Weather data could warn of cardiac arrest risk several days in advance
Weather data could help predict up to three days in advance when the number of out-of-hospital cardiac arrests is likely to rise above average, according to a nationwide study of more than 114,000 cases by researchers from Semmelweis University, the Budapest University of Technology and Economics, and the Hungarian National Ambulance Service.
A recent study has uncovered that weather data may be able to predict an increase in out-of-hospital cardiac arrests up to three days before they occur. Researchers from Semmelweis University, the Budapest University of Technology and Economics, and the Hungarian National Ambulance Service analyzed over 114,000 cases in a nationwide study.
They discovered that lower temperatures emerged as a significant risk factor, with each 1°C drop in average temperature leading to a 1.4% increase in daily out-of-hospital cardiac arrest cases. Winter months saw nearly 18% more such events compared to summer. The study also found that temperature changes of more than 5°C daily could serve as warning signals.
While a single day's temperature drop may not immediately trigger an increase, the effects could manifest up to three days later. This delayed response suggests the potential for early warning systems that could alert ambulance services and hospitals to anticipate higher demand several days ahead of time. The predictive model developed by the researchers uses meteorological data to estimate the expected daily number of out-of-hospital cardiac arrests nationwide, rather than individual risk levels.
By combining meteorological and ambulance service data, the model can predict when case numbers are likely to exceed average, providing valuable information for planning and preparation.
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