Higher Frequency of Atrial Fibrillation Linked to Colder Seasons and Air Temperature on the Day of Ischemic Stroke Onset

• Published in: Journal of stroke and cerebrovascular diseases Vol. 22; no. 4; pp. 476 - 481
• Main Authors: Fustinoni, Osvaldo, MD, Saposnik, Gustavo, MD, MSc, FAHA, Esnaola y Rojas, María Martha, MD, Lakkis, Susan G., PhD, Sposato, Luciano A., MD, MBA, FAHA
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.05.2013
• Subjects: Aged; Aged, 80 and over; Argentina - epidemiology; atrial fibrillation; Atrial Fibrillation - diagnosis; Atrial Fibrillation - epidemiology; Brain Ischemia - diagnosis; Brain Ischemia - epidemiology; Cardiovascular; Chi-Square Distribution; Cold Temperature; Humans; Ischemic stroke; Logistic Models; Middle Aged; Neurology; Odds Ratio; Registries; risk; Risk Assessment; Risk Factors; season; Seasons; Stroke - diagnosis; Stroke - epidemiology; temperature; Time Factors; weather; Argentina; temperature; weather; season; atrial fibrillation; risk; Ischemic stroke
• ISSN: 1052-3057; 1532-8511
• DOI: 10.1016/j.jstrokecerebrovasdis.2013.03.009

Background Whether a seasonal variation of atrial fibrillation among acute ischemic stroke (AIS) patients occurs is unknown. We studied the distribution of atrial fibrillation across seasons and air temperatures in a cohort of AIS patients. Methods We selected 899 AIS patients from the Argentinean Stroke Registry (ReNACer), who were admitted to 43 centers in the Province of Buenos Aires. We recorded the minimum and maximum temperatures at local weather centers on the day and the city where each stroke occurred. We used the goodness-of-fit χ2 test to assess the distribution of atrial fibrillation across seasons and air temperatures and the Pearson correlation coefficient to assess the relationship between these variables. We developed a regression model for testing the association between seasons and atrial fibrillation. Results We found a seasonal variation in the occurrence of atrial fibrillation, with a peak in winter and a valley in summer (23.1% versus 14.0%, P  < .001). The semester comprised by autumn and winter was associated with atrial fibrillation (Pearson P  < .001). Atrial fibrillation showed a nonhomogeneous distribution across ranges of temperature ( P  < .001, goodness-of-fit test), with a peak between 5°C and 9°C, and was associated with minimum (Pearson P = .042) and maximum (Pearson P  = .002) air temperature. After adjusting for significant covariates, there was a 2-fold risk of atrial fibrillation during autumn and winter. Conclusions In this cohort of AIS patients, atrial fibrillation showed a seasonal variation and a nonhomogeneous distribution across air temperatures, with peaks in cold seasons and low temperatures on the day of stroke onset.