Peterson, Eric D.

Background Dabigatran is a novel oral anticoagulant approved for thromboprophylaxis in atrial fibrillation. Adoption patterns of this new agent in community practice are unknown. Methods and Results We studied patterns of dabigatran use among patients enrolled in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT‐AF) Registry between June 2010 and August 2011 and followed for 12 months. Among 9974 atrial fibrillation patients included, 1217 (12%) were treated with dabigatran during the study. Overall, patients receiving dabigatran were younger (median age 72 versus 75 years, P <0.0001), more likely to be white (92% versus 89%, P =0.005), more likely to have private insurance (33% versus 25%, P <0.0001), and less likely to have prior cardiovascular disease (4% versus 33%, P <0.0001). They had more new‐onset atrial fibrillation (8.8% versus 4.1%, P <0.0001), lower CHADS 2 scores (estimated risk based on the presence of congestive heart failure, hypertension, aged ≥75 years, diabetes mellitus, and prior stroke or transient ischemic attack; mean 2.0 versus 2.3, P <0.0001), and lower Anticoagulation and Risk Factors in Atrial Fibrillation scores (mean 2.4 versus 2.8, P <0.0001). More than half (n=14/25, 56%) of patients with severe kidney disease were not prescribed reduced dosing, whereas 10% (n=91/920) with preserved renal function received lower dosing. Among patients not on dabigatran at baseline, 8% had dabigatran initiated during follow‐up. Patient education was significantly associated with switching from warfarin to dabigatran (adjusted odds ratio for postgraduate 1.73, P =0.007), whereas antiarrhythmic drug use significantly correlated with de novo adoption of dabigatran (adjusted odds ratio 2.4, P <0.0001). Conclusions Patients receiving dabigatran were younger and at a lower risk of stroke and bleeding. Patients appeared to drive switching from warfarin, whereas clinical characteristics influenced de novo start of dabigatran. These data suggest cautious early uptake of dabigatran, and more careful attention to dosing adjustments is warranted. Clinical Trial Registration URL : Clinicaltrials.gov. Unique identifier: NCT 01165710.

Background The prevalence of atrial fibrillation ( AF ) continues to increase; however, there are limited data describing the division of care among practitioners in the community and whether care differs depending on provider specialty. Methods and Results Using the Outcomes Registry for Better Informed Treatment of AF ( ORBIT ‐ AF ) Registry, we described patient characteristics and AF management strategies in ambulatory clinic practice settings, including electrophysiology ( EP ), general cardiology, and primary care. A total of 10 097 patients were included; of these, 1544 (15.3%) were cared for by an EP provider, 6584 (65.2%) by a cardiology provider, and 1969 (19.5%) by an internal medicine/primary care provider. Compared with those patients who were cared for by cardiologists or internal medicine/primary care providers, patients cared for by EP providers were younger (median age, 73 years [interquartile range, IQR , 64, 80 years, Q1, Q3] versus 75 years [ IQR , 67, 82 years] for cardiology and versus 76 years [ IQR , 68, 82 years] for primary care). Compared with cardiology and internal medicine/primary care providers, EP providers used rhythm control (versus rate control) management more often (44.2% versus 29.7% and 28.8%, respectively, P <0.0001; adjusted odds ratio [ OR ] EP versus cardiology, 1.66 [95% confidence interval, CI , 1.05 to 2.61]; adjusted OR for internal medicine/primary care versus cardiology, 0.91 [95% CI , 0.65 to 1.26]). Use of oral anticoagulant therapy was high across all providers, although it was higher for cardiology and EP providers (overall, 76.1%; P =0.02 for difference between groups). Conclusions Our data demonstrate important differences between provider specialties, the demographics of the AF patient population treated, and treatment strategies—particularly for rhythm control and anticoagulation therapy.

