A clinical risk score for atrial fibrillation in a biracial prospective cohort (from the Atherosclerosis Risk in Communities [ARIC] study)
Open accessAbstract
A risk score for atrial fibrillation (AF) has been developed by the Framingham Heart Study; however, the applicability of this risk score, derived using data from white patients, to predict new-onset AF in nonwhites is uncertain. Therefore, we developed a 10-year risk score for new-onset AF from risk factors commonly measured in clinical practice using 14,546 subjects from the Atherosclerosis Risk In Communities (ARIC) study, a prospective community-based cohort of blacks and whites in the United States. During 10 years of follow-up, 515 incident AF events occurred. The following variables were included in the AF risk score: age, race, height, smoking status, systolic blood pressure, hypertension medication use, precordial murmur, left ventricular hypertrophy, left atrial enlargement, diabetes, coronary heart disease, and heart failure. The area under the receiver operating characteristics curve (AUC) of a Cox regression model that included the previous variables was 0.78, suggesting moderately good discrimination. The point-based score developed from the coefficients in the Cox model had an AUC of 0.76. This clinical risk score for AF in the Atherosclerosis Risk In Communities cohort compared favorably with the Framingham Heart Study's AF (AUC 0.68), coronary heart disease (CHD) (AUC 0.63), and hard CHD (AUC 0.59) risk scores and the Atherosclerosis Risk In Communities CHD risk score (AUC 0.58). In conclusion, we have developed a risk score for AF and have shown that the different pathophysiologies of AF and CHD limit the usefulness of a CHD risk score in identifying subjects at greater risk of AF.
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Although men have higher absolute rates for incidence of atrial fibrillation, the relative rates of incident atrial fibrillation associated with diabetes are higher in women than in men for both type 1 and type 2 diabetes.
“Although men have higher absolute rates for incidence of AF, the relative rates of incident AF associated with diabetes are higher in women than in men for both T1DM and T2DM.[586][587][588]”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [586]
Type 1 diabetes is independently associated with a higher incidence of atrial fibrillation.
“Recent, large analyses confirmed that T1DM was also independently associated with a higher incidence of AF. [586][587][588]”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [586]
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“Women 161 (6) 159 (6) 160 (6) 161 (6) 163 (6) 161 (6) 161(6)”
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“The more risk factors that an individual has, the greater the likelihood that a person will develop AF and more persistent AF [90,91].”
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“Cardiovascular Health Study (inclusion from 1989 to 1993; last evaluation for AF in 1996) (6), the Atherosclerosis Risk in Communities study (inclusion from 1987 to 1989; follow-up until 1998) (7), and the Rotterdam Study (inclusion from 1990 to 1993; follow-up until 1999) (25)—followed their participants up to the 21…”
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Self-citationIncident Atrial Fibrillation Among Asians, Hispanics, Blacks, and Whites
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“Dans une étude prospective, l’hypertrophie ventriculaire gauche est également apparue prédictive de la survenue d’une FA de novo.(71) Les paramètres échocardiographiques prédictifs de FA ont des effets estimés d’ampleur similaire à celle des facteurs prédictifs électrocardiographiques et comprennent l’augmentation du…”
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“A score derived from the Atherosclerosis Risk in Communities (ARIC) study, based in a younger and biracial cohort, also found race (higher risk in white than African American), smoking status, height, history of diabetes and coronary heart disease, and left ventricular hypertrophy and left atrial enlargement (using EC…”
MethodEvaluating the Atrial Myopathy Underlying Atrial Fibrillation
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“30 M/F 1.5/1.5 Dublin et al.34 per unit BMI 1.03 Continued . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Table 1 Continued Less validated risk factors and risk markers Hazard ratio Marcus et al.18 – – Cham…”
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“Similarly, the Atherosclerosis Risk in Communities study showed that a 10-year clinical risk score incorporating age, race, smoking, systolic BP, hypertension treatment, electrocardiographic LVH, electrocardiographic left atrial enlargement, diabetes, CHD and heart failure was predictive for development of AF in a mul…”
BackgroundA Simple Clinical Risk Score (C2HEST) for Predicting Incident Atrial Fibrillation in Asian Subjects
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Are cardiovascular risk factors also associated with the incidence of atrial fibrillation?
