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. 2014 Jan;167(1):109-115.e2.
doi: 10.1016/j.ahj.2013.10.003. Epub 2013 Oct 17.

Relation between soluble ST2, growth differentiation factor-15, and high-sensitivity troponin I and incident atrial fibrillation

Michiel Rienstra  1 , Xiaoyan Yin  2 , Martin G Larson  2 , João D Fontes  3 , Jared W Magnani  3 , David D McManus  4 , Elizabeth L McCabe  5 , Erin E Coglianese  6 , Michael Amponsah  7 , Jennifer E Ho  3 , James L Januzzi Jr  5 , Kai C Wollert  8 , Michael G Fradley  5 , Ramachandran S Vasan  9 , Patrick T Ellinor  10 , Thomas J Wang  11 , Emelia J Benjamin  9
Affiliations

Relation between soluble ST2, growth differentiation factor-15, and high-sensitivity troponin I and incident atrial fibrillation

Michiel Rienstra et al. Am Heart J. 2014 Jan.

Abstract

Background: We investigated whether circulating concentrations of soluble ST2, growth differentiation factor-15 (GDF-15), and high-sensitivity troponin I (hsTnI) are associated with incident atrial fibrillation (AF) and whether these biomarkers improve current risk prediction models including AF risk factors, B-type natriuretic peptide (BNP), and C-reactive protein (CRP).

Methods: We studied the relation between soluble ST2, GDF-15, and hsTnI and development of AF in Framingham Heart Study participants without prevalent AF. We used Cox proportional hazard regression analysis to examine the relation of incident AF during a 10-year follow-up period with each biomarker. We adjusted for standard AF clinical risk factors, BNP, and CRP.

Results: The mean age of the 3,217 participants was 59 ± 10 years, and 54% were women. During a 10-year follow-up, 242 participants developed AF. In age- and sex-adjusted models, GDF-15 and hsTnI were associated with risk of incident AF; however, after including the AF risk factors and BNP and CRP, only hsTnI was significantly associated with AF (hazard ratio per 1 SD of loge hsTnI, 1.12, 95% CI 1.00-1.26, P = .045). The c statistic of the base model including AF risk factors, BNP, and CRP was 0.803 (95% CI 0.777-0.830) and did not improve by adding individual or all 3 biomarkers. None of the discrimination and reclassification statistics were significant compared with the base model.

Conclusion: In a community-based cohort, circulating hsTnI concentrations were associated with incident AF. None of the novel biomarkers evaluated improved AF risk discrimination or reclassification beyond standard clinical AF risk factors and biomarkers.

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Figures

Figure 1
Figure 1
Adjusted cumulative risk of atrial fibrillation, according to tertiles of each biomarker (Figure 1A: soluble ST2, Figure 1B: GDF-15, Figure 1C: hsTnI). Presented are 1-average of cause-specific survival functions, for which death was deemed a censoring factor. Covariates included age, sex, height, weight, systolic and diastolic blood pressure, hypertension treatment, smoking status, diabetes, prevalent heart failure, prevalent myocardial infarction, CRP and BNP.
Figure 1
Figure 1
Adjusted cumulative risk of atrial fibrillation, according to tertiles of each biomarker (Figure 1A: soluble ST2, Figure 1B: GDF-15, Figure 1C: hsTnI). Presented are 1-average of cause-specific survival functions, for which death was deemed a censoring factor. Covariates included age, sex, height, weight, systolic and diastolic blood pressure, hypertension treatment, smoking status, diabetes, prevalent heart failure, prevalent myocardial infarction, CRP and BNP.
Figure 1
Figure 1
Adjusted cumulative risk of atrial fibrillation, according to tertiles of each biomarker (Figure 1A: soluble ST2, Figure 1B: GDF-15, Figure 1C: hsTnI). Presented are 1-average of cause-specific survival functions, for which death was deemed a censoring factor. Covariates included age, sex, height, weight, systolic and diastolic blood pressure, hypertension treatment, smoking status, diabetes, prevalent heart failure, prevalent myocardial infarction, CRP and BNP.
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References

    1. Benjamin EJ, Levy D, Vaziri SM, D’Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA. 1994;271(11):840–844. - PubMed
    1. Krahn AD, Manfreda J, Tate RB, Mathewson FA, Cuddy TE. The natural history of atrial fibrillation: incidence, risk factors, and prognosis in the Manitoba Follow-Up Study. AmJMed. 1995;98(5):476–484. - PubMed
    1. Frost L, Hune LJ, Vestergaard P. Overweight and obesity as risk factors for atrial fibrillation or flutter: The Danish Diet, Cancer, and Health Study. Am J Med. 2005;118:489–495. - PubMed
    1. Schnabel RB, Sullivan LM, Levy D, Pencina MJ, Massaro JM, D’Agostino RB, Sr., et al. Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort study. Lancet. 2009;373(9665):739–45. - PMC - PubMed
    1. Alonso A, Krijthe BP, Aspelund T, Stepas KA, Pencina MJ, Moser CB, et al. A simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium. JAHA. 2013 e-published. - PMC - PubMed

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