z-logo
open-access-imgOpen Access
Early Detection of Atrial Fibrillation in Community Pharmacies—CRIFAFARMA Study
Author(s) -
María González Valdivieso,
Domingo OrozcoBeltrán,
Adriana LópezPineda,
Vicente Gil-Guillén,
José A. Quesada,
Concepción CarrataláMunuera,
Rauf Nouni-García
Publication year - 2022
Publication title -
journal of cardiovascular pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.787
H-Index - 50
eISSN - 1940-4034
pISSN - 1074-2484
DOI - 10.1177/10742484221078973
Subject(s) - medicine , dyslipidemia , atrial fibrillation , stroke (engine) , diabetes mellitus , logistic regression , population , observational study , disease , physical therapy , environmental health , mechanical engineering , engineering , endocrinology
Background: Atrial fibrillation (AF) is the most common arrhythmia to appear in clinical practice. People with AF have 5 times the risk of stroke compared to the general population.Objective: This study aimed to determine the prevalence of AF in people over the age of 50 without known AF, who presented to a community pharmacy to check their cardiovascular risk factors, to identify risk factors associated with AF, and to assess the risk of stroke in people who screened positive for AF.Methods: A multicenter observational descriptive study of a screening program took place from May to December 2016. A blood pressure monitor (Microlife Watch BP Home) was used to screen for AF, and the CHA2DS2-VASc questionnaire was used to assess stroke risk.Results: The study included 452 adults over the age of 50. The CRIFAFARMA study detected a prevalence of AF of 9.1%. Risk factors for AF were: age of 75 years or older ( P = .024), lack of physical activity ( P = .043), diabetes ( P < .001), dyslipidemia ( P = .003), and history of cardiovascular disease ( P = .003). Diabetes (OR 2.79, P = .005) and dyslipidemia (OR 2.16, P = .031) had a combined explanatory capacity in the multivariable logistic regression model adjusted for age. 85% were at high risk of stroke according to the CHA2DS2-VASc scale.Conclusions: AF was detected in more than 9% of the included population. Factors associated with AF were advanced age, lack of physical activity, diabetes, dyslipidemia, and history of cardiovascular disease, with diabetes and dyslipidemia standing out as the factors with independent explanatory capacity.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom