eFigure 1. Major Bleeding Event Rates per 100 Patient-years by Subgroup
eFigure 2. Stroke or Systemic Embolism Rates per 100 Patient-years by Subgroups
eTable 1. Components of the Full Continuous ORBIT Bleeding Model
eTable 2. Spearman Correlation Between INR Control Measures in Major Bleeding Analysis
eTable 3. Spearman Correlation Between INR Control Measures in Stroke or Systemic Embolism Analysis
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Pokorney SD, Holmes DN, Thomas L, et al. Association Between Warfarin Control Metrics and Atrial Fibrillation Outcomes in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation. JAMA Cardiol. 2019;4(8):756–764. doi:10.1001/jamacardio.2019.1960
Are metrics of international normalized ratio control associated with bleeding and thrombotic events beyond clinical risk scores for patients with atrial fibrillation taking warfarin sodium?
In this cohort study of 51 830 visits among 10 137 patients with atrial fibrillation, historical international normalized ratio variance was associated with future bleeding events, but no historical international normalized ratio metrics were associated with future stroke risk.
The findings suggest that physicians should be cautious when using historical international normalized ratio control measures to assess the likelihood of future bleeding or thrombotic events in patients with atrial fibrillation taking warfarin.
Bleeding and thrombotic events (eg, stroke and systemic embolism) are common in patients with atrial fibrillation (AF) taking warfarin sodium despite a well-established therapeutic range.
To evaluate whether history of therapeutic warfarin control in patients with AF is independently associated with subsequent bleeding or thrombotic events.
Design, Setting, and Participants
In this multicenter cohort study of 176 primary care, cardiology, and electrophysiology clinics in the United States, data were obtained during 51 830 visits among 10 137 patients with AF in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) Registry; 5545 patients treated with warfarin were included in the bleeding analysis, and 5635 patients were included in the thrombotic event analysis. Patient follow-up was performed from June 29, 2010, to November 30, 2014. Data analysis was performed from August 4, 2016, to February 15, 2019.
Multiple measures of warfarin control within the preceding 6 months were analyzed: time in therapeutic range of 2.0 to 3.0, most recent international normalized ratio (INR), percentage of time that a patient had interpolated INR values less than 2.0 or greater than 3.0, INR variance, INR range, and percentage of INR values in therapeutic range.
Main Outcomes and Measures
Association of INR measures, alone or in combination, with clinical factors and risk for thrombotic events and bleeding during the subsequent 6 months was assessed post hoc using logistic regression models.
A total of 5545 patients (mean [SD] age, 74.5 [9.8] years; 3184 [57.4%] male) with AF were included in the major bleeding analysis and 5635 patients (mean [SD] age, 74.5 [9.8] years; 3236 [57.4%] male) in the thrombotic event analysis. During a median follow-up of 1.5 years (interquartile range, 1.0-2.5 years), there were 339 major bleeds (6.1%) and 51 strokes (0.9%). Multiple metrics of warfarin control were individually associated with subsequent bleeding. After adjustment for clinical bleeding risk, 3 measures—time in therapeutic range (per 1-SD increase ≤55: adjusted odds ratio [aOR], 1.16; 95% CI, 1.02-1.32), variation in INR values (aOR, 1.32; 95% CI, 1.19-1.47), and maximum INR (aOR, 1.20; 95% CI, 1.10-1.31)—remained associated with bleeding risk. Adding INR variance to a clinical risk model slightly increased the C statistic from 0.68 to 0.69 and had a net reclassification improvement index of 0.028 (95% CI, −0.029 to 0.067). No INR measures were associated with subsequent stroke risk.
Conclusions and Relevance
Three metrics of prior warfarin control were associated with bleeding risk but only marginally more so than traditional clinical factors. This study did not identify any measures of INR control that were significantly associated with stroke risk.
The recommended treatment for patients with atrial fibrillation (AF) and risk factors for stroke is oral anticoagulation. Vitamin K antagonists (VKAs) remain the most commonly used oral anticoagulant and are associated with a two-thirds reduction in stroke risk.1,2 Studies3-5 have highlighted the importance of maintaining international normalized ratio (INR) measures within a narrow therapeutic range measured by INR with a goal of 2.0 to 3.0 to avoid either thrombotic or bleeding events.
Patients’ risk for future bleeding (hypertension, age, stroke, bleeding tendency or predisposition, labile INRs, elderly age and frailty, drugs such as concomitant aspirin or nonsteroidal anti-inflammatory drugs, or alcohol excess [HAS-BLED score]; Anticoagulation and Risk Factors in Atrial Fibrillation [ATRIA] study; and Outcomes Registry for Better Informed Treatment of Atrial Fibrillation [ORBIT-AF]) and thrombotic events (CHA2DS2-VASc [congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke or transient ischemic attack, vascular disease, age of 65-74 years, and sex category]) have generally been estimated based on clinical factors.6-9 However, among those patients already treated with VKAs, it is unclear whether past INR control data could be used to refine estimates of future stroke and bleeding risk. To date, however, the prognostic importance of past measures of INR control has not been fully characterized.10,11
Our objectives were to use longitudinal data from a large national community-based registry of patients with AF to investigate various measures of the quality of VKA control to determine (1) contemporary metrics for VKA therapeutic control in clinical practice in the United States; (2) the degree that various measures of INR control are associated with one another; and (3) the association of these metrics of INR control with future bleeding and thromboembolic events alone or in combination with other clinical risk factors.
