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01-12-2021 | Heart Failure | Research article

Temporal trends in cause-specific mortality among individuals with newly diagnosed atrial fibrillation in the Framingham Heart Study

Authors: Jelena Kornej, Qiuxi Huang, Sarah R. Preis, Steven A. Lubitz, Darae Ko, Joanne M. Murabito, Emelia J. Benjamin, Ludovic Trinquart

Published in: BMC Medicine | Issue 1/2021

Abstract

Background

All-cause mortality following atrial fibrillation (AF) has decreased over time. Data regarding temporal trends in causes of death among individuals with AF are scarce. The aim of our study was to analyze temporal trends in cause-specific mortality and predictors for cardiovascular (CVD) and non-CVD deaths among participants with incident AF in the Framingham Heart Study.

Methods

We categorized all newly diagnosed AF cases according to age at AF diagnosis (< 70, 70 to < 80, and ≥ 80 years) and epoch of AF diagnosis (< 1990, 1990–2002, and ≥ 2003). We followed participants until death or the last follow-up. We categorized death causes into CVD, non-CVD, and unknown causes. For each age group, we tested for trends in the cumulative incidence of cause-specific death across epochs. We fit multivariable Fine-Gray models to assess subdistribution hazard ratios (HR) between clinical risk factors at AF diagnosis and cause-specific mortality.

Results

We included 2125 newly diagnosed AF cases (mean age 75.5 years, 47.8% women). During a median follow-up of 4.8 years, 1657 individuals with AF died. There was evidence of decreasing CVD mortality among AF cases diagnosed < 70 years and 70 to < 80 years (p_trend < 0.001) but not ≥ 80 years (p = 0.76). Among the cases diagnosed < 70 years, the cumulative incidence of CVD death at 75 years was 67.7% in epoch 1 and 13.9% in epoch 3; among those 70 to < 80 years, the incidence at 85 years was 58.9% in epoch 1 and 18.9% in epoch 3. Advancing age (HR per 1 SD increase 6.33, 95% CI 5.44 to 7.37), prior heart failure (HR 1.49, 95% CI 1.14–1.94), and prior myocardial infarction (HR 1.44, 95% CI 1.15–1.80) were associated with increased rate of CVD death.

Conclusions

In this community-based cohort, CVD mortality among AF cases decreased over time. Most deaths in individuals with AF are no longer CVD-related, regardless of age at AF diagnosis.

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Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 Study. J Am Coll Cardiol. 2020;76(25):2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010.CrossRefPubMedPubMedCentral

Staerk L, Wang B, Preis SR, Larson MG, Lubitz SA, Ellinor PT, et al. Lifetime risk of atrial fibrillation according to optimal, borderline, or elevated levels of risk factors: cohort study based on longitudinal data from the Framingham Heart Study. BMJ. 2018;361:k1453.CrossRef

Mou L, Norby FL, Chen LY, O’Neal WT, Lewis TT, Loehr LR, et al. Lifetime risk of atrial fibrillation by race and socioeconomic status: ARIC Study (Atherosclerosis Risk in Communities). Circ Arrhythm Electrophysiol. 2018;11(7):e006350. https://doi.org/10.1161/CIRCEP.118.006350.CrossRefPubMedPubMedCentral

Kornej J, Börschel C, Benjamin E, Schnabel R. Epidemiology of atrial fibrillation in the 21st century: novel methods and new insights. Circ Res. 2020;27:4–20.CrossRef

Miyasaka Y, Barnes ME, Gersh BJ, Cha SS, Bailey KR, Abhayaratna WP, et al. Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence. Circulation. 2006;114(2):119–25. https://doi.org/10.1161/CIRCULATIONAHA.105.595140.CrossRefPubMed

Colilla S, Crow A, Petkun W, Singer DE, Simon T, Liu X. Estimates of current and future incidence and prevalence of atrial fibrillation in the U.S. adult population. Am J Cardiol. 2013;112(8):1142–7. https://doi.org/10.1016/j.amjcard.2013.05.063.CrossRefPubMed

Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, et al. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association of Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2020.

January CT, Wann LS, Calkins H, Chen LY, Cigarroa JE, Cleveland JC Jr, et al. 2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients with Atrial Fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society in Collaboration with the Society of Thoracic Surgeons. Circulation. 2019;140(2):e125–51. https://doi.org/10.1161/CIR.0000000000000665.CrossRefPubMed

Miyasaka Y, Barnes ME, Bailey KR, Cha SS, Gersh BJ, Seward JB, et al. Mortality trends in patients diagnosed with first atrial fibrillation: a 21-year community-based study. J Am Coll Cardiol. 2007;49(9):986–92. https://doi.org/10.1016/j.jacc.2006.10.062.CrossRefPubMed

10.

