Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals. (June 2020)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals. (June 2020)
- Main Title:
- Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals
- Authors:
- Yang, Mei
Zhou, Runze
Qiu, Xiangjun
Feng, Xiangfei
Sun, Jian
Wang, Qunshan
Lu, Qiufen
Zhang, Pengpai
Liu, Bo
Li, Wei
Chen, Mu
Zhao, Yan
Mo, Binfeng
Zhou, Xin
Zhang, Xi
Hua, Yingxue
Guo, Jin
Bi, Fangfang
Cao, Yajun
Ling, Feng
Shi, Shengming
Li, Yi-Gang - Abstract:
- Highlights: The correlation between PM2.5 and different arrhythmias was found in this study. The impact mode of PM2.5 for each type of arrhythmia was addressed in this study. This study was performed in Shanghai, a city with serious air pollution problem. The study was performed based on large-scale population data of over 200, 000 ECGs. Abstract: 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/m 3 during this period. Positive associations were evidenced between fine particulate matter level and prevalence of cardiacHighlights: The correlation between PM2.5 and different arrhythmias was found in this study. The impact mode of PM2.5 for each type of arrhythmia was addressed in this study. This study was performed in Shanghai, a city with serious air pollution problem. The study was performed based on large-scale population data of over 200, 000 ECGs. Abstract: 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/m 3 during this period. Positive associations were evidenced between fine particulate matter level and prevalence of cardiac arrhythmia by different lag models. Per 10 μg/m 3 increase in fine particulate matter was associated with a 0.584%(95%CI:0.346-0.689%, p < 0.001) increase of cardiac arrhythmia detected in these patient cohort at lag0-2. For different types of cardiac arrhythmias, an immediate arrhythmogenic effect of fine particulate matter (increase of the estimates of cardiac arrhythmia prevalence detected in daily outpatient visits) was found with paroxysmal supraventricular tachycardia; a lag effect was found with atrial fibrillation; and both immediate and lag effect was found with premature atrial contractions or atrial tachycardia, atrioventricular block. Moreover, the impact of fine particulate matter on cardiac arrhythmias was significantly greater in women (lag3 and lag0-4), and in people aged <65 years (lag0). Conclusion: Ambient exposure to fine particulate matter is linked with increased risk of arrhythmias in outpatients visiting Shanghai community hospitals, with an immediate or lag effect. The arrhythmogenic effect varies among different types of cardiac arrhythmias. … (more)
- Is Part Of:
- Environment international. Volume 139(2020)
- Journal:
- Environment international
- Issue:
- Volume 139(2020)
- Issue Display:
- Volume 139, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 139
- Issue:
- 2020
- Issue Sort Value:
- 2020-0139-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-06
- Subjects:
- Environmental protection -- Periodicals
Environmental health -- Periodicals
Environmental monitoring -- Periodicals
Environmental Monitoring -- Periodicals
Environnement -- Protection -- Périodiques
Hygiène du milieu -- Périodiques
Environnement -- Surveillance -- Périodiques
Environmental health
Environmental monitoring
Environmental protection
Periodicals
333.705 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01604120 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envint.2020.105745 ↗
- Languages:
- English
- ISSNs:
- 0160-4120
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.330000
British Library DSC - BLDSS-3PM
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