@article {1247, title = {Validation of an atrial fibrillation risk algorithm in whites and African Americans.}, journal = {Arch Intern Med}, volume = {170}, year = {2010}, month = {2010 Nov 22}, pages = {1909-17}, abstract = {

BACKGROUND: We sought to validate a recently published risk algorithm for incident atrial fibrillation (AF) in independent cohorts and other racial groups.

METHODS: We evaluated the performance of a Framingham Heart Study (FHS)-derived risk algorithm modified for 5-year incidence of AF in the FHS (n = 4764 participants) and 2 geographically and racially diverse cohorts in the age range 45 to 95 years: AGES (the Age, Gene/Environment Susceptibility-Reykjavik Study) (n = 4238) and CHS (the Cardiovascular Health Study) (n = 5410, of whom 874 [16.2\%] were African Americans). The risk algorithm included age, sex, body mass index, systolic blood pressure, electrocardiographic PR interval, hypertension treatment, and heart failure.

RESULTS: We found 1359 incident AF events in 100 074 person-years of follow-up. Unadjusted 5-year event rates differed by cohort (AGES, 12.8 cases/1000 person-years; CHS whites, 22.7 cases/1000 person-years; and FHS, 4.5 cases/1000 person-years) and by race (CHS African Americans, 18.4 cases/1000 person-years). The strongest risk factors in all samples were age and heart failure. The relative risks for incident AF associated with risk factors were comparable across cohorts and race groups. After recalibration for baseline incidence and risk factor distribution, the Framingham algorithm, reported in C statistic, performed reasonably well in all samples: AGES, 0.67 (95\% confidence interval [CI], 0.64-0.71); CHS whites, 0.68 (95\% CI, 0.66-0.70); and CHS African Americans, 0.66 (95\% CI, 0.61-0.71). Risk factors combined in the algorithm explained between 47.0\% (AGES) and 63.6\% (FHS) of the population-attributable risk.

CONCLUSIONS: Risk of incident AF in community-dwelling whites and African Americans can be assessed reliably by routinely available and potentially modifiable clinical variables. Seven risk factors accounted for up to 64\% of risk.

}, keywords = {African Continental Ancestry Group, Age Factors, Aged, Aged, 80 and over, Algorithms, Atrial Fibrillation, Blood Pressure, Body Mass Index, Cohort Studies, Electrocardiography, Europe, European Continental Ancestry Group, Female, Follow-Up Studies, Heart Failure, Humans, Hypertension, Incidence, Kaplan-Meier Estimate, Male, Middle Aged, Proportional Hazards Models, Risk Factors, Sex Factors, Systole, United States}, issn = {1538-3679}, doi = {10.1001/archinternmed.2010.434}, author = {Schnabel, Renate B and Aspelund, Thor and Li, Guo and Sullivan, Lisa M and Suchy-Dicey, Astrid and Harris, Tamara B and Pencina, Michael J and D{\textquoteright}Agostino, Ralph B and Levy, Daniel and Kannel, William B and Wang, Thomas J and Kronmal, Richard A and Wolf, Philip A and Burke, Gregory L and Launer, Lenore J and Vasan, Ramachandran S and Psaty, Bruce M and Benjamin, Emelia J and Gudnason, Vilmundur and Heckbert, Susan R} } @article {5878, title = {Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium.}, journal = {J Am Heart Assoc}, volume = {2}, year = {2013}, month = {2013 Mar 18}, pages = {e000102}, abstract = {

BACKGROUND: Tools for the prediction of atrial fibrillation (AF) may identify high-risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors.

METHODS AND RESULTS: Individual-level data from 3 large cohorts in the United States (Atherosclerosis Risk in Communities [ARIC] study, the Cardiovascular Health Study [CHS], and the Framingham Heart Study [FHS]), including 18 556 men and women aged 46 to 94 years (19\% African Americans, 81\% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment-Reykjavik study (AGES) and the Rotterdam Study (RS). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5-year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C-statistic, 0.765; 95\% CI, 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C-statistic, 0.767; 95\% CI, 0.750 to 0.783; categorical net reclassification improvement, -0.0032; 95\% CI, -0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable (AGES C-statistic, 0.664; 95\% CI, 0.632 to 0.697 and RS C-statistic, 0.705; 95\% CI, 0.664 to 0.747) and calibration was adequate.

CONCLUSION: A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the United States and Europe.

}, keywords = {African Americans, Age Factors, Aged, Aged, 80 and over, Atrial Fibrillation, Cohort Studies, Diabetes Mellitus, European Continental Ancestry Group, Female, Heart Failure, Humans, Hypertension, Iceland, Incidence, Male, Middle Aged, Myocardial Infarction, Netherlands, Proportional Hazards Models, Risk Assessment, Smoking, United States}, issn = {2047-9980}, doi = {10.1161/JAHA.112.000102}, author = {Alonso, Alvaro and Krijthe, Bouwe P and Aspelund, Thor and Stepas, Katherine A and Pencina, Michael J and Moser, Carlee B and Sinner, Moritz F and Sotoodehnia, Nona and Fontes, Jo{\~a}o D and Janssens, A Cecile J W and Kronmal, Richard A and Magnani, Jared W and Witteman, Jacqueline C and Chamberlain, Alanna M and Lubitz, Steven A and Schnabel, Renate B and Agarwal, Sunil K and McManus, David D and Ellinor, Patrick T and Larson, Martin G and Burke, Gregory L and Launer, Lenore J and Hofman, Albert and Levy, Daniel and Gottdiener, John S and K{\"a}{\"a}b, Stefan and Couper, David and Harris, Tamara B and Soliman, Elsayed Z and Stricker, Bruno H C and Gudnason, Vilmundur and Heckbert, Susan R and Benjamin, Emelia J} } @article {9637, title = {Development and Validation of the American Heart Association{\textquoteright}s PREVENT Equations.}, journal = {Circulation}, volume = {149}, year = {2024}, month = {2024 Feb 06}, pages = {430-449}, abstract = {

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS: Among 6 612 004 adults included, mean{\textpm}SD age was 53{\textpm}12 years, and 56\% were women. Over a mean{\textpm}SD follow-up of 4.8{\textpm}3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; =0.01).

CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

}, keywords = {Adult, Aged, Albumins, American Heart Association, Atherosclerosis, Cardiovascular Diseases, Creatinine, Female, Glycated Hemoglobin, Heart Failure, Humans, Male, Middle Aged, Risk Assessment, Risk Factors}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.123.067626}, author = {Khan, Sadiya S and Matsushita, Kunihiro and Sang, Yingying and Ballew, Shoshana H and Grams, Morgan E and Surapaneni, Aditya and Blaha, Michael J and Carson, April P and Chang, Alexander R and Ciemins, Elizabeth and Go, Alan S and Gutierrez, Orlando M and Hwang, Shih-Jen and Jassal, Simerjot K and Kovesdy, Csaba P and Lloyd-Jones, Donald M and Shlipak, Michael G and Palaniappan, Latha P and Sperling, Laurence and Virani, Salim S and Tuttle, Katherine and Neeland, Ian J and Chow, Sheryl L and Rangaswami, Janani and Pencina, Michael J and Ndumele, Chiadi E and Coresh, Josef} }