Schnabel RB, Yin X, Gona P, Larson MG, Beiser AS, McManus DD, et al. 50 year trends in atrial fibrillation prevalence, incidence, risk factors, and mortality in the Framingham Heart Study: a cohort study. Lancet. 2015;386(9989):154–62. https://doi.org/10.1016/S0140-6736(14)61774-8.CrossRefPubMedPubMedCentral

11.

Freeman JV, Wang Y, Akar J, Desai N, Krumholz H. National trends in atrial fibrillation hospitalization, readmission, and mortality for Medicare beneficiaries, 1999-2013. Circulation. 2017;135(13):1227–39. https://doi.org/10.1161/CIRCULATIONAHA.116.022388.CrossRefPubMed

12.

Bassand JP, Accetta G, Camm AJ, Cools F, Fitzmaurice DA, Fox KA, et al. Two-year outcomes of patients with newly diagnosed atrial fibrillation: results from GARFIELD-AF. Eur Heart J. 2016;37(38):2882–9. https://doi.org/10.1093/eurheartj/ehw233.CrossRefPubMedPubMedCentral

13.

Fauchier L, Villejoubert O, Clementy N, Bernard A, Pierre B, Angoulvant D, et al. Causes of death and influencing factors in patients with atrial fibrillation. Am J Med. 2016;129(12):1278–87. https://doi.org/10.1016/j.amjmed.2016.06.045.CrossRefPubMed

14.

Kuronuma K, Okumura Y, Yokoyama K, Matsumoto N, Tachibana E, Oiwa K, et al. Different determinants of vascular and nonvascular deaths in patients with atrial fibrillation: a SAKURA AF Registry substudy. J Cardiol. 2019;73(3):210–7. https://doi.org/10.1016/j.jjcc.2018.12.003.CrossRefPubMed

15.

Marijon E, Le Heuzey JY, Connolly S, Yang S, Pogue J, Brueckmann M, et al. Causes of death and influencing factors in patients with atrial fibrillation: a competing-risk analysis from the randomized evaluation of long-term anticoagulant therapy study. Circulation. 2013;128(20):2192–201. https://doi.org/10.1161/CIRCULATIONAHA.112.000491.CrossRefPubMed

16.

An Y, Ogawa H, Yamashita Y, Ishii M, Iguchi M, Masunaga N, et al. Causes of death in Japanese patients with atrial fibrillation: the Fushimi Atrial Fibrillation Registry. Eur Heart J Qual Care Clin Outcomes. 2019;5(1):35–42. https://doi.org/10.1093/ehjqcco/qcy033.CrossRefPubMed

17.

Dawber TR, Meadors GF, Moore FE Jr. Epidemiological approaches to heart disease: the Framingham Study. Am J Public Health Nations Health. 1951;41(3):279–81. https://doi.org/10.2105/AJPH.41.3.279.CrossRefPubMedPubMedCentral

18.

Kannel WB, Dawber TR, Kagan A, Revotskie N, Stokes J 3rd. Factors of risk in the development of coronary heart disease--six year follow-up experience. The Framingham Study. Ann Intern Med. 1961;55(1):33–50. https://doi.org/10.7326/0003-4819-55-1-33.CrossRefPubMed

19.

Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families. The Framingham Offspring Study. Am J Epidemiol. 1979;110(3):281–90. https://doi.org/10.1093/oxfordjournals.aje.a112813.CrossRefPubMed

20.

Lubitz SA, Yin X, Rienstra M, Schnabel RB, Walkey AJ, Magnani JW, et al. Long-term outcomes of secondary atrial fibrillation in the community: the Framingham Heart Study. Circulation. 2015;131(19):1648–55. https://doi.org/10.1161/CIRCULATIONAHA.114.014058.CrossRefPubMedPubMedCentral

21.

Allignol A, Schumacher M, Beyersmann J. A note on variance estimation of the Aalen-Johansen estimator of the cumulative incidence function in competing risks, with a view towards left-truncated data. Biom J. 2010;52(1):126–37. https://doi.org/10.1002/bimj.200900039.CrossRefPubMed

22.

Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94(446):496–509. https://doi.org/10.1080/01621459.1999.10474144.CrossRef

23.

Geskus RB. Cause-specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring. Biometrics. 2011;67(1):39–49. https://doi.org/10.1111/j.1541-0420.2010.01420.x.CrossRefPubMed

24.

Alonso A, Krijthe BP, Aspelund T, Stepas KA, Pencina MJ, Moser CB, et al. Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF Consortium. J Am Heart Assoc. 2013;2(2):e000102. https://doi.org/10.1161/JAHA.112.000102.CrossRefPubMedPubMedCentral

25.