Background— Patients with atrial fibrillation (AF) at the highest stroke risk derive the largest benefit from oral anticoagulation (OAC). Those with the highest stroke risk have been paradoxically less likely to receive OAC. This study assessed the association between stroke and bleeding risk on rates of OAC. Methods and Results— We analyzed OAC use among 10 098 patients with AF from 174 community-based outpatient practices enrolled in 2010–2011 in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF). OAC was defined as warfarin or dabigatran use at study enrollment. Stroke and bleeding risk were calculated using congestive heart failure, hypertension, age, diabetes mellitus, prior stroke (CHADS 2 ), and anticoagulation and risk factors in AF (ATRIA) scores, respectively. The mean subject age was 73 years; 58% were men. Overall, 76% of patients received OAC (71% warfarin and 5% dabigatran). The use of OAC increased among those with higher CHADS 2 scores, from 53% for CHADS 2 =0 to 80% for CHADS 2 ≥2 ( P <0.001). OAC use fell slightly with increasing ATRIA bleeding risk score, from 81% for ATRIA=3 to 73% for ATRIA≥5 ( P <0.001). A significant interaction existed between ATRIA and CHADS 2 scores ( P =0.021). Among those with low bleeding risk, use of OAC increased significantly with increasing stroke risk. Among those with high bleeding risk, CHADS 2 stroke risk had a smaller impact on use of OAC. Conclusions— In community-based outpatients with AF, use of OAC was high and driven by not only predominantly stroke but also bleeding risk. Stroke risk significantly affects OAC use among those with low bleeding risk, whereas those with high bleeding risk demonstrate consistently lower use of OAC regardless of stroke risk.

Background— Prior studies have demonstrated low use of implantable cardioverter defibrillators (ICDs) as primary prevention, particularly among women and blacks. The degree to which the overall use of ICD therapy and disparities in use have changed is unclear. Methods and Results— We examined 11 880 unique patients with a history of heart failure and left ventricular ejection fraction ≤35% who were ≥65 years old and enrolled in the Get With the Guidelines–Heart Failure (GWTG-HF) program from January 2005 through December 2009. We determined the rate of ICD use by year for the overall population and for sex and race groups. From 2005 to 2007, overall ICD use increased from 30.2% to 42.4% and then remained unchanged in 2008 to 2009. After adjustment for potential confounders, ICD use increased significantly in the overall study population during 2005 to 2007 (odds ratio, 1.28; 95% confidence interval, 1.11–1.48 per year; P =0.0008) and in black women (odds ratio, 1.82; 95% confidence interval, 1.28–2.58 per year; P =0.0008), white women (odds ratio, 1.30; 95% confidence interval, 1.06–1.59 per year; P =0.010), black men (odds ratio, 1.54; 95% confidence interval, 1.19–1.99 per year; P =0.0009), and white men (odds ratio, 1.25; 95% confidence interval, 1.06–1.48 per year; P =0.0072). The increase in ICD use was greatest among blacks. Conclusions— In the GWTG-HF quality improvement program, a significant increase in ICD therapy use was observed over time in all sex and race groups. The previously described racial disparities in ICD use were no longer present by the end of the study period; however, sex differences persisted.

Background— We sought to validate the recently developed Mayo Clinic Risk Score model for in-hospital mortality after percutaneous coronary intervention using an independent data set. The Mayo Clinic Risk Score has 7 simple clinical and noninvasive variables, available before coronary angiography, for prediction of in-hospital mortality. External validation using an independent data set would support broader applicability of the model. Methods and Results— In-hospital mortality after percutaneous coronary intervention on 309 351 patients from the National Cardiovascular Data Registry admitted from January 1, 2004, to March, 30, 2006, was studied. Using the Mayo Clinic Risk Score equation, we assigned predicted probabilities of death to each patient. The area under the receiver-operating characteristics curve was 0.884, indicating excellent discrimination overall as well as among subgroups, including gender, diabetes mellitus, renal failure, low ejection fraction, different age groups, and multivessel disease. Ninety-seven percent of patients undergoing percutaneous coronary intervention had a Mayo Clinic Risk Score <10, indicating low to intermediate risk. The Mayo Clinic Risk Score model initially slightly underpredicted event rates when applied in National Cardiovascular Data Registry data (observed 1.23% versus predicted 1.10%), but this underprediction was corrected after recalibration. The recalibrated risk score discriminated (c index=0.885) and calibrated well in an National Cardiovascular Data Registry validation data set consisting of procedures performed between April 1, 2006, and March 30, 2007. Conclusions— Seven variables can be combined into a convenient risk scoring system before coronary angiography is performed to predict in-hospital mortality after percutaneous coronary intervention. This model may be useful for providing patients with individualized, evidence-based estimates of procedural risk as part of the informed consent process before percutaneous coronary intervention.