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“97) (46), one report showed a null association (28), three reports were direct but non-significant (from 1.”
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Self-citationLifetime Risks, Projected Numbers, and Adverse Outcomes in Asian Patients With Atrial Fibrillation
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Risk Factor Management in Atrial Fibrillation
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“community-based cohorts [27–29].”
Novel genetic markers improve measures of atrial fibrillation risk prediction
Everett, B. M., Cook, N. R., Conen, D., Chasman, D. I., Ridker, P. M., & Albert, C. M. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht033 · Cited by 141 · see citing works
“26 In contrast, we found that a risk score comprised of 12 variants at nine AF loci improved several measures of AF risk prediction including the c-index, the continuous NRI, and the IDI in our population of women without established CVD.”
InfluentialPredicting Atrial Fibrillation in Primary Care Using Machine Learning
Hill, N. R., Ayoubkhani, D., McEwan, P. C., Sugrue, D., Farooqui, U., Lister, S., Lumley, M., Bakhai, A., Cohen, A. T., O'Neill, M. D., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0224582 · Cited by 137 · see citing works
“The risk factors emerging from our baseline model are therefore already well established, and include patient demographics[11–13], heart failure[11–13], diabetes[11, 12], left ventricular hypertrophy[11, 12], coronary heart disease[12], myocardial infarction[11], antihypertensive treatment[11–13], and SBP[11–13].”
BackgroundMethodInfluentialWalkey, A. J., Greiner, M. A., Heckbert, S. R., Jensen, P. N., Piccini, J. P., Sinner, M. F., Curtis, L. H., & Benjamin, E. J. (2013) · American Heart Journal · doi:10.1016/j.ahj.2013.03.020 · Cited by 136 · see citing works
Atrial fibrillation in patients with chronic lymphocytic leukemia (CLL)
Shanafelt, T. D., Parikh, S. A., Noseworthy, P. A., Goede, V., Rabe, K. G., Bahlo, J., Call, T. G., Schwager, S. M., Ding, W., Eichhorst, B. F., et al. (2016) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2016.1257795 · Cited by 135 · see citing works
“systems.[27,42,43] An association between ibrutinib and increased risk”
BackgroundAssociation between serum uric acid and atrial fibrillation: A systematic review and meta-analysis
Tamariz, L. J., Hernandez, F., Bush, A. L., Palacio, A., & Hare, J. M. (2014) · Heart Rhythm · doi:10.1016/j.hrthm.2014.04.003 · Cited by 131 · see citing works
Artificial Intelligence–Electrocardiography to Predict Incident Atrial Fibrillation
Christopoulos, G., Graff‐Radford, J., Lopez, C., Yao, X., Attia, Z. I., Rabinstein, A. A., Petersen, R. C., Knopman, D. S., Mielke, M. M., Kremers, W. K., et al. (2020) · Circulation Arrhythmia and Electrophysiology · doi:10.1161/circep.120.009355 · Cited by 126 · see citing works
“In the original CHARGE-AF Consortium study 6 the CHARGE-AF score was derived from 3 large US-based studies 12–14 and validated in 2 European studies.”
MethodKnuiman, M. W., Briffa, T. G., Divitini, M., Chew, D. P., Eikelboom, J. W., McQuillan, B., & Hung, J. (2014) · European Journal of Epidemiology · doi:10.1007/s10654-013-9875-y · Cited by 123 · see citing works
“Our finding of a greater risk of AF in people on treatment for hypertension is not surprising as this is well established and published AF risk scores all include antihypertensive treatment [17–19].”
BackgroundMethodResultInfluentialChamberlain, A. M., Alonso, Á., Gersh, B. J., Manemann, S. M., Killian, J. M., Weston, S. A., Byrne, M., & Roger, V. L. (2016) · American Heart Journal · doi:10.1016/j.ahj.2016.11.008 · Cited by 122 · see citing works
“The risk factors for AF have been studied, and several risk prediction tools have been developed to ascertain an individual's risk of developing AF.(5-9) Patients with AF have an excess risk of hospitalization and death than do patients without AF.”