The ORBIT-AF is a US national prospective registry of AF drawn from primary care physicians’, cardiologists’, and electrophysiologists’ outpatient clinical practices.12 Eligible patients are 18 years or older with electrocardiogram-documented AF without a reversible cause regardless of anticoagulation status. Patients were excluded if they had a life expectancy less than 6 months or were not capable of at least 2 years of follow-up. Sites entered data into a web-based case report form at baseline and every 6 months during follow-up. The registry and case report form prospectively collected all INR measurements. The Duke Clinical Research Institute was responsible for study design and data management. All patients provided written informed consent for participation in the registry, but data were not deidentified during the analysis process because the statistician had patient-level health information. The study was approved by the Duke University Institutional Review Board.
There were 10 137 consecutive patients with AF from 176 clinic sites enrolled in ORBIT-AF, accounting for 51 830 patient visits from June 29, 2010, through November 30, 2014. Patients were excluded from this analysis if they did not have follow-up data (388 patients and 388 patient visits). Baseline visits were excluded. Visits were excluded if a patient was not taking warfarin sodium at the time of the visit (15 689 visits) and if there were fewer than 3 INR values in the preceding 180-day period (4791 visits). End-of-study visits or last visits before a patient was unavailable for follow-up were excluded because there was no subsequent follow-up (3628 visits). For the major bleeding analysis, all visits after a major bleeding event were excluded (770 visits), and for the thrombotic event analysis, all visits after a stroke or thromboembolism were excluded (139 visits). The final population for the major bleeding analysis was 5545 patients from 160 sites with 16 815 eligible visits with 180-day follow-up. The final population for the thrombotic event analysis was 5635 patients enrolled at 160 sites with 17 446 eligible visits with 180-day follow-up. Data analysis was performed from August 4, 2016, to February 15, 2019.
The distributions of baseline characteristics were presented for major bleeding and thrombotic events separately. Continuous variables were presented as medians (interquartile range [IQR]) and categorical variables as numbers (percentages). Overall rates per 100 patient-years for International Society on Thrombosis and Haemostasis (ISTH) major bleeding and thrombotic events were presented by various time in therapeutic range (TTR) cut points. Major bleeding events were classified by investigators based on the ISTH definition of major bleeding.13 Thrombotic events were blindly adjudicated by a central committee.
The unit of analysis was the patient visit, occurring approximately every 6 months. At each visit, updated covariate information was obtained and used to estimate outcomes in the following 6 months. At the start of each window, the summary measures of INR history from the prior 6 months were calculated. Outcomes during the 6 months after the visit were modeled by logistic regression and pooled across visits. A categorical variable for the ORBIT-AF study visit was included. A robust, empirical variance accounted for the potential correlation attributable to repeated visits for the same individual.
Multiple INR metrics were calculated on a rolling basis for each patient visit during the 6-month period before any given patient visit. The most recent INR was the last INR value available before the patient visit. The maximum and minimum INR values were the highest and lowest INR values, respectively. The TTR was the percentage of time a patient had interpolated INR values of 2.0 to 3.0 using the method of linear interpolation of Rosendaal et al,14 including interpolation for gaps longer than 8 weeks. The percentage of INR values in range were the number of INR values of 2.0 to 3.0 of the total number of INR values measured. The percentage of time with INR values greater than 3.0 or less than 2.0 used the interpolated INR values to calculate the percentage of time above or below range, respectively. The INR variance was calculated by determining the mean INR, calculating the sum of the squared differences between each INR value and the mean, and dividing that sum by the number of INR samples minus 1. The Spearman correlation calculated the correlation among the various INR metrics by visit.
The unadjusted and adjusted associations between each individual INR summary measure and major bleeding were calculated. The ORBIT-AF bleeding score was used for adjustment in each model.9 The INR metrics that were evaluated for their association with major bleeding included recent INR value and the following metrics based on INR values for the preceding 6 months: percentage of time with INR values greater than 3.0, INR variance, maximum INR value, percentage of INR values of 2.0 to 3.0, and interpolated TTR.
A logistic regression model for the association between INR summary measures and major bleeding was developed. After forcing in the 12 variables from the ORBIT-AF full continuous model (eTable 1 in the Supplement), backward selection with a stay criterion of P < .05 was used to identify measures associated with major bleeding. The model was used to determine the C index, integrated discrimination increment, net reclassification improvement, and calibration plots across deciles. The INR metrics that were included in the development of the bleeding model included the metrics mentioned previously.