The American Heart Association’s (AHA’s) mission is “to build healthier lives, free of cardiovascular diseases and stroke.” This first article in a 2-part series will serve to present an overview of the work the AHA has undertaken to translate evidence into practice for healthcare professionals. It describes the extensive work of the AHA to support and further the delivery of evidence-based medicine, which includes the following: (1) supporting scientific discovery and the next generation of healthcare professionals and researchers; (2) disseminating scientific information; (3) developing evidence-based guidelines and statements; (4) creating and advocating for the implementation of performance indicators/measures; (5) developing clinical decision support and quality improvement tools; and (6) developing directed-cause campaigns, all of which can lead to improved patient care. This article also discusses the need for novel approaches and some of the AHA’s evolving strategies to help address gaps in care. The second article, which will be published shortly after this one, will examine the AHA’s efforts to engage and empower healthcare consumers to become more involved with their own health and health care.

Background— Prior studies have demonstrated an inconsistent association between patients’ arrival time for acute myocardial infarction (AMI) and their subsequent medical care and outcomes. Methods and Results— Using a contemporary national clinical registry, we examined differences in medical care and in-hospital mortality among AMI patients admitted during regular hours (weekdays 7 am to 7 pm ) versus off-hours (weekends, holidays, and 7 pm to 7 am weeknights). The study cohort included 62 814 AMI patients from the Get With the Guidelines–Coronary Artery Disease database admitted to 379 hospitals throughout the United States from July 2000 through September 2005. Overall, 33 982 (54.1%) patients arrived during off-hours. Compared with those arriving during regular hours, eligible off-hour patients were slightly less likely to receive primary percutaneous coronary intervention (adjusted odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89 to 0.98), had longer door-to-balloon times (median, 110 versus 85 minutes; P <0.0001), and were less likely to achieve door-to-balloon ≤90 minutes (adjusted OR, 0.34; 95% CI, 0.29 to 0.39). Arrival during off-hours was associated with slightly lower overall revascularization rates (adjusted OR, 0.94; 95% CI, 0.90 to 0.97). No measurable differences, however, were found in in-hospital mortality between regular hours and off-hours in the overall AMI, ST-elevated MI, and non–ST-elevated MI cohorts (adjusted OR, 0.99; 95% CI, 0.93 to 1.06; adjusted OR, 1.05; 95% CI, 0.94 to 1.18; and adjusted OR, 0.97; 95% CI, 0.90 to 1.04, respectively). Similar observations were made across most age and sex subgroups and with an alternative definition for arrival time (weekends/holidays versus weekdays). Conclusions— Despite slightly fewer primary percutaneous coronary interventions and overall revascularizations and significantly longer door-to-balloon times, patients presenting with AMI during off-hours had in-hospital mortality similar to those presenting during regular hours.

Background— Current risk models predict in-hospital mortality after either coronary artery bypass graft surgery or percutaneous coronary interventions separately, yet the overlap suggests that the same variables can define the risks of alternative coronary reperfusion therapies. Our goal was to seek a preprocedure risk model that can predict in-hospital mortality after either percutaneous coronary intervention or coronary artery bypass graft surgery. Methods and Results— We tested the ability of the recently validated, integer-based Mayo Clinic Risk Score (MCRS) for percutaneous coronary intervention, which is based solely on preprocedure variables (age, creatinine, ejection fraction, myocardial infarction ≤24 hours, shock, congestive heart failure, and peripheral vascular disease), to predict in-hospital mortality among 370 793 patients in the Society of Thoracic Surgeons database undergoing isolated coronary artery bypass graft surgery from 2004 to 2006. For the Society of Thoracic Surgeons coronary artery bypass graft surgery population studied, the median age was 66 years (quartiles 1 to 3, 57 to 74 years), with 37.2% of patients ≥70 years old. A high prevalence of comorbid conditions, including diabetes mellitus (37.1%), hypertension (80.5%), peripheral vascular disease (15.3%), and renal disease (creatinine ≥1.4 mg/dL; 11.8%), was present. A strong association existed between the MCRS and the observed mortality in the Society of Thoracic Surgeons database. The in-hospital mortality ranged between 0.3% (95% confidence interval 0.3% to 0.4%) with a score of 0 on the MCRS and 33.8% (95% confidence interval 27.3% to 40.3%) with an MCRS score of 20 to 24. The discriminatory ability of the MCRS was moderate, as measured by the area under the receiver operating characteristic curve (C-statistic=0.715 to 0.784 among various subgroups); performance was inferior to the Society of Thoracic Surgeons model for most categories tested. Conclusions— This model, which is based on 7 preprocedure risk variables, may be useful for providing patients with individualized, evidence-based estimates of procedural risk as part of the informed consent process before percutaneous or surgical revascularization.