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

Autor: Hans L. Hillege, Bastiaan Geelhoed, Rob A. Vermond, Xiaoyan Yin, Bart A. Mulder, Pim van der Harst, Michiel Rienstra, Isabelle C. Van Gelder, Emelia J. Benjamin, Joylene E. Siland
Přispěvatelé: Cardiovascular Centre (CVC), Faculteit Medische Wetenschappen/UMCG, Life Course Epidemiology (LCE), Groningen Kidney Center (GKC)
Rok vydání: 2016
Předmět:
Male
PROGNOSIS
Physiology
Myocardial Infarction
lcsh:Medicine
Blood Pressure
030204 cardiovascular system & hematology
Vascular Medicine
Biochemistry
0302 clinical medicine
Framingham Heart Study
Endocrinology
Risk Factors
Atrial Fibrillation
Medicine and Health Sciences
Cluster Analysis
030212 general & internal medicine
Prospective Studies
10. No inequality
Prospective cohort study
lcsh:Science
Netherlands
Multidisciplinary
Incidence (epidemiology)
Incidence
Atrial fibrillation
Middle Aged
Latent class model
Phenotype
Cohort
Female
ASSOCIATION CONSENSUS CONFERENCE
Arrhythmia
Cohort study
Research Article
Adult
Endocrine Disorders
Cardiology
Excretion
Disease cluster
03 medical and health sciences
Albumins
medicine
Diabetes Mellitus
Humans
COHORT
Heart Failure
business.industry
lcsh:R
Health Risk Analysis
Biology and Life Sciences
Proteins
medicine.disease
United States
Health Care
Metabolic Disorders
lcsh:Q
business
Physiological Processes
LATENT CLASS ANALYSIS
Demography
Follow-Up Studies
Zdroj: PLoS ONE
PLoS ONE, 11(11):e0165828. PUBLIC LIBRARY SCIENCE
PLoS ONE, Vol 11, Iss 11, p e0165828 (2016)
ISSN: 1932-6203
Popis: 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% (pCONCLUSIONS: 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.
Databáze: OpenAIRE
Externí odkaz: