Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals
التفاصيل البيبلوغرافية
العنوان:
Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals
Background: Recently, the impact of fine particulate matter pollution on cardiovascular system is drawing considerable concern worldwide. The association between ambient fine particulate and the cardiac arrhythmias is not clear now. Objective: To study associations of ambient fine particulate with incidence of arrhythmias in outpatients. Methods: Data was collected from the remote electrocardiogram (ECG) system covering 282 community hospitals in Shanghai from June 24th, 2014 to June 23rd, 2016. ECG was performed for patients admitted to above hospitals with complaining of chest discomfort or palpitation, or for regular check-ups. Air quality data during this time period was obtained from China National Environment Monitoring Center. A generalized additive quasi-Poisson model was established to examine the associations between PM2.5 and cardiac arrhythmias. Results: Cardiac arrhythmias were detected in 202,661 out of 1,016,579 outpatients (19.9%) and fine particulate matter ranged from 6 to 219 μg/m3 during this period. Positive associations were evidenced between fine particulate matter level and prevalence of cardiac arrhythmia by different lag models. Per 10 μg/m3 increase in fine particulate matter was associated with a 0.584%(95%CI:0.346-0.689%, p
