Emma Svennberg1, Bertil Lindahl2, Lars Berglund3, Kai M Eggers2, Per Venge4, Björn Zethelius5, Mårten Rosenqvist6, Lars Lind4, Ziad Hijazi2. 1. Karolinska Institutet, Dept. of Clinical Sciences, Cardiology Unit, Danderyd's University Hospital, Stockholm, Sweden. Electronic address: emma.svennberg@ds.se. 2. Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden; Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden. 3. Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden. 4. Department of Medical Sciences, Uppsala University, Uppsala, Sweden. 5. Department of Public Health/Geriatrics, Uppsala University and Medical Products Agency/Scientific Support, Uppsala, Sweden. 6. Karolinska Institutet, Dept. of Clinical Sciences, Cardiology Unit, Danderyd's University Hospital, Stockholm, Sweden.
Abstract
BACKGROUND: Biomarkers may be of value to identify individuals at risk of developing atrial fibrillation (AF). Using a multimarker approach, this study investigated if the biomarkers; NT-proBNP, high-sensitivity cardiac troponin (hs-cTn), growth differentiation factor-15 (GDF-15), cystatin C and high-sensitivity C-reactive protein (CRP) are independent predictors for incident AF. METHODS: Blood samples were collected from 883 individuals in the Uppsala Longitudinal Study of Adult Men (ULSAM) and 978 individuals in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study. Participants were followed for 10-13years with n=113 incident AF cases in ULSAM and n=148 in PIVUS. The associations between biomarkers and incident AF were analysed in Cox proportional hazards regression models. RESULTS: The hazard ratio (HR) for incident AF was significant for all five biomarkers in unadjusted analyses in both cohorts. Only NT-proBNP remained significant when adjusting for cardiovascular risk factors and the other biomarkers (HR (1SD) 2.05 (1.62-2.59) (ULSAM) and 1.56 (1.30-1.86) (PIVUS), both p<0.001). The C-index improved from 0.64 to 0.69 in ULSAM and from 0.62 to 0.68 in PIVUS, by adding NT-proBNP to cardiovascular risk factors (both p<0.001). The C-index of the CHARGE-AF risk score increased from 0.62 to 0.68 (ULSAM) and 0.60 to 0.66 (PIVUS) by addition of NT-proBNP (p<0.001). CONCLUSIONS: Using a multimarker approach NT-proBNP was the strongest predictor of incident AF in two cohorts, and improved risk prediction when added to traditional risk factors. NT-proBNP significantly improved the predictive ability of the novel CHARGE-AF risk score, although the predictive value remained modest.
BACKGROUND: Biomarkers may be of value to identify individuals at risk of developing atrial fibrillation (AF). Using a multimarker approach, this study investigated if the biomarkers; NT-proBNP, high-sensitivity cardiac troponin (hs-cTn), growth differentiation factor-15 (GDF-15), cystatin C and high-sensitivity C-reactive protein (CRP) are independent predictors for incident AF. METHODS: Blood samples were collected from 883 individuals in the Uppsala Longitudinal Study of Adult Men (ULSAM) and 978 individuals in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study. Participants were followed for 10-13years with n=113 incident AF cases in ULSAM and n=148 in PIVUS. The associations between biomarkers and incident AF were analysed in Cox proportional hazards regression models. RESULTS: The hazard ratio (HR) for incident AF was significant for all five biomarkers in unadjusted analyses in both cohorts. Only NT-proBNP remained significant when adjusting for cardiovascular risk factors and the other biomarkers (HR (1SD) 2.05 (1.62-2.59) (ULSAM) and 1.56 (1.30-1.86) (PIVUS), both p<0.001). The C-index improved from 0.64 to 0.69 in ULSAM and from 0.62 to 0.68 in PIVUS, by adding NT-proBNP to cardiovascular risk factors (both p<0.001). The C-index of the CHARGE-AF risk score increased from 0.62 to 0.68 (ULSAM) and 0.60 to 0.66 (PIVUS) by addition of NT-proBNP (p<0.001). CONCLUSIONS: Using a multimarker approach NT-proBNP was the strongest predictor of incident AF in two cohorts, and improved risk prediction when added to traditional risk factors. NT-proBNP significantly improved the predictive ability of the novel CHARGE-AF risk score, although the predictive value remained modest.
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