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      Estimated prevalence of undiagnosed atrial fibrillation in the United States

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          Abstract

          Introduction

          As atrial fibrillation (AF) is often asymptomatic, it may remain undiagnosed until or even after development of complications, such as stroke. Consequently the observed prevalence of AF may underestimate total disease burden.

          Methods

          To estimate the prevalence of undiagnosed AF in the United States, we performed a retrospective cohort modeling study in working age (18–64) and elderly (≥65) people using commercial and Medicare administrative claims databases. We identified patients in years 2004–2010 with incident AF following an ischemic stroke. Using a back-calculation methodology, we estimated the prevalence of undiagnosed AF as the ratio of the number of post-stroke AF patients and the CHADS 2-specific stroke probability for each patient, adjusting for age and gender composition based on United States census data.

          Results

          The estimated prevalence of AF (diagnosed and undiagnosed) was 3,873,900 (95%CI: 3,675,200–4,702,600) elderly and 1,457,100 (95%CI: 1,218,500–1,695,800) working age adults, representing 10.0% and 0.92% of the respective populations. Of these, 698,900 were undiagnosed: 535,400 (95%CI: 331,900–804,400) elderly and 163,500 (95%CI: 17,700–400,000) working age adults, representing 1.3% and 0.09% of the respective populations. Among all undiagnosed cases, 77% had a CHADS 2 score ≥1, and 56% had CHADS 2 score ≥2.

          Conclusions

          Using a back-calculation approach, we estimate that the total AF prevalence in 2009 was 5.3 million of which 0.7 million (13.1% of AF cases) were undiagnosed. Over half of the modeled population with undiagnosed AF was at moderate to high risk of stroke.

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          Most cited references22

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          Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study.

          Atrial fibrillation is the most common arrhythmia in elderly persons and a potent risk factor for stroke. However, recent prevalence and projected future numbers of persons with atrial fibrillation are not well described. To estimate prevalence of atrial fibrillation and US national projections of the numbers of persons with atrial fibrillation through the year 2050. Cross-sectional study of adults aged 20 years or older who were enrolled in a large health maintenance organization in California and who had atrial fibrillation diagnosed between July 1, 1996, and December 31, 1997. Prevalence of atrial fibrillation in the study population of 1.89 million; projected number of persons in the United States with atrial fibrillation between 1995-2050. A total of 17 974 adults with diagnosed atrial fibrillation were identified during the study period; 45% were aged 75 years or older. The prevalence of atrial fibrillation was 0.95% (95% confidence interval, 0.94%-0.96%). Atrial fibrillation was more common in men than in women (1.1% vs 0.8%; P<.001). Prevalence increased from 0.1% among adults younger than 55 years to 9.0% in persons aged 80 years or older. Among persons aged 50 years or older, prevalence of atrial fibrillation was higher in whites than in blacks (2.2% vs 1.5%; P<.001). We estimate approximately 2.3 million US adults currently have atrial fibrillation. We project that this will increase to more than 5.6 million (lower bound, 5.0; upper bound, 6.3) by the year 2050, with more than 50% of affected individuals aged 80 years or older. Our study confirms that atrial fibrillation is common among older adults and provides a contemporary basis for estimates of prevalence in the United States. The number of patients with atrial fibrillation is likely to increase 2.5-fold during the next 50 years, reflecting the growing proportion of elderly individuals. Coordinated efforts are needed to face the increasing challenge of optimal stroke prevention and rhythm management in patients with atrial fibrillation.
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            Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence.

            Limited data exist on trends in incidence of atrial fibrillation (AF). We assessed the community-based trends in AF incidence for 1980 to 2000 and provided prevalence projections to 2050. The adult residents of Olmsted County, Minnesota, who had ECG-confirmed first AF in the period 1980 to 2000 (n=4618) were identified. Trends in age-adjusted incidence were determined and used to construct model-based prevalence estimates. The age- and sex-adjusted incidence of AF per 1000 person-years was 3.04 (95% CI, 2.78 to 3.31) in 1980 and 3.68 (95% CI, 3.42 to 3.95) in 2000. According to Poisson regression with adjustment for age and sex, incidence of AF increased significantly (P=0.014), with a relative increase of 12.6% (95% CI, 2.1 to 23.1) over 21 years. The increase in age-adjusted AF incidence did not differ between men and women (P=0.84). According to the US population projections by the US Census Bureau, the number of persons with AF is projected to be 12.1 million by 2050, assuming no further increase in age-adjusted incidence of AF, but 15.9 million if the increase in incidence continues. The age-adjusted incidence of AF increased significantly in Olmsted County during 1980 to 2000. Whether or not this rate of increase continues, the projected number of persons with AF for the United States will exceed 10 million by 2050, underscoring the urgent need for primary prevention strategies against AF development.
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              Increasing prevalence of atrial fibrillation and flutter in the United States.