Selvin E, Manzi J, Stevens LA, Van Lente F, Lacher DA, Levey AS, et al. Calibration of serum creatinine in the National Health and Nutrition Examination Surveys (NHANES) 1988-1994, 1999-2004. Am J Kidney Dis. 2007;50(6):918–26. https://doi.org/10.1053/j.ajkd.2007.08.020.CrossRefPubMed

26.

Stevens LA, Levey AS. Measured GFR as a confirmatory test for estimated GFR. J Am Soc Nephrol. 2009;20(11):2305–13. https://doi.org/10.1681/ASN.2009020171.CrossRefPubMed

27.

Conner SC, Lodi S, Lunetta KL, Casas JP, Lubitz SA, Ellinor PT, et al. Refining the association between body mass index and atrial fibrillation: G-formula and restricted mean survival times. J Am Heart Assoc. 2019;8(16):e013011. https://doi.org/10.1161/JAHA.119.013011.CrossRefPubMedPubMedCentral

28.

Ruff CT, Giugliano RP, Braunwald E, Hoffman EB, Deenadayalu N, Ezekowitz MD, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet. 2014;383(9921):955–62. https://doi.org/10.1016/S0140-6736(13)62343-0.CrossRefPubMed

29.

Hart RG, Pearce LA, Aguilar MI. Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation. Ann Intern Med. 2007;146(12):857–67. https://doi.org/10.7326/0003-4819-146-12-200706190-00007.CrossRefPubMed

30.

Pathak RK, Middeldorp ME, Lau DH, Mehta AB, Mahajan R, Twomey D, et al. Aggressive risk factor reduction study for atrial fibrillation and implications for the outcome of ablation: the ARREST-AF Cohort Study. J Am Coll Cardiol. 2014;64(21):2222–31. https://doi.org/10.1016/j.jacc.2014.09.028.CrossRefPubMed

31.

Pathak RK, Middeldorp ME, Meredith M, Mehta AB, Mahajan R, Wong CX, et al. Long-term effect of goal-directed weight management in an atrial fibrillation cohort: a long-term follow-up study (LEGACY). J Am Coll Cardiol. 2015;65(20):2159–69. https://doi.org/10.1016/j.jacc.2015.03.002.CrossRefPubMed

32.

Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet. 2020;395(10226):795–808. https://doi.org/10.1016/S0140-6736(19)32008-2.CrossRefPubMed

33.

Roth GA, Forouzanfar MH, Moran AE, Barber R, Nguyen G, Feigin VL, et al. Demographic and epidemiologic drivers of global cardiovascular mortality. N Engl J Med. 2015;372(14):1333–41. https://doi.org/10.1056/NEJMoa1406656.CrossRefPubMedPubMedCentral

34.

Collaborators GBDRF. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1223–49.CrossRef

35.

Hylek EM, Go AS, Chang Y, Jensvold NG, Henault LE, Selby JV, et al. Effect of intensity of oral anticoagulation on stroke severity and mortality in atrial fibrillation. N Engl J Med. 2003;349(11):1019–26. https://doi.org/10.1056/NEJMoa022913.CrossRefPubMed

36.

Collaborators GBDRF. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1659–724.CrossRef

37.

Healey JS, Oldgren J, Ezekowitz M, Zhu J, Pais P, Wang J, et al. Occurrence of death and stroke in patients in 47 countries 1 year after presenting with atrial fibrillation: a cohort study. Lancet. 2016;388(10050):1161–9. https://doi.org/10.1016/S0140-6736(16)30968-0.CrossRefPubMed

38.

Schnabel R, Pecen L, Engler D, Lucerna M, Sellal JM, Ojeda FM, et al. Atrial fibrillation patterns are associated with arrhythmia progression and clinical outcomes. Heart. 2018;104(19):1608–14. https://doi.org/10.1136/heartjnl-2017-312569.CrossRef

39.

Lubitz SA, Moser C, Sullivan L, Rienstra M, Fontes JD, Villalon ML, et al. Atrial fibrillation patterns and risks of subsequent stroke, heart failure, or death in the community. J Am Heart Assoc. 2013;2(5):e000126. https://doi.org/10.1161/JAHA.113.000126.CrossRefPubMedPubMedCentral

Title: Temporal trends in cause-specific mortality among individuals with newly diagnosed atrial fibrillation in the Framingham Heart Study
Authors: Jelena Kornej
Qiuxi Huang
Sarah R. Preis
Steven A. Lubitz
Darae Ko
Joanne M. Murabito
Emelia J. Benjamin
Ludovic Trinquart
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Heart Failure
Atrial Fibrillation
Published in: BMC Medicine / Issue 1/2021
Electronic ISSN: 1741-7015
DOI: https://doi.org/10.1186/s12916-021-02037-x

At a glance: The STEP trials

Springer Medicine

Temporal trends in cause-specific mortality among individuals with newly diagnosed atrial fibrillation in the Framingham Heart Study

Abstract

Background

Methods

Results

Conclusions

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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