Self-citationElectrocardiographic PR Interval and Adverse Outcomes in Older Adults
Magnani, J. W., Wang, N., Nelson, K. P., Connelly, S., Deo, R., Rodondi, N., Schelbert, E. B., Garcia, M. E., Phillips, C. L., Shlipak, M. G., et al. (2012) · Circulation Arrhythmia and Electrophysiology · doi:10.1161/circep.112.975342 · Cited by 120 · see citing works
“PR interval has been associated with AF in multiple longitudinal cohort studies, as has its constituent component, P wave duration.(14,27,28) There has been discussion regarding the decreased prevalence of AF in blacks, despite both clinical risk factors and prolonged measures of atrial electric function, compared wit…”
ResultPoststroke atrial fibrillation: Cause or consequence?
Sposato, L. A., Riccio, P. M., & Hachinski, V. (2014) · Neurology · doi:10.1212/wnl.0000000000000265 · Cited by 116 · see citing works
“Neurology 82 April 1, 2014 1183 CABG surgery (OR 0.60, 95% CI 0.46–0.78).55 Further studies are needed for assessing the benefit of these drugs and other agents (i.e., angiotensin inhibitors and diuretics) in the acute setting of ischemic stroke for preventing the occurrence of paroxysmal AF.”
BackgroundInfluentialGenetic Risk Prediction of Atrial Fibrillation
Lubitz, S. A., Yin, X., Lin, H. J., Kolek, M. J., Smith, J. G., Trompet, S., Rienstra, M., Rost, N. S., Teixeira, P. L., Almgren, P., et al. (2016) · Circulation · doi:10.1161/circulationaha.116.024143 · Cited by 112 · see citing works
Self-citationAssociation of Sex Hormones, Aging, and Atrial Fibrillation in Men: The Framingham Heart Study
Magnani, J. W., Moser, C. B., Murabito, J. M., Sullivan, L. M., Wang, N., Ellinor, P. T., Vasan, R. S., Benjamin, E. J., & Coviello, A. D. (2014) · Circulation: Arrhythmia and Electrophysiology · doi:10.1161/circep.113.001322 · Cited by 112 · see citing works
“The risk of incident AF in men is approximately twice that of women.(1) As a result, we consider identifying sex-specific risk factors as relevant to the epidemiology of AF.”
BackgroundWin, T. T., Ambale‐Venkatesh, B., Volpe, G. J., Mewton, N., Rizzi, P., Sharma, R. K., Strauss, D. G., Lima, J. A. C., & Tereshchenko, L. G. (2014) · Heart Rhythm · doi:10.1016/j.hrthm.2014.09.044 · Cited by 114 · see citing works
“Common risk factors of AF (hypertension, coronary heart disease, HF, and diabetes) are well acknowledged.(7,8) In response”
BackgroundKokubo, Y., Watanabe, M., Higashiyama, A., Nakao, Y. M., KUSANO, K. F., & Miyamoto, Y. (2017) · Circulation Journal · doi:10.1253/circj.cj-17-0277 · Cited by 110 · see citing works
Brieger, D. B., Amerena, J. V., Attia, J., Bajorek, B. V., Chan, K. H., Connell, C., Freedman, B., Ferguson, C., Hall, T. L., Haqqani, H. M., et al. (2018) · The Medical Journal of Australia · doi:10.5694/mja18.00646 · Cited by 106 · see citing works
Wetmore, J. B., Mahnken, J. D., Rigler, S. K., Ellerbeck, E. F., Mukhopadhyay, P., Spertus, J. A., Hou, Q., & Shireman, T. I. (2011) · Kidney International · doi:10.1038/ki.2011.416 · Cited by 106 · see citing works
The impact of height on the risk of atrial fibrillation: the Cardiovascular Health Study
Rosenberg, M. A., Patton, K. K., Sotoodehnia, N., Karas, M. G., Kizer, J. R., ZIMETBAUM, P. J., Chang, J. D., Siscovick, D. S., Gottdiener, J. S., Kronmal, R. A., et al. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs301 · Cited by 101 · see citing works
Christophersen, I. E., Yin, X., Larson, M. G., Lubitz, S. A., Magnani, J. W., McManus, D. D., Ellinor, P. T., & Benjamin, E. J. (2016) · American Heart Journal · doi:10.1016/j.ahj.2016.05.004 · Cited by 102 · see citing works
