Intracranial Hemorrhage Among Patients With Atrial Fibrillation Anticoagulated With Warfarin or Rivaroxaban
The Rivaroxaban Once Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation
Background and Purpose—Intracranial hemorrhage (ICH) is a life-threatening complication of anticoagulation.
Methods—We investigated the rate, outcomes, and predictors of ICH in 14 264 patients with atrial fibrillation from Rivaroxaban Once Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF). Cox proportional hazards modeling was used.
Results—During 1.94 years (median) of follow-up, 172 patients (1.2%) experienced 175 ICH events at a rate of 0.67% per year. The significant, independent predictors of ICH were race (Asian: hazard ratio, 2.02; 95% CI, 1.39–2.94; black: hazard ratio, 3.25; 95% CI, 1.43–7.41), age (1.35; 1.13–1.63 per 10-year increase), reduced serum albumin (1.39; 1.12–1.73 per 0.5 g/dL decrease), reduced platelet count below 210×109/L (1.08; 1.02–1.13 per 10×109/L decrease), previous stroke or transient ischemic attack (1.42; 1.02–1.96), and increased diastolic blood pressure (1.17; 1.01–1.36 per 10 mm Hg increase). Predictors of a reduced risk of ICH were randomization to rivaroxaban (0.60; 0.44–0.82) and history of congestive heart failure (0.65; 0.47–0.89). The ability of the model to discriminate individuals with and without ICH was good (C-index, 0.69; 95% CI, 0.64–0.73).
Conclusions—Among patients with atrial fibrillation treated with anticoagulation, the risk of ICH was higher among Asians, blacks, the elderly, and in those with previous stroke or transient ischemic attack, increased diastolic blood pressure, and reduced platelet count or serum albumin at baseline. The risk of ICH was significantly lower in patients with heart failure and in those who were randomized to rivaroxaban instead of warfarin. The external validity of these findings requires testing in other atrial fibrillation populations.
Most individuals with atrial fibrillation (AF) are at sufficient risk of thromboembolic ischemic stroke to warrant prophylactic oral anticoagulation therapy.1 The most feared complication of anticoagulation is intracranial hemorrhage (ICH) because it is responsible for most of the death and disability attributable to anticoagulant-associated bleeding.2 A burning clinical question is how to predict reliably which patients with AF are at high (and low) risk of ICH if anticoagulated, and which factors reliably discriminate risk of ICH (which may be caused by anticoagulation) from risk of thromboembolic ischemic stroke (which may be prevented by anticoagulation).
All-cause ICH in the general population has been linked to Asian and black ethnicity; the presence of an apolipoprotein E2 or E4 allele; decreased low-density lipoprotein cholesterol and triglycerides; and increasing age, blood pressure, and alcohol consumption.3–6 All-cause ICH in the anticoagulated population occurs at a rate of 0.2% to 1.0% per year7–9 and has likewise been associated not only with increasing age and blood pressure but also with previous ischemic stroke, chronic kidney disease, the early period of anticoagulation use, higher intensity (ie, poorly controlled) anticoagulation, antiplatelet use in addition to anticoagulation, and brain imaging evidence of cerebral leukoaraiosis and microbleeds.9–26 Difficulty arises in clinical practice, because the risk factors for ICH with anticoagulation are also risk factors for ischemic stroke that could be prevented with anticoagulation. A recent study suggests that increasing age and previous stroke are more often associated with ischemic stroke than with ICH, whereas a history of hypertension, diabetes mellitus, renal impairment, and alcohol intake are equally associated.26 In the Rivaroxaban Once Daily, Oral, Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) cohort of 14 264 patients with nonvalvular AF and creatinine clearance ≥30 mL/min who were randomized to rivaroxaban or dose-adjusted warfarin, the factors at randomization that were independently associated with the occurrence of all stroke (ischemic and hemorrhagic) or non–central nervous system embolism among 575 patients (4.0%) over a median follow-up of 1.94 years were reduced creatinine clearance, previous stroke or transient ischemic attack (TIA), elevated diastolic blood pressure and heart rate, as well as vascular disease of the heart and limbs.27 However, the predictors of hemorrhagic and ischemic stroke subtypes in the ROCKET AF cohort have not been reported.
