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Risk of Atrial Fibrillation, Ischemic Stroke and Cognitive Impairment: Study of a Population Cohort ≥65 Years of Age

PURPOSE: To evaluate a model for calculating the risk of AF and its relationship with the incidence of ischemic stroke and prevalence of cognitive decline. MATERIALS AND METHODS: It was a multicenter, observational, retrospective, community-based study of a cohort of general population ≥6ct 35 years...

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Detalles Bibliográficos
Autores principales: Clua-Espuny, Jose-Luis, Muria-Subirats, Eulalia, Ballesta-Ors, Juan, Lorman-Carbo, Blanca, Clua-Queralt, Josep, Palà, Elena, Lechuga-Duran, Iñigo, Gentille-Lorente, Delicia, Bustamante, Alejandro, Muñoz, Miguel Ángel, Montaner, Joan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605602/
https://www.ncbi.nlm.nih.gov/pubmed/33149596
http://dx.doi.org/10.2147/VHRM.S276477
Descripción
Sumario:PURPOSE: To evaluate a model for calculating the risk of AF and its relationship with the incidence of ischemic stroke and prevalence of cognitive decline. MATERIALS AND METHODS: It was a multicenter, observational, retrospective, community-based study of a cohort of general population ≥6ct 35 years, between 01/01/2016 and 31/12/2018. Setting: Primary Care. Participants: 46,706 people ≥65 years with an active medical history in any of the primary care teams of the territory, information accessible through shared history and without previous known AF. Interventions: The model to stratify the risk of AF (PI) has been previously published and included the variables sex, age, mean heart rate, mean weight and CHA2DS2VASc score. Main measurements: For each risk group, the incidence density/1000 person/years of AF and stroke, number of cases required to detect a new AF, the prevalence of cognitive decline, Kendall correlation, and ROC curve were calculated. RESULTS: The prognostic index was obtained in 37,731 cases (80.8%) from lowest (Q1) to highest risk (Q4). A total of 1244 new AFs and 234 stroke episodes were diagnosed. Q3-4 included 53.8% of all AF and 69.5% of strokes in men; 84.2% of all AF and 85.4% of strokes in women; and 77.4% of cases of cognitive impairment. There was a significant linear correlation between the risk-AF score and the Rankin score (p < 0.001), the Pfeiffer score (p < 0.001), but not NIHSS score (p 0.150). The overall NNS was 1/19. CONCLUSION: Risk stratification allows identifying high-risk individuals in whom to intervene on modifiable risk factors, prioritizing the diagnosis of AF and investigating cognitive status.