Li, Y., Bisson, A., Bodin, A., Herbert, J., Grammatico‐Guillon, L., Joung, B., Wang, Y., Lip, G. Y. H., & Fauchier, L. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.119.012546 · Cited by 102 · see citing works
Zhu, W., Yuan, P., Shen, Y., Wan, R., & Hong, K. (2016) · International Journal of Cardiology · doi:10.1016/j.ijcard.2016.05.013 · Cited by 102 · see citing works
“Among these 16 articles, 8 articles[22, 23, 27, 28, 30, 31, 33, 34] divided participants into never, former, and current smokers, while 4 articles[25, 28, 29, 33] compared the risk of AF between”
InfluentialChen, L. Y., Leening, M. J. G., Norby, F. L., Roetker, N. S., Albert Hofman, D., Franco, O. H., Pan, W., Polak, J. F., Witteman, J. C. M., Kronmal, R. A., et al. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.115.002907 · Cited by 103 · see citing works
Self-citationAssociations of Abdominal Obesity and New‐Onset Atrial Fibrillation in the General Population
Baek, Y., Yang, P., Kim, T., Uhm, J., Park, J., Pak, H., Lee, M., & Joung, B. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.116.004705 · Cited by 100 · see citing works
“In community-dwelling cohorts, increased WC and waist-to-hip circumference ratio are associated with 11% to 13% higher risk of AF over a 13- to 15-year follow-up period.(4,8,39) Elevated body fat mass has been recently associated with a 29% increased risk of AF during a 13.”
BackgroundHimmelreich, J. C. L., Veelers, L., Lucassen, W. A. M., Schnabel, R. B., Rienstra, M., van Weert, H. C. P. M., & Harskamp, R. E. (2020) · EP Europace · doi:10.1093/europace/euaa005 · Cited by 100 · see citing works
“…0.00; I2 = 94% Heterogeneity: Tau2 = 0.00; I2 = 100% Heterogeneity: Tau2 = 0.00; I2 = 100% FHS-AF ten-year model Alonso 2013 (AGES) Alonso 2013 (RS) Chamberlain 2011 (ARIC) Kokubo 2017 (Suita) Schnabel 2009 (FHS)a Subtotal (95% CI) 4469 3203 14546 6864 4764 33846 20.0% 18.2% 20.1% 20.6% 21.2%…”
InfluentialAune, D., Mahamat‐Saleh, Y., Kobeissi, E., Feng, T., Heath, A. K., & Janszky, I. (2023) · European Journal of Epidemiology · doi:10.1007/s10654-022-00914-0 · Cited by 105 · see citing works
Wagoner, D. R. V., Piccini, J. P., Albert, C. M., Anderson, M. E., Benjamin, E. J., Brundel, B. J. J. M., Califf, R. M., Calkins, H. G., Chen, P., Chiamvimonvat, N., et al. (2014) · Heart Rhythm · doi:10.1016/j.hrthm.2014.11.011 · Cited by 95 · see citing works
Gumprecht, J. J., Domek, M., Lip, G. Y. H., & Shantsila, A. (2019) · Journal of Human Hypertension · doi:10.1038/s41371-019-0279-7 · Cited by 97 · see citing works
Lip, G. Y. H., Gelder, I. C. V., Bax, J. J., Hylek, E. M., Kääb, S., Schotten, U., Wegscheider, K., Boriani, G., Ezekowitz, M. D., Diener, H. C., et al. (2011) · Thrombosis and Haemostasis · doi:10.1160/th11-07-0517 · Cited by 91 · see citing works
Dzeshka, M. S., Shahid, F., Shantsila, A., & Lip, G. Y. H. (2017) · American Journal of Hypertension · doi:10.1093/ajh/hpx013 · Cited by 91 · see citing works
Nasir, J. M., Pomeroy, W. C., Marler, A. T., Hann, M. C., Baykaner, T., Jones, R., Stoll, R., Hursey, K., Meadows, A., Walker, J., et al. (2017) · Heart Rhythm · doi:10.1016/j.hrthm.2017.04.026 · Cited by 91 · see citing works
Liao, J., Chao, T., Liu, C., Wang, K.-L., Chen, S., Lin, Y., Chang, S., Lo, L., Hu, Y., Tuan, T., et al. (2015) · Kidney International · doi:10.1038/ki.2014.393 · Cited by 90 · see citing works
Badimón, L., Bugiardini, R., Cenko, E., Cubedo, J., Dorobanţu, M., Duncker, D. J., Estruch, R., Miličić, D., Tousoulis, D., Vasiljević, Z., et al. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx181 · Cited by 88 · see citing works
