The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Typical, atypical, and asymptomatic presentations of new-onset atrial fibrillation in the community: Characteristics and prognostic implications
Open accessAbstract
Background The prognostic significance of the clinical presentation of atrial fibrillation (AF) is poorly defined. Objective We aimed to determine the frequency, associations, and prognostic impact of different clinical presentations of new-onset AF. Methods One thousand patients with incident AF in Olmsted County, MN, were randomly selected (2000-2010). Patients with AF that was complicated at presentation [heart failure (n=71), thromboembolism (n=24)], provoked (n=346), or unable to determine symptoms (n=83) were excluded. In the remaining patients, characteristics and prognosis associated with different types of symptoms were examined. Results Among 476 patients, 193 had typical (palpitations), 122 had atypical (other non-palpitation symptoms), and 161 had asymptomatic AF presentation. Patients with typical presentation had lower CHA2DS2-VASc scores (mean 2.3±2) compared to atypical and asymptomatic presentation (mean 3.2±1.8 and 3.3±1.9, respectively; p<0.001). Fifty-nine cerebrovascular events (CVE) and 149 deaths (n=49 cardiovascular) were documented over median 5.6 and 6.0 years, respectively. Atypical and asymptomatic AF conferred higher risks of CVE compared to typical AF after adjustment for CHA2DS2-VASc score and age (hazard ratio (HR) 3.51, 95% confidence interval (CI) 1.65-7.48 and HR 2.70, 95% CI 1.29-5.66, respectively), and associations remained statistically significant after further adjustments including comorbidities and warfarin use. Asymptomatic AF was associated with an increased risk of cardiovascular (HR 3.12, 95% CI 1.50-6.45) and all-cause mortality (HR 2.96, 95% CI 1.89-4.64) compared to typical AF after adjustment for CHA2DS2-VASc score and age. Conclusion The type of clinical presentation may have important implications for the prognosis of new-onset AF in the community.
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Heart Disease and Stroke Statistics—2012 Update: A Report From the American Heart Association
Writing Group Members, Roger, V. L., Go, A. S., Lloyd-Jones, D. M., Benjamin, E. J., Berry, J. D., Borden, W. B., Bravata, D. M., Dai, S., Ford, E. S., et al. (2012) · Circulation · doi:10.1161/cir.0b013e31823ac046 · Cited by 7,333
Self-citationSubclinical atrial fibrillation and the risk of stroke
Healey, J. S., Connolly, S. J., Gold, M. R., Israel, C. W., Van Gelder, I. C., Capucci, A., Lau, C. P., Fain, E., Yang, S., Bailleul, C., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1105575 · Cited by 2,100
Mass Screening for Untreated Atrial Fibrillation: The STROKESTOP Study
Svennberg, E., Engdahl, J., Al-Khalili, F., Friberg, L., Frykman, V., & Rosenqvist, M. (2015) · Circulation · doi:10.1161/circulationaha.114.014343 · Cited by 605
Flaker, G. C., Belew, K., Beckman, K., Vidaillet, H., Kron, J., Safford, R., Mickel, M., & Barrell, P. (2005) · American Heart Journal · doi:10.1016/j.ahj.2004.06.032 · Cited by 341
Xiong, Q., Proietti, M., Senoo, K., & Lip, G. Y. H. (2015) · International Journal of Cardiology · doi:10.1016/j.ijcard.2015.05.011 · Cited by 161
Cited by
Calkins, H., Hindricks, G., Cappato, R., Kim, Y.-H., Saad, E. B., Aguinaga, L., Akar, J. G., Badhwar, V., Brugada, J., Camm, J., et al. (2017) · Heart Rhythm · doi:10.1016/j.hrthm.2017.05.012 · Cited by 2,755
Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
Siontis, K. C., Noseworthy, P. A., Attia, Z. I., & Friedman, P. A. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-020-00503-2 · Cited by 914
Self-citationHalcox, J. P. J., Wareham, K., Cardew, A., Gilmore, M., Barry, J. P., Phillips, C., & Gravenor, M. B. (2017) · Circulation · doi:10.1161/circulationaha.117.030583 · Cited by 580
Atrial Fibrillation and Hypertension
Dzeshka, M. S., Shantsila, A., Shantsila, E., & Lip, G. Y. H. (2017) · Hypertension · doi:10.1161/hypertensionaha.117.08934 · Cited by 148
How will machine learning inform the clinical care of atrial fibrillation?
Siontis, K. C., Yao, X., Pirruccello, J. P., Philippakis, A. A., & Noseworthy, P. A. (2020) · Circulation Research · doi:10.1161/circresaha.120.316401 · Cited by 61
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Metadata
- Authors
- Siontis, K. C., Gersh, B. J., Killian, J. M., Noseworthy, P. A., McCabe, P., Weston, S. A., Roger, V. L., & Chamberlain, A. M.
- Venue
- Heart Rhythm
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 13
- Issue
- 7
- Pages
- 1418-1424
- ISSN
- 1547-5271 (ISSN-L)
- OpenAlex
- W2289502982
- Cited by
- 178
- References
- 5
- FWCI
- 11.70
- Type
- journal article
- Language
- en
- Open access
- green
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- Siontis, K. C., Gersh, B. J., Killian, J. M., Noseworthy, P. A., McCabe, P., Weston, S. A., Roger, V. L., & Chamberlain, A. M. (2016). Typical, atypical, and asymptomatic presentations of new-onset atrial fibrillation in the community: Characteristics and prognostic implications. Heart Rhythm. https://doi.org/10.1016/j.hrthm.2016.03.003
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