All INR summary measures were checked for linearity with the outcomes, and nonlinearity was addressed with linear splines. Missing data on the covariates used in the modeling was handled with single imputation, and imputed values were obtained by Markov chain Monte Carlo or regression methods. Last value carried forward method was used for missing values in follow-up.
A second set of analyses was performed to estimate the chance of having a thromboembolic event during the subsequent 6 months based on the INR history during the prior 6 months using various measures of INR control. Intracranial bleeds occurring on the same day of a thromboembolic event were not counted as a thromboembolic event. The same analysis strategy as described above was used with the following exceptions. The CHA2DS2-VASc score was forced into the model for thromboembolic event.6 The INR metrics that were evaluated for their association with a thromboembolic event included most recent INR value and the following metrics based on INR values for the preceding 6 months: percentage of time with INR values less than 2.0, INR variance, minimum INR value, percentage of INR values of 2.0 to 3.0, and interpolated TTR. Because no INR measure was associated with a thromboembolic event, a model was not developed for thromboembolic events.
All analyses were performed using SAS statistical software, version 9.4 (SAS Institute Inc). All P values were 2-sided, and P < .05 was considered to be statistically significant.
A total of 5545 patients (mean [SD] age, 74.5 [9.8] years; 3184 [57.4%] male) with AF were included in the major bleeding analysis and 5635 patients (mean [SD] age, 74.5 [9.8] years; 3236 [57.4%] male) in the thrombotic event analysis. The patients had a median CHA2DS2-VASc score of 4.0 (range, 3.0-5.0) and a median ORBIT-AF bleeding score of 2.0 (IQR, 1.0-3.0) (Table 1). Patients had been taking warfarin for a median of 4.0 years (IQR, 1.7-7.5) at baseline. Median follow-up in both the bleeding and thrombotic event analyses was 1.5 years (IQR, 1.0-2.5), and the median number of INR checks in any given 6-month period in both cohorts was 7 (IQR, 5-9).
The median interpolated TTR was 68.6% (IQR, 48.5%-87.1%) in the major bleeding cohort and 68.3% (IQR, 48.3%-86.7%) in the thrombotic event cohort. The median percentage of time a patient had interpolated INR values greater than 3.0 was 5.1% (IQR, 0%-22.0%) in the major bleeding cohort and 5.3% (IQR, 0%-22.1%) in the thrombotic event cohort (Table 2). There were correlations (r) between interpolated TTR and percentage of INR values in range (range across visits, 0.86-0.88), INR variance and maximum INR (range, 0.82-0.83), and maximum INR and percent of time greater than 3.0 (range, 0.86-0.87) (eTable 2 in the Supplement). These trends were similar in the thrombotic event cohort (eTable 3 in the Supplement).
There were 339 major bleeds (6.1%), 23 (6.8%) of which were fatal, and 51 strokes (0.9%). Overall rates per 100 patient-years were 4.1 ISTH major bleeding events and 0.6 thrombotic events in this population of patients taking warfarin. Patients with a TTR greater than 75% during a 6-month period had lower rates of major bleeding (3.2 per 100 patient-years) during the subsequent 6-month period compared with patients with a TTR of 75% or less (4.8 per 100 patient-years) (eFigure 1 in the Supplement). Patients taking warfarin had similar rates of thrombotic events during a 6-month period regardless of the TTR during the previous 6 months (eFigure 2 in the Supplement).
In logistic regression models, the ORBIT-AF bleeding score was associated with major bleeding events with an odds ratio (OR) of 1.62 per 1-SD increase (95% CI, 1.47-1.79; P < .001) (Table 3). The clinical risk assessment with the ORBIT-AF bleeding score was more strongly associated with major bleeding events than any INR metric (χ2 = 96). After adjusting for the ORBIT-AF bleeding score, a 6-month measurement of variance was the INR metric that was most strongly associated with major bleeding during the subsequent 6 months with an OR of 1.32 per 0.1-SD increase (95% CI, 1.19-1.47; χ2 = 26; P < .001).
The C statistics for the INR metrics for major bleeding events ranged from 0.53 (95% CI, 0.50-0.56) for the most recent INR value to 0.59 (95% CI, 0.56-0.62) for INR variance (Table 3). After forcing in the variables from the ORBIT-AF full continuous model (eTable 1 in the Supplement) and backward selection, the variance during a 6-month period was the only INR metric that entered the model for estimating major bleeding events during the subsequent 6 months, and the C statistic with INR variance increased from 0.68 (95% CI, 0.66-0.72) to 0.69 (95% CI, 0.67-0.73). The addition of INR variance to the ORBIT-AF bleeding score improved the discrimination (integrated discrimination increment index, 0.0018; 95% CI, 0.0005-0.0038) and the calibration (Figure) of the model. The net reclassification improvement index was 0.028 (95% CI, −0.029 to 0.067) with the addition of INR variance to the ORBIT-AF bleeding full continuous model.