We aimed to determine the rate, outcomes, and independent, significant predictors of ICH in the large, international cohort of 14 264 patients with AF who were enrolled in the ROCKET AF trial and followed-up prospectively for the occurrence of ICH.28,29 We also aimed to determine whether there are any predictors of ICH that are not also predictors of ischemic stroke and thereby may help identify patients for whom anticoagulants may be more hazardous than helpful.
The design, methods, and primary results of the ROCKET AF trial have been described.28,29 Briefly, this was a multinational, randomized, double-blind, double-dummy clinical trial comparing fixed-dose rivaroxaban (20 mg daily; 15 mg daily in patients with creatinine clearance, 30–49 mL/min) with dose-adjusted warfarin (target international normalized ratio, 2.5; range, 2.0–3.0) in participants with nonvalvular AF to prevent all stroke (ischemic or hemorrhagic) or systemic embolism.28,29 The trial protocol was approved by appropriate national regulatory authorities and ethics committees at the participating centers, and all participants provided written informed consent.
Eligible participants had electrocardiographically documented AF and increased risk of stroke as determined by a history of stroke, TIA, or systemic embolism or ≥2 of the following risk factors: heart failure or left ventricular ejection fraction ≤35%, hypertension, age ≥75 years, or diabetes mellitus. Participants were excluded if they had any condition associated with increased bleeding risk.29
Patients were evaluated prospectively at 1, 2, and 4 weeks and monthly thereafter for the duration of the study for study drug management and surveillance for primary end point events. A standardized questionnaire and examination were used to screen for stroke symptoms and potential clinical events during follow-up.
Outcomes and Their Definitions
The primary outcome for this analysis was ICH, which was ascertained by local investigators and reported for central adjudication by an independent clinical events committee. The committee adjudicated all suspected ICHs, masked to baseline characteristics and treatment allocation of all participants, and applied the protocol definition and classification of ICH.
ICH was defined as any primary bleed into the cranial cavity that was clinically overt (ie, caused symptoms or signs) and was confirmed by brain imaging (computed tomography or MRI brain scan) or autopsy. If the hemorrhage was intraparenchymal and caused focal neurological symptoms or signs, it was classified as a hemorrhagic stroke. If the intraparenchymal hemorrhage was secondary hemorrhagic transformation of a focal brain infarct (ie, primary ischemic stroke), it was not considered an ICH.
ICH was categorized as a major bleed and classified according to the site of hemorrhage as any bleed into the brain parenchyma or ventricular system (intracerebral hemorrhage), subarachnoid space (subarachnoid hemorrhage), subdural space (subdural hemorrhage), or extradural space (extradural hemorrhage) in the skull.
ICH was classified as spontaneous or not spontaneous. Intraparenchymal (intracerebral) hemorrhage was classified as traumatic or nontraumatic, but extracerebral (subdural, subarachnoid, and extradural) hemorrhage was not classified as traumatic or nontraumatic. Deaths after ICH were adjudicated as secondary to trauma if trauma clearly precipitated the ICH and death (eg, assault and motor vehicle accident).
Outcome after ICH because of hemorrhagic stroke (ie, intraparenchymal or subarachnoid) was classified according to the modified Rankin Scale score (0–6) and residence (home, rehabilitation center, and long-term care) at 3 months after ICH (and 1 month after ICH if the ICH occurred at the end of the study). The modified Rankin Scale score was not measured if the ICH did not cause a clinical stroke syndrome of sudden onset of focal neurological dysfunction (eg, subdural hematoma and extradural hematoma).
All patients were included in the analysis regardless of study drug exposure (ie, intention-to-treat population). Data were analyzed using SAS version 9.2 (SAS Institute; Cary, NC).
Baseline characteristics were presented separately for participants with ICH, ischemic stroke, stroke of unknown pathological type, and no ICH or stroke. Baseline characteristics were summarized as numbers (percentages) for categorical variables and medians (25th, 75th percentiles) for continuous variables.
Survival free of ICH was calculated, and survival curves were generated by means of the Kaplan–Meier product limit technique.
Multivariable Cox proportional hazards models were developed using stepwise selection of predefined candidate variables that have previously been shown to predict ICH in other studies.9–26 Entry and exit criteria of the stepwise selection was α<0.05. All variables in Table 1 were candidate variables for the models. The models were derived from the intention-to-treat population (ie, all patients randomized), of whom 13 832 patients had complete data for the covariates selected for the final model.