              The prevalence data for atrial fibrillation (AF) are dated. The present retrospective study estimated the current and projected prevalence of AF and atrial flutter (AFL) in the United States using a large national database. Claims data drawn from July 2004 to December 2005 from the MarketScan research databases from Thomson Reuters were used to identify patients aged >or=20 years with nontransient AF and/or AFL and age- and gender-matched controls without these conditions. Of the 21,648,681 patients in the databases, 242,903 (1.12%) had nontransient AF and/or AFL (222,605 AF only, 5,376 AFL only, and 14,922 AF and AFL). Patients with AF only, AFL only, and AF and AFL had a greater (p <0.001) prevalence of co-morbidities, including hypertension (62.0%, 61.3%, and 57.0%, respectively) and coronary artery disease (43.0%, 44.7%, and 44.5%, respectively), than matched controls (45.1% hypertension and 19.4% coronary artery disease). Applying the US Census Bureau population estimates to the prevalence rates for AF and/or AFL in the databases, it was estimated that 3.03 million persons in the United States had AF only, 0.07 million had AFL only, and 0.19 million had AF and AFL in 2005. The projected prevalence for 2050 was 7.56 million for AF only, 0.15 million for AFL only, and 0.44 million for AF and AFL. In conclusion, the current prevalence of AF and AFL is high and is projected to increase considerably by 2050. The current and projected increases in the prevalence of AF are greater than predicted by a previous sentinel study and might reflect more than the aging of the population.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Funding acquisitionRole: ResourcesRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Funding acquisitionRole: ResourcesRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: ResourcesRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 April 2018
                2018
                : 13
                : 4
                : e0195088
                Affiliations
                [1 ] Stanford University School of Medicine, Stanford, California, United States of America
                [2 ] Precision Health Economics, Los Angeles, California, United States of America
                [3 ] Pfizer Inc., New York, New York, United States of America
                [4 ] Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, California, United States of America
                University of Palermo, ITALY
                Author notes

                Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: Dr. Shafrin had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. In accordance with ICMJE guidelines, all authors have read and approved the final manuscript being submitted. The study was funded by Bristol-Myers Squibb and Pfizer based on a proposal that co-author Dana P. Goldman and Mintu P. Turakhia presented to the sponsors. Jason Shafrin and Katalin Bognar are employees of; Dana P. Goldman serves as a consultant to Precision Health Economics, who were paid consultants to Pfizer in connection with the development of this manuscript. Jeffrey Trocio, Younos Abdulsattar, and Daniel Wiederkehr are employees and shareholders of Pfizer, Inc. Bristol-Myers Squibb provided funding but was not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Through Pfizer-affiliated coauthors, Pfizer was involved in the design of the study, the interpretation of data, and the preparation, review, and approval of the manuscript for publication. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Article
                PONE-D-17-36475
                10.1371/journal.pone.0195088
                5896911
                29649277
                1fa20a79-293d-4860-b588-101f64d980c9
                © 2018 Turakhia et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 October 2017
                : 18 March 2018
                Page count
                Figures: 3, Tables: 3, Pages: 11
                Funding
                Funded by: Pfizer (US)
                Funded by: Bristol-Myers Squibb (US)
                The research reported in this manuscript was funded by Bristol-Myers Squibb and Pfizer based on a proposal that co-author Dana P. Goldman and Mintu P. Turakhia presented to the sponsors. Jason Shafrin and Katalin Bognar are employees of; Dana P. Goldman serves as a consultant to Precision Health Economics, who were paid consultants to Pfizer in connection with the development of this manuscript. Jeffrey Trocio, Younos Abdulsattar, and Daniel Wiederkehr are employees and shareholders of Pfizer, Inc. Bristol-Myers Squibb provided funding but was not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Through Pfizer-affiliated coauthors, Pfizer was involved in the design of the study, the interpretation of data, and the preparation, review, and approval of the manuscript for publication.
                Categories
                Research Article
                Medicine and Health Sciences
                Cardiology
                Arrhythmia
                Atrial Fibrillation
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Ischemic Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Ischemic Stroke
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Hemorrhagic Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Hemorrhagic Stroke
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Medicine and Health Sciences
                Geriatrics
                Social Sciences
                Political Science
                Public Policy
                Medicare
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Hypertension
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Custom metadata
                The authors have posted all underlying program code at the Open Science Framework website located: https://osf.io/ufgdc/. The underlying data used in the analysis come from two sources: Optum and the Centers for Medicare & Medicaid Services. Our data use agreements with Optum and CMS have legally enforceable usability restrictions that preclude our making the data available publicly. However, researchers can access the Medicare Limited Data Sets (the data used in our analysis) from CMS. As stated on the ResDAC website ( https://www.resdac.org/cms-data/request/limited-data-sets), “LDS requests do not require a ResDAC review and can be submitted directly to CMS by the researcher." The DUA-Limited Data Sets (LDS) page on the CMS website ( https://www.cms.gov/Research-Statistics-Data-and-Systems/Files-for-Order/Data-Disclosures-Data-Agreements/DUA_-_NewLDS.html) describes the process for requesting LDS files. Researchers can contact Optum about accessing the Touchstone data by visiting their website: https://www.optum.com/solutions/prod-nav/claims-data.html.

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