In a multivariate model, the CHA2DS2-VASc score was associated with a thrombotic event with an OR of 1.87 per 1-SD increase (95% CI, 1.42-2.46; P < .001) (Table 4). After adjustment for the clinical stroke risk assessment with the CHA2DS2-VASc score, none of the additional INR metrics were statistically significant; thus, no INR metrics were associated with 6-month thrombotic event after adjustment for clinical risk factors for stroke.
Although the risk of bleeding with high INR values and the risk of thrombotic events with low INR values while taking VKAs have been described for patients with AF, the best metric among multiple possible INR metrics has not been well defined. We found that numerous metrics of INR control and variability were independently associated with bleeding risk. These metrics included INR variance, TTR, and maximum INR. However, these metrics added only modest prognostic information when used alone and only limited incremental value beyond patients’ clinical factors for estimating future bleeding events. No measure of prior warfarin control was associated with subsequent thrombotic events in our data, alone or after adjustment for CHA2DS2-VASc.
The target INR range of 2.0 to 3.0 for stroke prevention in AF was established based on case-control studies of patients taking warfarin, which used the INR value at the time of the ischemic strokes or an intracranial hemorrhage event3-5; this target was also tested in a randomized clinical trial compared with low-intensity warfarin with aspirin.15 The TTR has been associated with outcomes, and retrospective analyses identified TTR values of 65% to 70% as inflection points associated with higher rates of stroke, major bleeding, and death.16-18 Analyses of TTR within the United States have shown individual mean TTRs ranging from 50% to 58%.19-22 The mean TTR in ORBIT-AF was 65% (median, 68%),23 whereas the mean TTR in a highly organized anticoagulation network such as Sweden was 75%.24
The rate of major bleeding among patients taking warfarin in this analysis was 4.1% per 100 patient-years, which was modestly higher than the rate of major bleeding seen in the warfarin arms of the oral anticoagulant trials (range, 3.1%-3.4%).25-28 Patients with a TTR greater than 75% were at lower risk for bleeding than patients with a TTR of 75% or lower, but patients with a TTR greater than 75% still had a 3.2% risk of major bleeds during the subsequent 6 months. The residual bleeding risk in the patients with conditions well controlled with warfarin was likely associated with variability in INR values over time because past INR performance is not highly associated with future INR performance.10,11 Similar challenges in estimating outcomes based on TTR have been seen with the SAMe-TT2R2 (sex, age, medical history, treatment, tobacco use, and race) score (C index, 0.57).29 The SAMe-TT2R2 score was associated with TTR and clinical outcomes, although the C index for major bleeding events in follow-up was 0.58.
The INR variance was the INR metric most strongly associated with major bleeding events, with an unadjusted OR of 1.36 per 1-SD increase (95% CI, 1.23-1.52) and a C statistic of 0.59 (95% CI, 0.56-0.62). Unstable INR variability compared with stable INR variability has previously been found to be independently associated with major bleeding (hazard ratio, 1.57) in data from the Veterans Health Administration.30 The variance analysis from the Veterans Health Administration data also found an independent association with ischemic stroke with a hazard ratio of 1.45 for unstable INR variability (compared with stable INR variability) among 1239 ischemic strokes.30 Similarly, periods of high variability in prothrombin time in patients with mechanical valves have been associated with thromboembolic events.31 Data from Sweden revealed an association between INR variability and major bleeding, stroke or thromboembolism, and death among patients with a TTR less than 70%.18
Clinical risk tools for risk stratification of stroke have been developed, but they have focused on patient characteristics and not on anticoagulation quality variables and have modest risk stratification accuracy.6,32 Similarly, bleeding scores have been developed to estimate the association between warfarin use and risk of major bleeding events, but aside from labile INR values, which are included in the HAS-BLED score, the INR metrics have not been included in these scores.7-9 In this analysis, the clinical risk scores (CHA2DS2-VASc for stroke and ORBIT-AF for bleeding) were more strongly associated with clinical outcomes than any of the INR metrics. The C statistics for the various INR metrics ranged from 0.53 to 0.59, whereas the C statistic for the ORBIT-AF bleeding score was 0.66. None of the INR metrics were associated with 6-month stroke or systemic embolism after adjustment for CHA2DS2-VASc, and only INR variability was included in the backward selection multivariable model for assessing major bleeding events after adjustment for the ORBIT-AF bleeding model. These findings may be attributable to overlap between INR metrics and clinical factors because INR measures may be surrogates for clinical characteristics or clinical characteristics may affect INR measures.
The findings of this analysis do not obviate the need to target the well-established INR goal of 2.0 to 3.0. However, the analysis indicates that it is challenging to identify historical INR metrics that would be associated with future low risk of bleeding events. As such, it is important to consider modifiable patient characteristics, such as antiplatelet use, to reduce major bleeding.