The candidate variables for the primary model for ICH were all variables in Table 1 except for geographical region and medications at baseline, before randomization. A nomogram was created from this model.
Associations are reported as hazards ratios (HRs) with 95% confidence intervals (CIs) and P values. The linearity assumption of Cox proportional hazards regression modeling was tested for continuous variables. When deviations were found, linear splines or variable truncations were used.
To evaluate the possibility that the factors associated with the occurrence of ICH may have differed according to the randomized treatment assignment (dose-adjusted warfarin versus rivaroxaban), we conducted interaction tests across all candidate variables.
The models were validated by 2 methods. One was by means of bootstrapping to obtain the optimism-corrected C-index. The second was summarizing how often each variable was selected in stepwise models fit with 1000 bootstrap samples of the data set. Bootstrap samples of the same size as the original were taken from the original by means of random sampling with replacement. A table showing the number of times each variable was chosen in the 1000 models was produced.
A sensitivity analysis was undertaken by deriving models based on: (1) the population of patients who adhered to their randomized treatment allocation (the safety and on-treatment population); (2) allowing geographical region to enter the model; and (3) including medication recorded at baseline, taken before randomization. We also developed models for secondary outcomes of intracerebral hemorrhage, ischemic stroke, and hemorrhagic stroke.
A total of 14 264 participants were randomized between December 18, 2006, and June 17, 2009. Overall, the median age was 73 years, the median congestive heart failure, hypertension, age >75 years, diabetes mellitus, prior stroke or TIA (CHADS2) score was 3.0, and 52% had a history of previous stroke or TIA.27 The median (25th, 75th) duration of follow-up was 1.94 years (1.42, 2.41) and was 99.8% complete (n=32 [0.2%] lost to follow-up).
Number of ICHs
A total of 172 (1.2%) participants (intracerebral hemorrhage [n=128], subarachnoid hemorrhage [n=5], subdural hemorrhage [n=38], and extradural hemorrhage [n=1]) experienced ≥1 (n=175) ICH events. Hence, 3 of the participants experienced >1 ICH event. The characteristics of all patients according to the occurrence of ICH, ischemic stroke, unknown pathological type of stroke, and no ICH or stroke are shown in Table 1.
Rate of ICH
The average rate of ICH for the duration of follow-up was 0.67% per 100 patient-years. Table I in the online-only Data Supplement shows the rates of ICH in different regions of the world, highest in Asia Pacific (1.21 per 100 patient-years) and lowest in Eastern Europe (0.33 per 100 patient-years). A Kaplan–Meier plot is presented showing the rates by randomized treatment (Figure I in the online-only Data Supplement).
Causes and Treatment of ICH
Trauma caused 9 (7%) intracerebral hemorrhages. Among 135 ICHs for which treatments were reported, medical or surgical intervention was undertaken in 92 (68%) cases, and transfusion of fresh, frozen plasma in 27 (20%) cases.
Outcome of ICH
Among the 172 participants with ICH, 75 (43%) died within 30 days (all attributed to the ICH), 90 were still alive at 30 days, and 7 had <30 days of follow-up. At 90 days, 87 (51%) had died (84 attributed to ICH and 3 to other causes), 70 were alive, and 15 had <90 days of follow-up. Table 2 shows that there was no significant difference in case fatality from ICH among participants assigned warfarin (50%) and rivaroxaban (48%).
Among 90 participants who experienced an ICH because of hemorrhagic stroke, and in whom the modified Rankin Scale score was measured at 3 months after stroke or 1 month after stroke if the stroke occurred at the end of the study, the median time from hemorrhagic stroke to modified Rankin Scale score measurement in surviving patients was 92.5 days (89, 107). A total of 15 (17%) survived free of disability, 13 (14%) were disabled, and 62 (69%) were dead at 3 months after hemorrhagic stroke.
Among the remaining 82 participants with ICHs that were not hemorrhagic stroke, 59 (72%) survived (followed up for a median of 328 [101, 528] days after hemorrhage) and 23 (28%) died (followed up for a median of 5 [2, 18] days after hemorrhage).