Alexander, B., Milden, J., Hazim, B., Haseeb, S., Bayés‐Genís, A., Elosúa, R., Martínez‐Sellés, M., Yeung, C., Hopman, W. M., de Luna, A. B., et al. (2019) · Annals of Noninvasive Electrocardiology · doi:10.1111/anec.12669 · Cited by 90 · see citing works
“…increase in the risk of major embolic events such as stroke as well as an increased risk of heart failure and death (Alonso et al., 2013; Chamberlain et al., 2011; January et al., 2014; Kokubo 1Division of Cardiology, Queen’s University, Kingston, Ontario, Canada 2Generalitat de…”
BackgroundMethodAronis, K. N., Zhao, D., Hoogeveen, R. C., Alonso, Á., Ballantyne, C. M., Güallar, E., Jones, S. R., Martin, S. S., Nazarian, S., Steffen, B. T., et al. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.117.007372 · Cited by 86 · see citing works
“Lp(a) levels are associated with atherosclerotic cardiovascular disease, which, in turn, is associated with incident AF.14,15 Other markers of atherosclerosis such as coronary calcium score and carotid intima- media thickness have been associated with AF.16,17 The role of Lp(a) as an independent risk factor for AF rem…”
BackgroundInfluentialFrost, L., Benjamin, E. J., Fenger‐Grøn, M., Pedersen, A., Tjønneland, A. M., & Overvad, K. (2014) · Obesity · doi:10.1002/oby.20706 · Cited by 86 · see citing works
“8 Alcohol (g per day) 13 (2-47) 16 (2-59) Total energy intake (kj per day) 9544 (6604-13385) 9920 (6918-13835)”
BackgroundAtrial Fibrillation Predictors: Importance of the Electrocardiogram
German, D. M., Kabir, M., Dewland, T. A., Henrikson, C. A., & Tereshchenko, L. G. (2015) · Annals of Noninvasive Electrocardiology · doi:10.1111/anec.12321 · Cited by 85 · see citing works
“78,[70] and has been shown to correlate with underlying structural changes in the atria, such as infiltrated atrial adipose tissue.”
New-onset atrial fibrillation prediction: the HARMS2-AF risk score
Segan, L. A., Cánovas, R., Nanayakkara, S., Chieng, D., Prabhu, S., Voskoboinik, A., Sugumar, H., Ling, L., Lee, G., Morton, J. B., et al. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad375 · Cited by 81 · see citing works
Alonso, Á., Roetker, N. S., Soliman, E. Z., Chen, L. Y., Greenland, P., & Heckbert, S. R. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.115.003077 · Cited by 81 · see citing works
“Starting with a risk score created by the Framingham Heart Study (FHS) investigators,(4) and validated in separate cohorts,(5) other models have been developed in single cohorts, such as the Atherosclerosis Risk in Communities (ARIC) study.(6) More recently, the Cohorts for Heart and Aging Research in Genomic Epidemio…”
MethodSelf-citationToledo, M. E. G., Klein, F., Riccio, P. M., Cassará, F. P., Giacomelli, F. M., Racosta, J. M., Roberts, E., & Sposato, L. A. (2013) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2013.05.015 · Cited by 79 · see citing works
Liu, X., Abudukeremu, A., Jiang, Y., Cao, Z., Wu, M., Ma, J., Sun, R., He, W., Chen, Z., Chen, Y., et al. (2023) · Cardiovascular Diabetology · doi:10.1186/s12933-023-01777-9 · Cited by 78 · see citing works
Obesity Begets Atrial Fibrillation
Magnani, J. W., Hylek, E. M., & Apovian, C. M. (2013) · Circulation · doi:10.1161/circulationaha.113.001840 · Cited by 72 · see citing works
“Two of the risk scores were conducted in biracial cohorts, thereby enhancing their generalizability.(7,8) Figure 1 presents the Framingham Heart Study 10-year AF risk calculator for the patient described in the case presentation (http://www.”
