Literature DB >> 32334122

Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals.

Mei Yang1, Runze Zhou2, Xiangjun Qiu3, Xiangfei Feng1, Jian Sun1, Qunshan Wang1, Qiufen Lu1, Pengpai Zhang1, Bo Liu1, Wei Li1, Mu Chen1, Yan Zhao1, Binfeng Mo1, Xin Zhou4, Xi Zhang4, Yingxue Hua5, Jin Guo6, Fangfang Bi7, Yajun Cao8, Feng Ling9, Shengming Shi10, Yi-Gang Li11.   

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/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 < 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.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

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Year:  2020        PMID: 32334122     DOI: 10.1016/j.envint.2020.105745

Source DB:  PubMed          Journal:  Environ Int        ISSN: 0160-4120            Impact factor:   9.621


  4 in total

1.  ECG Utilization Patterns of Patients With Arrhythmias During COVID-19 Epidemic and Post-SARS-CoV-2 Eras in Shanghai, China.

Authors:  Cheng Li; Mu Chen; Mohan Li; Haicheng Wang; Xiangjun Qiu; Xiaoliang Hu; Qunshan Wang; Jian Sun; Mei Yang; Yuling Zhu; Peng Liao; Baohong Zhou; Min Chen; Xia Liu; Yuelin Zhao; Mingzhen Shen; Jinkang Huang; Li Luo; Hong Wu; Yi-Gang Li
Journal:  Front Cardiovasc Med       Date:  2022-04-27

2.  Numerical calculation and analysis of filtration performance of an effective novel structural fiber for PM2.5.

Authors:  Hui Yang; Hui Zhu; Haiming Fu
Journal:  PLoS One       Date:  2020-10-22       Impact factor: 3.240

Review 3.  Cardiac monitoring for patients with palpitations.

Authors:  Jaume Francisco-Pascual; Javier Cantalapiedra-Romero; Jordi Pérez-Rodon; Begoña Benito; Alba Santos-Ortega; Jenson Maldonado; Ignacio Ferreira-Gonzalez; Nuria Rivas-Gándara
Journal:  World J Cardiol       Date:  2021-11-26

Review 4.  How machine learning is impacting research in atrial fibrillation: implications for risk prediction and future management.

Authors:  Ivan Olier; Sandra Ortega-Martorell; Mark Pieroni; Gregory Y H Lip
Journal:  Cardiovasc Res       Date:  2021-06-16       Impact factor: 10.787

  4 in total

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