Predictors of ICH
Table 3 shows that the significant, independent baseline predictors of an increased risk of ICH were race (Asian HR, 2.02; 95% CI, 1.39–2.94; black HR, 3.25; 95% CI, 1.43–7.41), age (1.35; 1.13–1.63 per 10-year increase), reduced serum albumin (1.39; 1.12–1.73 per 0.5 g/dL decrease), reduced platelet count below 210×109/L (1.08; 1.02–1.13 per 10×109/L decrease), previous stroke or TIA (1.42; 1.02–1.96), and increased diastolic blood pressure (1.17; 1.01–1.36 per 10 mm Hg increase). The predictors of a reduced risk of ICH were randomization to rivaroxaban (0.60; 0.44–0.82) and history of congestive heart failure (CHF; 0.65; 0.47–0.89). The ability of the model to discriminate individuals with and without ICH was good (C-index, 0.69; 95% CI, 0.64–0.73).30,31
The results of interaction tests for all candidate variables are shown in Table II in the online-only Data Supplement. There was no significant interaction between treatment allocation (rivaroxaban or warfarin) and any of the variables listed in Table 1 and, therefore, no evidence that different factors would be selected for the model depending on whether the subject was taking rivaroxaban or warfarin.
Table III in the online-only Data Supplement shows the results of internal validation by means of taking 1000 bootstrap samples from the data and summarizing the percentage of bootstrap samples in which each variable was selected in the 1000 stepwise models. In the case of highly correlated variables, the validation was run, including only 1 of these variables and was repeated with the other. These variables are shown as the contribution in a model that does not include the correlated variable. Interval validation by means of bootstrapping realized the optimism-corrected C-index as 0.669.
Table 4 shows the platelets, albumin, no CHF, warfarin, age, race, diastolic blood pressure, stroke (PANWARDS) nomogram for predicting absolute risk of ICH in this cohort, which is based on the independent, significant prognostic factors for ICH and the strength of their association with risk of ICH. Table 5 and the Figure show the predicted probabilities of ICH at 2.5 years according to the score derived from the variables within the PANWARDS nomogram. There was evidence of good calibration between predicted and observed ICH rates (Figure II in the online-only Data Supplement).
Sensitivity analyses showed that the primary model in the intention-to-treat population (Table 3) was internally consistent in the safety, on-treatment population (Table IV in the online-only Data Supplement), except diastolic blood pressure and history of CHF did not enter.
The multivariate analysis of the effect of geographical region on the risk of ICH revealed that the adjusted HRs for ICH among residents of Asia Pacific (HR, 3.27; 95% CI, 2.06–5.21), Latin America (2.74; 1.64–4.56), North America (2.76; 1.70–4.47), and Western Europe (1.99; 1.16–3.41) were similar. Consequently, these regions were combined (versus Eastern Europe) in a second model (Table V in the online-only Data Supplement). In the second model, with geographical region entered into the model, residence in Eastern Europe (0.37; 0.25–0.55) and reduced creatinine clearance (1.11; 1.04–1.19 per 10 mL/min decrease) emerged as additional significant, independent predictors of ICH, whereas race, age, and history of CHF did not.
A third model, in which baseline use of antithrombotic agents (aspirin, vitamin K antagonism, and thienopyridines) was allowed to enter the model (Table VI in the online-only Data Supplement), showed that the baseline use of a thienopyridine significantly increased the hazard of ICH (HR, 2.57; 95% CI, 1.30–5.07; P=0.006), and previous experience with a vitamin K antagonist was associated with a significantly lower risk of ICH (0.68; 0.50–0.94; P=0.018).
Predictors of Intracerebral Hemorrhage and Hemorrhagic Stroke
The independent, significant predictors of intracerebral hemorrhage (ie, intraparenchymal hemorrhage only [n=128]; excluding subarachnoid, subdural, and extradural hemorrhage) were the same as those for all ICH (Table 3), except for the inclusion of creatinine clearance rather than age (HR, 1.09; 95% CI, 1.01–1.17 per 10 mL/min decrease) and the absence of stroke history in the model (Table VII in the online-only Data Supplement).
The independent, significant predictors of hemorrhagic stroke (ie, intraparenchymal hemorrhage causing focal neurological symptoms or signs [n=90]) were the same as those for all ICH (Table 3), except for the exclusion of previous stroke as a significant, independent predictor of hemorrhagic stroke (Table VIII in the online-only Data Supplement).