Electrocardiographic abnormalities and cardiac arrhythmias in chronic obstructive pulmonary disease
Goudis, C. A., Konstantinidis, A. K., Ntalas, I. V., & Korantzopoulos, P. G. (2015) · International Journal of Cardiology · doi:10.1016/j.ijcard.2015.06.096 · Cited by 72 · see citing works
Garg, P. K., O’Neal, W. T., Chen, L. Y., Loehr, L. R., Sotoodehnia, N., Soliman, E. Z., & Alonso, Á. (2018) · Journal of the American Heart Association · doi:10.1161/jaha.117.008424 · Cited by 72 · see citing works
Self-citationAmbrus, D. B., Benjamin, E. J., Bajwa, E. K., Hibbert, K. A., & Walkey, A. J. (2015) · Journal of Critical Care · doi:10.1016/j.jcrc.2015.06.003 · Cited by 69 · see citing works
“Prior studies using population-based [2,3], singlecenter [7-9], or trial [10] data have shown that acute factors (eg, choice of vasopressor, acute organ failures, mechanical ventilation, and right heart catheterization), rather than preexisting cardiovascular comorbidities [11,12] are associated with increased risk fo…”
Trajectories of Risk Factors and Risk of New-Onset Atrial Fibrillation in the Framingham Heart Study
Rahman, F., Yin, X., Larson, M. G., Ellinor, P. T., Lubitz, S. A., Vasan, R. S., McManus, D. D., Magnani, J. W., & Benjamin, E. J. (2016) · Hypertension · doi:10.1161/hypertensionaha.116.07683 · Cited by 68 · see citing works
Usefulness of HATCH score in the prediction of new-onset atrial fibrillation for Asians
Suenari, K., Chao, T., Liu, C.-J., Kihara, Y., Chen, T.-J., & Chen, S.-A. (2017) · Medicine · doi:10.1097/md.0000000000005597 · Cited by 67 · see citing works
Zeller, T., Schnabel, R. B., Appelbaum, S., Ojeda, F., Berisha, F., Steinberg, B. S., Brueckmann, B.-E., Kuulasmaa, K., Jousilahti, P., Blankenberg, S., et al. (2018) · European Journal of Preventive Cardiology · doi:10.1177/2047487318778346 · Cited by 70 · see citing works
Valbusa, F., Bertolini, L., Bonapace, S., Zenari, L., Zoppini, G., Arcaro, G., Byrne, C. D., & Targher, G. (2013) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2013.04.012 · Cited by 66 · see citing works
Performance of the CHARGE-AF risk model for incident atrial fibrillation in the EPIC Norfolk cohort
Pfister, R., Brägelmann, J., Michels, G., Wareham, N. J., Luben, R., & Khaw, K. (2014) · European Journal of Preventive Cardiology · doi:10.1177/2047487314544045 · Cited by 65 · see citing works
“thoroughly or included risk factors which are not routinely available in primary care such as PR interval on ECG and echocardiographic left-ventricular hypertrophy and left atrial enlargement.(6,7) Recently the CHARGE-HF consortium published a simple risk model derived from three US cohorts using variables readily ava…”
MethodGrecu, M., Blomström‐Lundqvist, C., Kautzner, J., Laroche, C., Gelder, I. C. V., Jordaens, L. J. L. M., Tavazzi, L., Cihak, R. J., Campal, J. M. R., Kalarus, Z. F., et al. (2019) · EP Europace · doi:10.1093/europace/euz225 · Cited by 64 · see citing works
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 · see citing works
Schmidt, M., Bøtker, H. E., Pedersen, L. H., & Sørensen, H. T. (2013) · European Journal of Epidemiology · doi:10.1007/s10654-013-9867-y · Cited by 62 · see citing works
Soliman, E. Z., Cammarata, M., & Li, Y. (2013) · Heart Rhythm · doi:10.1016/j.hrthm.2013.10.003 · Cited by 62 · see citing works
Self-citationHeidenreich, P. A., Solis, P., Estes, N. A. M., Fonarow, G. C., Jurgens, C. Y., Marine, J. E., McManus, D. D., & McNamara, R. L. (2016) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/hcq.0000000000000018 · Cited by 62 · see citing works
