ATRIA score reflects the experience of a large, diverse group of patients with atrial fibrillation assembled from community care and followed for a longer time period than prior studies. The model development used rigorous contemporary methods such as split-sample testing and bootstrap sampling approaches to underwrite internal validity.
When collapsed into a 3-category risk score, the ATRIA risk scheme was able to identify sizable proportions of patients who fell into the most clinically meaningful categories, i.e., low or high risk for hemorrhage. The low-risk category, accounting for 83% of follow-up, had an observed major hemorrhage rate of < 1% per year. The high-risk category represented only 10.2% of patient follow-up yet accounted for 42% of the major bleeding events. The ATRIA scheme led to improvements in accurate net reclassification when compared to alternative schemes. The c-index of 0.74, while not representing perfect discrimination, indicates good performance for a prediction model and compares favorably to other widely used risk stratification schemes such as the CHADS2
stroke risk index, which has a c-index of ~0.6(15
). Certainly, identifying novel predictors of bleeding and improving current methods of risk stratification are important areas of further investigation.
The variables in our model have each been linked to increased hemorrhage risk in prior studies(5
). Anemia was strongly associated with future bleeding risk. Although we were unable to determine the mechanism of association, anemia may reflect a predisposition to hemorrhage or recent subclinical hemorrhage. Severe renal disease was also a powerful predictor of hemorrhage risk. All-cause prior bleeding was associated with future bleeding, and presumably identifies patients with a potential bleeding lesion or diathesis. Finally, older age and hypertension were independently associated with hemorrhage risk. Similar to other hemorrhage risk schemes, this analysis focused on all-cause major hemorrhage, both intracranial and extracranial. Although intracranial hemorrhages are the most important outcomes, the rarity of such events makes their risk prediction challenging(16
). High quality models to predict intracranial hemorrhage are vitally needed.
Our risk model is clinically applicable when counseling patients about the relative benefits and harms of anticoagulation. Particularly as newer, easier to administer anticoagulants become available, accurate estimates of hemorrhage risk will strongly influence the anticoagulation decision. Our risk score may not affect the anticoagulation decision for most patients at high risk for stroke, since they derive a large benefit from anticoagulation. However, bleeding risk is significantly more influential in patients at moderate or lower stroke risk. Our bleeding risk estimates can be incorporated into formal decision-analysis models or can be used to counsel individual patients about their estimated risks of stroke and bleeding. For such patients, providing estimates of the risk of bleeding on anticoagulation can be a very informative addition to individualized patient decision-making.
There are several limitations to our analysis. Our assessment of clinical risk factors was based on computerized databases that did not have information on several covariates such as measurements of blood pressure and genotype. We lacked information about non-prescription use of aspirin or NSAIDs. Although the hemorrhage rate in ATRIA was generally lower than described by the other risk schemes, the rates are similar to some recent randomized trials(17
). Finally, it will be important to test the ATRIA risk scheme in a separate population. Although internal validation reduces the likelihood of chance playing a major role in development of our model, external validity needs to be tested empirically.
The risk of anticoagulant-associated hemorrhage is a major deterrent to more widespread use of anticoagulants. Risk stratification schemes can help clinicians estimate the magnitude of hemorrhage risk when prescribing or continuing anticoagulant therapy. Such schemes can also provide important information for comparing the hemorrhage risk of patients enrolled in clinical studies or when comparing the safety of different anticoagulation strategies(18