Predictors of Ischemic Stroke
Table IX in the online-only Data Supplement shows the independent, significant predictors of ischemic stroke. Three of these 6 factors were also predictors of ICH (ie, previous stroke or TIA, reduced albumin, and increased diastolic blood pressure), whereas 3 were not predictors of ICH (reduced creatinine clearance [HR, 1.14; 95% CI, 1.09–1.19 per 10 mL/min decrease], increasing blood glucose [1.03; 1.01–1.05 per 10 mg/dL increase], and increasing platelet count [1.02; 1.01–1.04 per 10×109/L increase]). Indeed, a decreasing platelet count below 210×109/L was associated with an increased hazard of ICH (Table 3; Figure III in the online-only Data Supplement), and an increasing platelet count above 210×109/L was associated with an increased hazard of ischemic stroke (Table IX and Figure IV in the online-only Data Supplement).
The predictors of a reduced risk of ICH that were not predictors of ischemic stroke were history of CHF (HR, 0.65; 95% CI, 0.47–0.89) and randomization to rivaroxaban (0.60; 0.44–0.82). Predictors of an increased risk of ICH that were not predictors of ischemic stroke were age (1.35; 1.13–1.63 per 10-year increase) and Asian (2.02; 1.39–2.94) or black race (3.25; 1.43–7.41; Table 3).
In an international cohort of 14 264 patients with AF at moderate to high risk of stroke who were treated with anticoagulation, the overall rate of ICH was 0.67% per 100 patient-years, and the overall case fatality rate was 49%. There was no difference in case fatality from ICH among participants assigned warfarin or rivaroxaban. The risk of ICH was significantly higher in Asians, blacks, the elderly, those with a history of stroke or TIA, those with increased diastolic blood pressure, and those with reduced platelet count and serum albumin at baseline. The risk of ICH was significantly lower among those who had a history of heart failure and who were randomized to rivaroxaban instead of warfarin. Internal validation by bootstrapping revealed that race and region were highly correlated, as were diastolic and systolic blood pressure. The discriminative capacity of the model was good (C-index, 0.69; 95% CI, 0.64–0.73).30,31 The PANWARDS nomogram has been derived from the model for predicting the probability of ICH at 2.5 years for any individual patient.
Our Results in Context With Other Studies
The rate and outcomes of ICH observed in ROCKET AF were similar to those observed among anticoagulated participants in large cohorts32,33 and in the Randomized Evaluation of Long-Term Anticoagulant Therapy (RELY) trial.9 The similarly high case fatality rates from ICH among patients taking warfarin or rivaroxaban in ROCKET AF and warfarin or dabigatran in RE-LY are consistent with other studies that report a poor prognosis in anticoagulant-associated ICH.34
Our findings of a higher risk of anticoagulant-associated ICH in Asians, blacks, the elderly, and patients with a history of stroke and elevated blood pressure are consistent with other observational studies and schema for predicting an increased risk of major (intracranial and extracranial) hemorrhage among anticoagulated individuals in other populations, supporting the external validity of our results.9–26,35–37 The more novel findings from this study are the association of declining platelet count and albumin with an increased risk of ICH and the association of a history of heart failure and taking rivaroxaban (instead of warfarin) with a reduced risk of ICH.
Declining platelet count has also been reported as a component of the hepatic or renal disease, ethanol abuse, malignancy, older age, rebleeding, reduced platelet count or function, hypertension, anemia, genetic factors (CYP2C9), excessive fall risk, and stroke (HEMORRHAGES) scheme for predicting all major bleeding, but it was not reported whether reduced platelet count actually added independent, significant predictive power for major bleeding.38 Furthermore, a low platelet count, particularly a low-normal platelet count, has not been reported previously as an independent, significant predictor of ICH.
