Literature DB >> 29967953

Seasonal variations of weather conditions on acute myocardial infarction onset: Oita AMI Registry.

Hidefumi Akioka1, Kunio Yufu2, Yasushi Teshima1, Kyoko Kawano1, Yumi Ishii1, Ichitaro Abe1, Hidekazu Kondo1, Shotaro Saito1, Akira Fukui1, Norihiro Okada1, Yasuko Nagano1, Tetsuji Shinohara1, Mikiko Nakagawa1, Masahide Hara1, Naohiko Takahashi1.   

Abstract

The onset of acute myocardial infarction (AMI) has been reportedly related to weather conditions. The aim of this study was to investigate the impact of weather conditions on AMI onset. Our study population consisted of 274 patients enrolled in the Oita AMI Registry who were admitted with AMI between June 2012 and May 2013. We divided the 365 days of the year into the four seasons: spring (March, April, May), summer (June, July, August), autumn (September, October, November), and winter (December, January, February). We classified each day as a day of onset of AMI (onset day) or a day of non-onset of AMI (non-onset day). Information on maximum temperature, minimum temperature, mean humidity, and mean atmospheric pressure was obtained from the Japan Meteorological Agency. In summer, the temperatures and intraday temperature differences were significantly lower on onset days than on non-onset days. Receiver operating characteristic analysis for predicting AMI onset in each season showed that the maximum temperature 2 days before AMI onset in summer had the largest area under the curve (AUC = 0.72, p = 0.0005). Our analysis demonstrated that there exist specific weather conditions that influence AMI onset in each season in Oita prefecture. AMI onset in summer was particularly associated with the maximum temperature 2 days before AMI onset.

Entities:  

Keywords:  Acute myocardial infarction; Oita AMI Registry; The maximum temperature 2 days before AMI onset; Weather conditions

Mesh:

Year:  2018        PMID: 29967953     DOI: 10.1007/s00380-018-1213-6

Source DB:  PubMed          Journal:  Heart Vessels        ISSN: 0910-8327            Impact factor:   2.037


  5 in total

1.  Prediction Model of Deep Learning for Ambulance Transports in Kesennuma City by Meteorological Data.

Authors:  Ohmi Watanabe; Norio Narita; Masahito Katsuki; Naoya Ishida; Siqi Cai; Hiroshi Otomo; Kenichi Yokota
Journal:  Open Access Emerg Med       Date:  2021-01-28

2.  Weather Impact on Acute Myocardial Infarction Hospital Admissions With a New Model for Prediction: A Nationwide Study.

Authors:  Chen-Yu Li; Po-Jui Wu; Chi-Jen Chang; Chien-Ho Lee; Wen-Jung Chung; Tien-Yu Chen; Chien-Hao Tseng; Chia-Chen Wu; Cheng-I Cheng
Journal:  Front Cardiovasc Med       Date:  2021-12-14

3.  Diagnosis of Cardiac Rehabilitation after Percutaneous Coronary Intervention in Acute Myocardial Infarction Patients by Emission Computed Tomography Image Features under Filtered Back Projection Reconstruction Algorithm.

Authors:  Yuan Lv; Suyu Zhao
Journal:  J Healthc Eng       Date:  2021-10-22       Impact factor: 2.682

Review 4.  The Impact of Meteorological Factors and Air Pollutants on Acute Coronary Syndrome.

Authors:  Andreea-Alexandra Rus; Cristian Mornoş
Journal:  Curr Cardiol Rep       Date:  2022-08-06       Impact factor: 3.955

5.  Acute myocardial infarction: Circadian, daily, monthly and seasonal patterns of occurrence in diabetics.

Authors:  Mohammad Rouzbahani; Javad Azimivghar; Reza Heidari Moghadam; Nafiseh Montazeri; Parisa Janjani; Alireza Rai; Etrat Javadi Rad; Arsalan Naderipour; Nahid Salehi
Journal:  J Diabetes Metab Disord       Date:  2021-05-20
  5 in total

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