Analysis of Seasonal Variations in The Incidence of Primary Acute Cerebral Infarction
10.3969/j.issn.0253-9896.2014.04.023
- VernacularTitle:初发急性脑梗死的时间序列研究
- Author:
Peilin LIU
;
Lin WANG
;
Xin LI
;
Xiaoshuang XIA
;
Juanjuan XUE
- Publication Type:Journal Article
- Keywords:
acute cerebral infarction;
primary;
time variations;
seasonal variation;
monthly variation;
weekly variation
- From:
Tianjin Medical Journal
2014;(4):370-373
- CountryChina
- Language:Chinese
-
Abstract:
Objective Investigating the relationship between the incidence of Primary Acute Cerebral Infarction (PACI) and seasonal variation to employ measures to prevent PACI with climate change. Methods A retrospective analysis of patients diagnosed with PACI between 2009 and 2013 in the department of Neurology of Second hospital of Tian Jin Medi-cal University (n=1 198 patients) was carried out. Combined with the general clinical data, we analyzed seasonal, monthly and weekly variation among PACI incidents. Results The incidence of PACI increases over years between 2009 to 2013 (P ＜ 0.01). Significant difference of incidents of PACI was observed between each season (P=0.047). Incidence of PACI peaked in winter(30.33 ± 9.63/month), while bottomed in spring(21.83 ± 5.36/month). Significant difference of incidents of PACI was also observed between each months(P=0.010). The monthly incidence was highest in January and February (33.25 ± 9.62/month)and lowest in March and April(20.75 ± 4.89/month). The seasonal variation was only found in the pa-tients who are complicated with pulmonary infection (P＜0.01) regardless of the presence or absence of other risk factors, such as smoking, drinking ,hypertension, coronary heart disease, and diabetes mellitus. The weekly variation of PACI was on-ly significant in patients younger than 65 years old(P=0.043). The peak incidence among a week was Monday(17.86%),and incidence bottomed on Friday (13.36%). Conclusion Our study revealed that the incidence of PACI increase over year be-tween 2009 to 2013 and it shew a characteristic variation with respect to season, month and week. Based on these results, we can formulate prevention measures accordingly.