The higher risk of ICH with declining serum albumin may reflect that both warfarin and rivaroxaban are highly protein bound. The lower risk of ICH in patients with a history of CHF may reflect a hypercoagulable state in heart failure.39
The significantly lower risk of ICH in patients with rivaroxaban when compared with those with warfarin, irrespective of age, is consistent with the lower risk of ICH with dabigatran when compared with warfarin.9 This may reflect the possibility that warfarin compromises a normal hemostatic mechanism in the brain. In the event of injury to a vessel wall in the brain, tissue factor, which is found in high concentrations in the brain, interacts with activated factor VII (VIIa) to initiate coagulation and provide hemostatic protection.40,41 Warfarin blocks vitamin K–dependent γ-carboxylation of coagulation factors II, VII, IX, and X; suppresses the production of factor VIIa; and compromises the formation of tissue factor–VIIa complexes. In contrast, rivaroxaban selectively inhibits factor Xa, and dabigatran inhibits thrombin. Both agents do not compromise the formation of tissue factor–VIIa complexes, which are primary cellular initiators of coagulation. Our study did not have the statistical power to identify or exclude reliably a difference in rates of subdural hemorrhage between participants assigned rivaroxaban and warfarin, which, if real, would invalidate the theory proposed above. Other mechanisms, such as the fact that rivaroxaban does not substantially penetrate the blood–brain barrier, may also be important.42
The finding in our second model of a consistently lower rate of ICH among residents of Eastern Europe, when compared with other parts of the world, most likely reflects ascertainment or diagnostic bias for several reasons. First, the validity of the diagnosis of ICH in Eastern Europe is less robust because the pathological diagnosis of stroke (ischemic versus hemorrhagic) was based on definitive brain imaging less often in Eastern Europe (computed tomography brain scan, 65% and MRI brain scan, 11%) when compared with other regions of the world (computed tomography brain scan range, 77%–84% and MRI brain scan range, 12%–26%). Second, the prevalence of hypertension and mean level of diastolic blood pressure (major causal risk factors for hemorrhagic stroke) were highest among residents of Eastern Europe when compared with other regions of the world. Third, the magnitude of the effect of residence in Eastern Europe on ICH, as the strongest predictor (χ2, 24.3; HR, 0.37; 95% CI, 0.25–0.55), is extraordinary, not previously reported, and unlikely to be plausible. Fourth, there was no significant association between residence in Eastern Europe and risk of ischemic stroke.
One of the challenges in selecting patients with AF for anticoagulant therapy is that the predictors of harm (ie, high risk of ICH) are frequently the same predictors of benefit (ie, high risk of ischemic stroke).26 Our prediction models for ICH and ischemic stroke reinforce this impression to some extent. Previous stroke or TIA, increased diastolic blood pressure, and reduced serum albumin were independent, significant predictors of both ICH and ischemic stroke. However, the independent predictors of an increased risk of ICH that were not predictors of an increased risk of ischemic stroke were race (Asian, black), increased age, and reduced platelet count. The independent predictors of a reduced risk of ICH that were not predictors of an increased risk of ischemic stroke were a history of CHF and randomization to rivaroxaban instead of warfarin. A reduced platelet count below 210×109/L was associated with an increased hazard of ICH, and an elevated platelet count was associated with an increased hazard of ischemic stroke.
The PANWARDS nomogram is derived from the independent, significant prognostic factors for ICH and the strength of their association with risk of ICH. It is designed to enable clinicians to predict the probability of ICH for the next 2.5 years for any individual patient with AF who is anticoagulated. In the ROCKET AF cohort, most patients scored between 20 and 50 on the nomogram, which corresponded to a probability of ICH at 2.5 years ranging from 0.4% (score of 20) to 3.5% (score of 50). The predicted risk of ICH correlated closely with the observed rates of ICH, but the predictive ability of the PANWARDS nomogram awaits external validation in other cohorts of anticoagulated patients with AF.
A strength of our study is that it complies with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting an observational study.43 The study design was prospective and follow-up was prospective, regular, and nearly complete (99.8%), thus optimizing ascertainment of ICH events. ICH was diagnosed by means of standardized diagnostic criteria, including brain imaging and autopsy, and audited by a committee blinded to the study hypothesis and treatment allocation. The number of outcome events was reasonably large (n=175 ICH events in 172 patients), thus enabling ≥17 prognostic variables to be examined reliably in the prognostic model, and the effect of potential confounding by associated variables that were recorded was adjusted for by means of multiple regression analysis.
