Dataset Information

Cluster Individuals Based on Phenotype and Determine the Risk for Atrial Fibrillation in the PREVEND and Framingham Heart Study Populations.

ABSTRACT:

Background

Risk prediction of atrial fibrillation (AF) is of importance to improve the early diagnosis and treatment of AF. Latent class analysis takes into account the possible existence of classes of individuals each with shared risk factors, and maybe a better method of incorporating the phenotypic heterogeneity underlying AF.

Methods and findings

Two prospective community-based cohort studies from Netherlands and United States were used. Prevention of Renal and Vascular End-stage Disease (PREVEND) study, started in 1997, and the Framingham Heart Study (FHS) Offspring cohort started in 1971, both with 10-years follow-up. The main objective was to determine the risk of AF using a latent class analysis, and compare the discrimination and reclassification performance with traditional regression analysis. Mean age in PREVEND was 49±13 years, 49.8% were men. During follow-up, 250(3%) individuals developed AF. We built a latent class model based on 18 risk factors. A model with 7 distinct classes (ranging from 341 to 1517 individuals) gave the optimum tradeoff between a high statistical model-likelihood and a low number of model parameters. All classes had a specific profile. The incidence of AF varied; class 1 0.0%, class 2 0.3%, class 3 7.5%, class 4 0.2%, class 5 1.3%, class 6 4.2%, class 7 21.7% (p<0.001). The discrimination (C-statistic 0.830 vs. 0.842, delta-C -0.013, p = 0.22) and reclassification (IDI -0.028, p<0.001, NRI -0.090, p = 0.049, and category-less-NRI -0.049, p = 0.495) performance of both models was comparable. The results were successfully replicated in a sample of the FHS study (n = 3162; mean age 58±9 years, 46.3% men).

Conclusions

Latent class analysis to build an AF risk model is feasible. Despite the heterogeneity in number and severity of risk factors between individuals at risk for AF, latent class analysis produces distinguishable groups.

SUBMITTER: Rienstra M

PROVIDER: S-EPMC5104331 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Cluster Individuals Based on Phenotype and Determine the Risk for Atrial Fibrillation in the PREVEND and Framingham Heart Study Populations.

Rienstra Michiel M Geelhoed Bastiaan B Yin Xiaoyan X Siland Joylene E JE Vermond Rob A RA Mulder Bart A BA Van Der Harst Pim P Hillege Hans L HL Benjamin Emelia J EJ Van Gelder Isabelle C IC

PloS one 20161110 11

<h4>Background</h4>Risk prediction of atrial fibrillation (AF) is of importance to improve the early diagnosis and treatment of AF. Latent class analysis takes into account the possible existence of classes of individuals each with shared risk factors, and maybe a better method of incorporating the phenotypic heterogeneity underlying AF.<h4>Methods and findings</h4>Two prospective community-based cohort studies from Netherlands and United States were used. Prevention of Renal and Vascular End-st ...[more]

PMID: 27832125

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Project description:BackgroundThere have been conflicting reported associations between dietary factors and incident atrial fibrillation (AF).ObjectiveWe evaluated associations between consumption of alcohol, caffeine, fiber, and polyunsaturated fatty acids (PUFAs) and incident AF in the Framingham Heart Study.DesignParticipants without AF (n = 4526; 9640 examinations; mean age: 62 y; 56% women) from the original and offspring cohorts completed food-frequency questionnaires and were followed prospectively for 4 y. We examined the associations between dietary exposures and AF with Cox proportional hazards regression.ResultsA total of 296 individuals developed AF (177 men, 119 women). In multivariable analyses, there were no significant associations between examined dietary exposures and AF risk. Hazard ratios (HRs) for increasing quartiles of dietary factors were as follows: for alcohol, 0.73 (95% CI: 0.5, 1.05), 0.85 (95% CI: 0.61, 1.18), and 1.12 (95% CI: 0.83, 1.51) (P for trend = 0.48); for caffeine, 0.84 (95% CI: 0.62, 1.15), 0.87 (95% CI: 0.64, 1.2), and 0.98 (95% CI: 0.7, 1.39) (P for trend = 0.84); for total fiber, 0.86 (95% CI: 0.61, 1.2), 0.64 (95% CI: 0.44, 0.92), and 0.81 (95% CI: 0.54, 1.2) (P for trend = 0.16); and for n-3 (omega-3) PUFAs, 1.11 (95% CI: 0.81, 1.54), 0.92 (95% CI: 0.65, 1.29), and 1.18 (95% CI: 0.85, 1.64) (P for trend = 0.57; quartile 1 was the reference group). In exploratory analyses, consumption of >4 servings of dark fish/wk (5 cases and 21 individuals at risk) was significantly associated with AF risk compared with the consumption of <1 serving of dark fish/wk (HR: 6.53; 95% CI: 2.65, 16.06; P < 0.0001).ConclusionsConsumption of alcohol, caffeine, fiber, and fish-derived PUFAs was not significantly associated with AF risk. The observed adverse association between the consumption of dark fish and AF merits further investigation. Our findings suggest that the dietary exposures examined convey limited attributable risk of AF in the general population.

Dataset Information

Cluster Individuals Based on Phenotype and Determine the Risk for Atrial Fibrillation in the PREVEND and Framingham Heart Study Populations.

Background

Methods and findings

Conclusions

Publications

Cluster Individuals Based on Phenotype and Determine the Risk for Atrial Fibrillation in the PREVEND and Framingham Heart Study Populations.

Similar Datasets

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