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Next week’s weather forecast: cloudy, cold, with a chance of cardiac arrest
  1. David Foster Gaieski
  1. Emergency Medicine, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA 19107, USA
  1. Correspondence to Dr David Foster Gaieski, Emergency Medicine, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA 19107, USA; david.gaieski{at}jefferson.edu

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The relationship between lower ambient temperature and increased incidence of cardiovascular events, including myocardial infarction and cardiac arrest, has been demonstrated in a number of previous retrospective observational studies. For example, Arntz et al examined 5 years of consecutive cardiac arrests occurring in (West) Berlin between 1987 and 1991 and found that the incidence was 18.7% higher during the winter months when using summer months as the comparator.1 This increase was most pronounced in people aged over 65 years. In the warmer climate of Los Angeles, Kloner et al found similar results, with the highest incidence of cardiac arrest and coronary death occurring in December and January and the lowest between June and September.2 Interestingly, they also noted that the highest incidence occurred around the end-of-year holidays and acknowledged that this could not be explained by meteorological factors alone. They posited that overindulgence and holiday-related stress may be contributing factors. These descriptive data suggest that the occurrence of emergency coronary events including cardiac arrest is the end result of a complex network of factors including patient predisposition, age, weather, stress, overindulgence and physical exertion. A deeper understanding of this matrix may lead to improved prevention, allocation of resources and timely treatment of cardiovascular emergencies.

Advancing research along these lines, in ‘A machine learning model for predicting the out-of-hospital cardiac arrest using meteorological data,’ Nakashima et al 3 employ a novel approach to predict the incidence of out-of-hospital cardiac arrest (OHCA) in Japan. The analysis combines data from the All-Japan Utstein Registry of OHCA cases with high-resolution meteorological and chronological data to predict daily OHCA incidence based on weather patterns. The cardiac arrests …

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Footnotes

  • Contributors DFG is the sole author responsible for writing, editing and integrity of the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Commissioned; externally peer reviewed.

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