Svennberg, E., Lindahl, B., Berglund, L., Eggers, K. M., Venge, P., Zethelius, B., Rosenqvist, M., Lind, L., & Hijazi, Z. (2016) · International Journal of Cardiology · doi:10.1016/j.ijcard.2016.08.001 · Cited by 60 · see citing works
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Clinical Predictors of Risk for Atrial Fibrillation
Brunner, K. J., Bunch, T. J., Mullin, C. M., May, H. T., Bair, T. L., Elliot, D. W., Anderson, J. L., & Mahapatra, S. (2014) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2014.08.016 · Cited by 58 · see citing works
Usefulness of the Electrocardiographic P-Wave Axis as a Predictor of Atrial Fibrillation
Rangel, M. O., O’Neal, W. T., & Soliman, E. Z. (2015) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2015.10.013 · Cited by 58 · see citing works
Self-citationHeidenreich, P. A., Solis, P., Estes, N. A. M., Fonarow, G. C., Jurgens, C. Y., Marine, J. E., McManus, D. D., & McNamara, R. L. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.03.521 · Cited by 58 · see citing works
Atrial Fibrillation and Race – A Contemporary Review
Amponsah, M., Benjamin, E. J., & Magnani, J. W. (2013) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-013-0327-8 · Cited by 55 · see citing works
Atrial fibrillation: age at diagnosis, incident cardiovascular events, and mortality
Paludan‐Müller, C., Vad, O. B., Stampe, N. K., Diederichsen, S. Z., Andreasen, L., Monfort, L. M., Fosbøl, E. L., Køber, L., Torp-Pedersen, C. T., Svendsen, J. H., et al. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae216 · Cited by 55 · see citing works
“Conventional AF prediction models have mostly been based on non-modifiable risk factors, 2,32,33 but the HARMS 2 -AF model incorporating lifestyle factors was recently Figure 4 Average life expectancy.”
- Authors
- Chamberlain, A. M., Agarwal, S. K., Folsom, A. R., Soliman, E. Z., Chambless, L. E., Crow, R., Ambrose, M., & Alonso, A.
- Affiliations
- Mayo Clinic (US)
- University of North Carolina at Chapel Hill (US)
- University of Minnesota (US)
- Wake Forest University Health Sciences (US)
- Johns Hopkins University (US)
- Corresponding author
- Chamberlain, Alanna M.
- ORCID
- Venue
- The American Journal of Cardiology
- Publisher
- Elsevier BV
- Published
- 2011-01
- Volume
- 107
- Issue
- 1
- Pages
- 85-91
- ISSN
- 0002-9149 (ISSN-L)
- PMC
- PMC3031130
- OpenAlex
- W2154432863
- Cited by
- 354
- References
- 30
- Citations by year
- 2026: 6 · 2025: 22 · 2024: 25 · 2023: 19 · 2022: 24 · 2021: 37 · 2020: 30 · 2019: 14 · 2018: 24 · 2017: 26 · 2016: 33 · 2015: 17 · 2014: 22 · 2013: 31 · 2012: 14
- FWCI
- 11.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The American Journal of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- American Heart Association (RC1HL101056, RC1HL099452)
- National Heart, Lung, and Blood Institute (T32-HL-007779, 09SDG2280087)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Health Sciences › Medicine › Epidemiology › Acute Ischemic Stroke Management
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- atrial fibrillation, risk score, new-onset atrial fibrillation, Framingham Heart Study, Atherosclerosis Risk in Communities Study, racial differences, black and white populations, left atrial enlargement, left ventricular hypertrophy, hypertension, diabetes mellitus, heart failure, coronary artery disease
- MeSH terms
- Atrial Fibrillation, Female, Follow-Up Studies, Forecasting, Humans, Male, Middle Aged, Risk Factors, Cohort Studies, Incidence
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