This analysis has several important limitations. The target INR range for patients was not known. The ORBIT-AF investigators may not be representative of all US practitioners. Measurements of INR and warfarin management were at the discretion of the prescribing physician, but ORBIT-AF achieved even better than historical warfarin control because the median number of INR checks in a 6-month period was 7 and the mean TTR was 65%.23 Visits with fewer than 3 INR values in the preceding 180 days were excluded, and it was not known what portion of these were attributable to nonadherence vs temporary interruption, although temporary interruption explained most.33 In addition, we were unable to account for changes in antiplatelet regimens, discontinuation of warfarin use, or transitions to alternative oral anticoagulants between study visits, although 3 INR values during a 6-month period between study visits were required, and data after a study visit at which warfarin use was discontinued were excluded. The INR values at the time of a bleed or stroke were not known, but these data were not needed to assess future events based on historical INR metrics. Finally, there were only 51 thrombotic events in the current ORBIT-AF analysis. Although there was an association between CHA2DS2-VASc and thromboembolism in the current analysis, a larger number of events may be needed if the association between INR variability and stroke is smaller than that of the clinical risk score, as was seen in the bleeding model.
Among patients with AF taking warfarin, clinical risk scores for major bleeding and thrombotic events were more strongly associated with future clinical events than any INR metrics for warfarin control. Past INR variability was associated with future major bleeding events, but no INR metric was associated with subsequent thrombotic events. It was challenging to identify patients taking warfarin who were at low risk of future major bleeding and thrombotic events despite using multiple metrics of high-quality historical INR control.
Accepted for Publication: April 24, 2019.
Published Online: July 3, 2019. doi:10.1001/jamacardio.2019.1960
Open Access: This article is published under the JN-OA license and is free to read on the day of publication.
Corresponding Author: Sean D. Pokorney, MD, MBA, Division of Cardiology, Duke University Medical Center, DUMC 3845, Durham, NC 27710 (email@example.com).
Author Contributions: Drs Pokorney and Peterson had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Pokorney, Thomas, Fonarow, Kowey, Reiffel, Mahaffey, Hylek, Naccarelli, Ezekowitz, Piccini, Peterson.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Pokorney, Naccarelli.
Critical revision of the manuscript for important intellectual content: Pokorney, Holmes, Thomas, Fonarow, Kowey, Reiffel, Singer, Freeman, Gersh, Mahaffey, Hylek, Ezekowitz, Piccini, Peterson.
Statistical analysis: Holmes, Thomas, Kowey.
Obtained funding: Peterson.
Administrative, technical, or material support: Piccini.
Supervision: Thomas, Kowey, Reiffel, Mahaffey, Ezekowitz, Piccini, Peterson.
Conflict of Interest Disclosures: Dr Pokorney reported receiving grants from Janssen Pharmaceuticals and the US Food and Drug Administration; receiving grants and personal fees from Bristol-Myers Squibb, Pfizer, Boston Scientific, and Janssen Pharmaceuticals; and personal fees from Medtronic and Philips. Ms Holmes reported receiving grants from Janssen Scientific. Dr Thomas reported receiving grants from Jansen and BMS. Dr Fonarow reported receiving personal fees from Janssen, Bayer, Medtronic, Abbott, Novartis, and AstraZeneca. Dr Kowey reported receiving personal fees from Johnson & Johnson. Dr Reiffel reported receiving grants from Janssen; receiving personal fees from Janssen, Portola, and Boehringer Ingelheim; and working as an investigator and/or consultant regarding antiarrhythmic control of and diagnostic monitoring for atrial fibrillation. Dr Singer reported receiving personal fees from Johnson & Johnson, Pfizer, and Merck and receiving grants and personal fees from Boehringer Ingelheim and Bristol-Myers Squibb. Dr Freeman reported receiving personal fees from Janssen Pharmaceuticals, Medtronic, Boston Scientific, and Biosense Webster. Dr Gersh reported receiving personal fees from Janssen Scientific Affairs, Boston Scientific, Janssen, BMS, and Sanofi. Dr Mahaffey reported receiving grants and personal fees from Janssen. Dr Hylek reported receiving personal fees from Bayer, Bristol-Myers Squibb/Pfizer, Boehringer Ingelheim, Janssen, Medtronic, and Portola. Dr Naccarelli reported receiving grants from Janssen and receiving personal fees from Janssen, Omeicos, Acesion, Sanofi, Milestone, and GlaxoSmithKline. Dr Ezekowitz reported receiving grants from Pfizer, Boehringer Ingelheim, Bristol-Myers Squibb, and Daiichi Sankyo and receiving personal fees from Boston Scientific. Dr Piccini reported receiving grants from Johnson & Johnson, Boston Scientific, and Abbott. Dr Peterson reported receiving grants and personal fees from Janssen, Amgen, AstraZeneca, Merck & Co, and Sanofi. No other disclosures were reported.