A limitation of our study is that we were unable to adjust for variables that may influence ICH risk but were not measured at baseline or at the time of ICH, such as the presence or absence of the apolipoprotein E2 or E4 allele,4 CYP2C9 polymorphism,18 cerebral leukoaraiosis,12 cerebral microbleeds,21,22 cerebrovascular pathology such as amyloid angiopathy,21,22 creatinine clearance <30 mL/min,20,25 and international normalized ratio at the time of ICH.10 There is also the possibility of systematic differences in the ascertainment and diagnosis of cases of ICH among different centers and regions. We also did not record specific details of how ICH was treated. Finally, because our model was derived from a large but, nevertheless, selected clinical trial population with specific inclusion criteria (eg, 55% with previous stroke/TIA) and exclusion criteria (eg, creatinine clearance, <30 mL/min), the results may not be generalizable to patient populations dissimilar from the population enrolled in ROCKET AF.
Among 14 264 patients with AF at moderate to high risk of stroke who were treated with anticoagulation, the average annual rate of ICH was 0.67% per 100 patient-years, and the mortality rate from ICH was 49%. The risk of ICH was significantly higher among Asians and blacks, those with a history of stroke or TIA, those with increased age and diastolic blood pressure, and those with decreased platelet count and serum albumin. The risk of ICH was significantly lower among those with a history of CHF and who were randomized to take rivaroxaban instead of warfarin. These data suggest that ICH during anticoagulation may be reduced by lowering blood pressure and using rivaroxaban instead of warfarin. The external validity of these findings requires testing in other AF populations.
Sources of Funding
The trial was supported by research grants from Johnson & Johnson Pharmaceutical Research & Development (Raritan, NJ) and Bayer HealthCare AG (Leverkusen, Germany).
Dr Hankey has received honoraria for serving on executive committees for Johnson & Johnson and Bayer. Dr Piccini has received research grants from ARCA Pharmaceuticals, Janssen, GE Healthcare, and ResMed, and provides consulting to Forest Laboratories, Janssen, Medtronic, and Spectranetics. Dr Mahaffey’s disclosures prior to August 1, 2013, can be found at http://www.dcri.org, and disclosures after August 1, 2013, at http://med.stanford.edu/profiles/kenneth_mahaffey. Dr Halperin has received consulting fees/honoraria and research grant support from AstraZeneca, Bayer AG HealthCare, Boehringer Ingelheim, Daiichi Sankyo, Johnson & Johnson, Pfizer, and Sanofi-Aventis, Biotronik Inc. Dr Patel has received honoraria from Johnson & Johnson and Bayer HealthCare for serving on the executive committee of the Rivaroxaban Once Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) trial; consulting fees from Ortho McNeil Janssen and Bayer HealthCare; and advisory board fees from Genzyme. Dr Breithardt has received honoraria from Johnson & Johnson and Bayer and advisory board fees from Boehringer Ingelheim, Bristol-Myers Squibb, Pfizer, and Sanofi-Aventis. Dr Singer was supported in part by the Eliot B. and Edith C. Shoolman fund of the Massachusetts General Hospital (Boston, MA); has served as a consultant and member of a scientific advisory board for Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi-Sankyo, Johnson & Johnson, and Pfizer; has an institutional research support contract with Johnson & Johnson and Bristol-Myers Squibb; and served as an unpaid ROCKET AF executive committee member. Dr Becker received consulting fees/honoraria and research grant support from Johnson & Johnson, Regado, Boehringer Ingelheim, AstraZeneca, and Daiichi-Sankyo. Dr Berkowitz is an employee of Bayer. Dr Paolini was an employee of Bayer with compensation and stock options provided by the company at the time the work was done. Dr Nessel is employee of Janssen (formerly Johnson & Johnson PRD). Dr Hacke received consulting fees/honoraria and research grant support from Bayer, Johnson & Johnson, and Boehringer Ingelheim. K.A.A. Fox received grant funding and honoraria from Bayer and Johnson & Johnson. Dr Califf's disclosures are available at https://www.dcri.org/about-us/conflict-of-interest/COI-Califf_Jan-Mar2013.pdf. The other authors report no conflicts.
Guest Editor for this article was Kazunori Toyoda, MD.
Presented in part at the International Stroke Conference of the American Heart Association, New Orleans, LA, January 31–February 3, 2012.
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.113.004506/-/DC1.
- Received December 12, 2013.
- Revision received March 10, 2014.
- Accepted March 11, 2014.
- © 2014 American Heart Association, Inc.
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