Funding/Support: The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) is sponsored by Janssen Scientific Affairs LLC, Raritan, New Jersey. Janssen Scientific Affairs LLC provided the funding for the registry and this study.
Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Group Information: The ORBIT-AF investigators are as follows: Robert Mendelson, The Jamaica Hospital Medical Center, Jamaica, New York; Ahed Nahhas, Toledo Clinic Incorporated, Toledo, Ohio; Joel Neutel, Orange County Research Center, Tustin, California; Benzy Padanilam, The Care Group, Indianapolis, Indiana; David Pan, Orange County Heart Institute and Research Center, Orange, California; James Poock, Northeast Iowa Family Practice Center, Waterloo, Iowa; Joseph Raffetto, Peninsula Cardiology Associates, Salisbury, Maryland; Richard Greengold, Therapeutic Research Institute of Orange County, Laguna Hills, California; Peter Roan, Mercy Physician Group Cardiology, Nampa, Idaho; Fadi Saba, Professional Health Care of Pinellas Inc, St Petersburg, Florida; Matthew Sackett, Centra Cardiovascular Group, Lynchburg, Virginia; Ricky Schneider, Holy Cross Medical Group, Coral Springs, Florida; Zachary Seymour, AnMed Hospital, Anderson, South Carolina; Jeffrey Shanes, Consultants in Cardiovascular Medicine, Melrose Park, Illinois; James Shoemaker, Ormond Medical Arts Research Center, Ormond Beach, Florida; Victor Simms, Kelsey Research Foundation, Houston, Texas; Nasser Smiley, Northwest Ohio Cardiology Consultants, Toledo, Ohio; David Smith, Tallahassee Research Institute, Tallahassee, Florida; Calvin Snipes, Foothills Internal Medicine, Easley, South Carolina; Rodolfo Sotolongo, Southeast Texas Clinical Research Center, Beaumont, Texas; Cezar Staniloae, Gotham Cardiovascular Research PC, New York, New York; Steven Stoltz, South Texas Institutes of Health, McAllen, Texas; Damodhar P. Suresh, St Elizabeth Physicians, Crestview Hills, Kentucky; Tahir Tak, FSH/Mayo Health System, La Crosse, Wisconsin; Alan Tannenbaum, Primary Care Associates, Ft Myers, Florida; Samir Turk, Trinity Health Organization, Minot, North Dakota; Kishor Vora, Research Integrity, Owensboro, Kentucky; Preet Randhawa, New Jersey Heart, Linden, New Jersey; James Zebrack, Heart Center, Salt Lake City, Utah; Eugene Silva, Rockford Cardiovascular Associates, Rockford, Illinois; Eustace Riley, Piedmont Health Group, Hodges, South Carolina; Debra Weinstein, Atlantic Clinical Research, Boynton Beach, Florida; Tomas Vasiliauskas, Santa Rosa, California; Seth Goldbarg, New York Hospital Queens, Flushing, New York; Daniel Hayward, Southwestern Medical Clinic, Bridgman, Michigan; Chakri Yarlagadda, Ohio Heart Institute, Youngstown, Ohio; Donald Laurion, Nanticoke Cardiology PA, Seaford, Delaware; Abayomi Osunkoya, Profen Research Network at East Carolina Medical Associates, Jacksonville, North Carolina; Randall Burns, Heart Center Research LLC, Huntsville, Alabama; Terrance Castor, Worthington Internal Medicine, Worthington, Ohio; Dennis Spiller, South Florida Research Solutions LLC, Hollywood, Florida; Christopher Luttman, LGLN Cardiology Consultants LLC, Pawtucket, Rhode Island; Salwan Anton, Advanced Cardiovascular Health Specialists, Livonia, Michigan; Joseph McGarvey, Central Bucks Specialists, Doylestown, Pennsylvania; Barry Collins, Advanced Clinical Research, Pell City, Alabama; Roger Guthrie, Arroyo Medical Group Inc, Pismo Beach, California; George Deriso, WellStar Health System, Marietta, Georgia; Roy Flood, Virgin Islands Heart, St Thomas, Virgin Islands; Leslie Fleischer, White-Wilson Medical Center, Fort Walton Beach, Florida; Jeffrey S. Fierstein, Clinlogix Spring House Corporate Center, Spring House, Pennsylvania; Rahul Aggarwal, CVMS Research Institute LLC, Jupiter, Florida; Glenn Jacobs, Cardiology Consultants, Toms River, New Jersey; Nasser Adjei, Sparks Regional Medical Center, Fort Smith, Arkansas; Ayim Akyea-Djamson, Metropolitan Cardiovascular Consultants LLC, Beltsville, Maryland; Anthony Alfieri, Alfieri Cardiology, Newark, Delaware; James Bacon, Mid Ohio Heart Clinic Inc, Mansfield, Ohio; Noel Bedwell, Mobile Heart Specialists PC, Mobile, Alabama; Peter Berger, Geisinger Medical Center, Danville, Pennsylvania; John Berry, Cardiovascular Associates PC, Kingsport, Tennessee; Ravi Bhagwat, Cardiology Associates of Northwest Indiana PC, Hammond, Indiana; Stephen Bloom, Midwest Heart and Vascular, Overland Park, Kansas; Fernando Boccalandro, Permian Research Foundation, Odessa, Texas; James Capo, Executive Health and Research Associates Inc, Atlanta, Georgia; Shaival Kapadia, Cardiovascular Associates of Virginia, Midlothian, Virginia; Rene Casanova, Deerfield Beach Cardiology Research, Oakland Park, Florida; J. E. Morriss III, Southern Clinic PC, Dothan, Alabama; Tom Christensen, Calabash Medical Center, Calabash, North Carolina; John Elsen, Pharmakon Inc, Evergreen Park, Illinois; Ramin Farsad, Diagnamics Inc, Carlsbad, California; Donald Fox, Eastwick Primary Care PC, Philadelphia, Pennsylvania; Brad Frandsen, Sound Medical Research, Port Orchard, Washington; Mark Gelernt, Cardiovascular Associates of the Delaware Valley, Elmer, New Jersey; Santosh Gill, Fox Valley Clinical Research Center LLC, Aurora, Illinois; Stephen Grubb, Tabor City Family Medicine, Tabor City, North Carolina; Christopher Hall, Portage Medical Group, South Bend, Indiana; Hoadley Harris, Odyssey Research/Plains Medical Clinic, Fargo, North Dakota; David Hotchkiss, Charlotte Cardiovascular Institute, Port Charlotte, Florida; John Ip, Thoracic & Cardiovascular Healthcare Foundation, Lansing, Michigan; Naseem Jaffrani, Cambridge Medical Trials, Alexandria, Louisianna; Alan Jones, Northwest Medical Associates PS, Vancouver, Washington; John Kazmierski, Mount Clemens Regional Medical Center, Mount Clemens, Michigan; Frank Waxman, Deerfield Beach Cardiology Associates, Deerfield Beach, Florida; G. L. Kneller, Memorial Medical Group d/b/a LaPorte Medical Group, LaPorte, Indiana; Ajay Labroo, Advanced Cardiovascular Consultants, Rock Island, Illinois; Brian Jaffe, Munson Medical Center, Traverse City, Michigan; Mark Lebenthal, Cardiology Associates of Somerset County PA, Bridgewater, New Jersey; Daniel Lee, Bay Regional Medical Center, Bay City, Michigab; Michael Lillestol, Lillestol Research LLC, Fargo, North Dakota; Kenneth LeClerc, Brooke Army Medical Center Ft Sam Houston, San Antonio, Texas; Paul Maccaro, Huntington Hospital, Huntington, New York; Nolan Mayer, Ventura Cardiology Consultants, Ventura, California; Jay Kozlowski, Cardiology and Vascular Associates at Huron Valley Sinai Hospital, Commerce, Michigan; Sabrina Benjamin, Universal Research Group LLC, Tacoma, Washington; Robert Detweiler, Detweiler Family Medicine and Associates, Lansdale, Pennsylvania; Petar Igic, Meriter Wisconsin Heart, Madison, Wisconsin; Timothy Jackson, Heritage Valley Medical Group Inc, Beaver, Pennsylvania; John Pappas, Cardiology Associates of Corpus Christi, Corpus Christi, Texas; Ronald Littlefield, Palmetto Research Center LLC, Spartanburg, South Carolina; Anthony Frey, Atlantic Cardiology Associates PA, Salisbury, Maryland; Robert Vranian, Virginia Cardiovascular Consultants, Fredericksburg, Virginia; William Long, Barat Research, Charlotte, North Carolina; Paul Grena, Cardiology Consultants of Philadelphia, Yardley, Pennsylvania; Amy Arouni, The Creighton Cardiac Center, Omaha, Nebraska; John Quinn, Winchester Medical Center, Winchester, Virginia; Kevin Browne, Watson Clinic Center for Research Inc, Lakeland, Florida; Steven Forman, Los Alamitos Cardiovascular, Los Alamitos, California; Matthew Ebinger, Genesys Regional Medical Center, Grand Blanc, Michigan; Ronald Blonder, Pikes Peak Cardiology, Colorado Springs, Colorado; Harvey Snyder, Cardiovascular Associates of the Delaware Valley, Haddon Heights, New Jersey; Stan F. Slabic, MD, Internal Medicine and Lipid Management, Erie, Pennsylvania; David Williams, Black Warrior Research, Tuscaloosa, Alabama; Robert Stein, Penobscot Bay Medical Center, Rockport, Maine; Stephen Kirkland, Piedmont Medical Research, Winston-Salem, North Carolina; Kenneth Cohen, New West Physicians, Golden, Colorado; Walter Walthall, Oakwell Clinical Research LLC, San Antonio, Texas; Keith Davis, Pinehurst Medical Clinic, Pinehurst, North Carolina; Brian Snoddy, Birmingham Heart Clinic PC, Birmingham, Alabama; Odilon Alvarado, The Medical Group of Texas, Fort Worth, Texas; Charles R. Leach, MD, Arlington, Texas; Steven Rothman, Lankenau Hospital, Wynnewood, Pennsylvania; Amit Sharma, University of Alabama at Birmingham - Health Center Montgomery, Montgomery, Alabama; Abiodun Olatidoye, Southern Heart Research Institute LLC, Riverdale, Georgia; Soufian AlMahameed, Carilion Clinic, Roanoke, Virginia; Steven Rosenthal, Atlanta Institute for Medical Research Inc, Decatur, Georgia; Gary Sutter, HealthCare Partners Medical Group, Los Angeles, California; William Reiter, Community Hospital of Anaconda, Anaconda, Montana; Troy Thompson, Southwestern Medical Clinic, Stevensville, Michigan; Stephen Thew, Kootenai Heart Clinics LLC, Spokane, Washington; John Kobayashi, Memorial Medical Group / John Kobayashi, South Bend, Indiana; Marcus Williams, The Valley Hospital, Oakland, New Jersey; Jeffrey Kramer, Cardiovascular Associates of the Delaware Valley, Sewell, New Jersey; Shuaib A. Latif, The Reading Hospital and Medical Center, West Reading, Pennsylvania; Benjamin Rhee, Carle Foundation Hospital, Urbana, Illinois; Alexander Adler, Methodist Medical Center of Illinois, Peoria, Illinois; Denis Ruiz-Serrano, Denis Ruiz-Serrano Cardologia, Rio Grande, Puerto Rico; Stanley Stringam, Saltzer Medical Group, Nampa, Idaho; Kenneth Wolok, Tri-County Medical Clinic, Sterling Heights, Michigan; Michael Burnam, Medvin Clinical Research, Tarzana, California; Augusto Focil, Diverse Research Solutions, Oxnard, California; Samuel Butman, Verde Valley Medical Center, Cottonwood, Arizona; Henry Ingersoll, Sharp Rees-Stealy Medical Group, San Diego, California; Richard Borge, Abington Medical Specialists, Abington, Pennsylvania; Youssef Al-Saghir, First Coast Cardiovascular Institute, Orange Park, Florida; Peter Coats, Mobile Diagnostic Center, Mobile, Alabama; Neil Farris, The Research Group of Lexington LLC, Lexington, Kentucky; Kenneth Shore, Medical Clinic of North Texas, Plano, Texas; Michael B. Schwartz, DuPage Medical Group, Winfield, Illinois; Charles Gornick, Minneapolis Heart Institute Foundation, Minneapolis, Minnesota; Paz Eilat, Devise Research, Torrance, California; Edward Quinlan, Southern Maine Medical Center PrimeCare Physicians, Biddeford, Maine; Yogesh Paliwal, Indus Clinical Research Institute, Pomona, California; Raman Mitra, Memorial Medical Group/Raman Mitra, South Bend, Indiana; Stanley Golanty, Pacific Internal Medicine Group, Long Beach, California; Eric Batres, Futura Research, Montebello, California; Ahmad Jingo, RST Data Research Inc, Decatur, Georgia; A. A. Aslam, Northwest Houston Heart Center, Tomball, Texas; Larry Allen, University of Colorado Denver, Aurora, Colorado; Randy Watson, Jean Brown Research, Salt Lake City, Utah; Stephen Voyce, Advanced Cardiology Specialists, Scranton, Pennsylvania; Minang Turakhia, VA Palo Alto Healthcare System, Palo Alto, California; Dina Goytia-Leos, Sonterra Clinical Research, San Antonio, Texas; Mark Lurie, Torrance Memorial Medical Center, Torrance, California; George Mallis, VAMC-Northport, Northport, New York; Brett Atwater, Durham VAMC, Durham, North Carolina; John Strobel, Premier Healthcare LLC, Bloomington, Indiana; John Murray, Meharry Medical College Clinical Research Center, Nashville, Tennessee; Daniel Fisher, Capitol Interventional Cardiology, Carmichael, California; Mahmoud Atieh, Sanford Cardiology, Sanford, North Carolina; Robert Landes, Piqua Family Practice, Piqua, Ohio; Andrew Drabick, Family Medical Associates of Raleigh, Raleigh, North Carolina; Eric Harman, Mountain Region Family Medicine, Kingsport, Tennessee; Brent Ashcraft, Mound Family Practice Associates, Miamisburg, Ohio; Matthew Krista, Prime Care, Dothan, Alabama; Andrea Videlefsky, Urban Family Practice, Marietta, Georgia; Elvin Rivera-Zayas, Ashford Medical Center, San Juan, Puerto Rico; and Alfred E. Tan, West Coast Research LLC, San Ramon, California.
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