The Effects of Acute Atmospheric Pressure Changes on the Occurrence of ST-Elevation Myocardial Infarction: A Case-Crossover Study

Influence of daily temperature on the occurrence of ST-elevation myocardial infarction

BACKGROUND

Epidemiological studies reported that acute myocardial infarction (AMI) occurs more often in winter season or days with low temperatures. However, most of these studies did not distinguish ST-elevation myocardial infarction (STEMI) from AMI. The purpose of this study was to investigate the relationship between temperature and the occurrence of STEMI.

METHODS

We reviewed all daily temperature in Saitama City between January 2015 and December 2021 (2557 days) and divided them into days in which our institution received STEMI (days with STEMI) and days in which our institution did not receive STEMI (days without STEMI).

RESULTS

The daily maximum temperature was significantly lower in days with STEMI than in days without STEMI [20.0 °C (68.0 °F) versus 21.2 °C (70.2 °F), p = 0.001]. The maximum temperature was significantly lower in days with STEMI than in days without STEMI in the elderly [19.9 °C (67.8 °F) versus 21.1 °C (70.0 °F), p = 0.003], whereas this trend was weaker in the non-elderly [20.2 °C (68.4 °F) versus 20.9 °C (69.6 °F), p = 0.171]. Furthermore, the maximum temperature was significantly lower in days with STEMI than in days without STEMI in male [20.0 °C (68.0 °F) versus 21.1 °C (70.0 °F), p = 0.002], whereas this trend was weaker in females [20.0 °C (68.0 °F) versus 20.9 °C (69.6 °F), p = 0.169].

CONCLUSIONS

The daily temperatures were significantly lower in days with STEMI than in days without STEMI, and this relationship was pronounced in elderly or male patients.

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

Purpose of Review

Several studies have found that air pollution and climate change can have an impact on acute coronary syndromes (ACS), the leading cause of death worldwide. We synthesized the latest information about the impact of air pollution and climate change on ACS, the latest data about the pathophysiological mechanisms of meteorological factors and atmospheric pollutants on atherosclerotic disease, and an overall image of air pollution and coronary heart disease in the context of the COVID-19 pandemic.

Recent Findings

The variation of meteorological factors in different seasons increased the risk of ACS. Both the increase and the decrease in apparent temperature were found to be risk factors for ACS admissions. It was also demonstrated that exposure to high concentrations of air pollutants, especially particulate matter, increased cardiovascular morbidity and mortality.

Summary

Climate change as well as increased emissions of air pollutants have a major impact on ACS. The industrialization era and the growing population cause a constant increase in air pollution worldwide. Thus, the number of ACS favored by air pollution and the variations in meteorological factors is expected to increase dramatically in the next few years.

Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence

Background

The prediction of the number of acute coronary syndromes (ACSs) based on the weather conditions in the individual climate zones is not effective. We sought to investigate whether an artificial intelligence system might be useful in this prediction.

Methods

Between 2008 and 2018, a total of 105,934 patients with ACS were hospitalized in Lesser Poland Province, one covered by two meteorological stations. The predicted daily number of ACS has been estimated with the Random Forest machine learning system based on air temperature (°C), air pressure (hPa), dew point temperature (Td) (°C), relative humidity (RH) (%), wind speed (m/s), and precipitation (mm) and their daily extremes and ranges derived from the day of ACS and from 6 days before ACS.

Results

Of 840 pairwise comparisons between individual weather parameters and the number of ACS, 128 (15.2%) were significant but weak with the correlation coefficients ranged from −0.16 to 0.16. None of weather parameters correlated with the number of ACS in all the seasons and stations. The number of ACS was higher in warm front days vs. days without any front [40 (29–50) vs. 38 (27–48), respectively, P < 0.05]. The correlation between the predicted and observed daily number of ACS derived from machine learning was 0.82 with 95% CI of 0.80–0.84 (P < 0.001). The greatest importance for machine learning (range 0–1.0) among the parameters reached Td daily range with 1.00, pressure daily range with 0.875, pressure maximum daily range with 0.864, and RH maximum daily range with 0.853, whereas among the clinical parameters reached hypertension daily range with 1.00 and diabetes mellitus daily range with 0.28. For individual seasons and meteorological stations, the correlations between the predicted and observed number of ACS have ranged for spring from 0.73 to 0.77 (95% CI 0.68–0.82), for summer from 0.72 to 0.76 (95% CI 0.66–0.81), for autumn from 0.72 to 0.83 (95% CI 0.67–0.87), and for winter from 0.76 to 0.79 (95% CI 0.71–0.83) (P < 0.001 for each).

Conclusion

The weather parameters have proven useful in predicting the prevalence of ACS in a temperate climate zone for all the seasons, if analyzed with an artificial intelligence system. Simultaneously, the analysis of individual weather parameters or frontal scenarios has provided only weak univariate relationships. These findings will require validation in other climatic zones.

Associations of apparent temperature with acute cardiac events and subtypes of acute coronary syndromes in Beijing, China

Limited evidence is available on apparent temperature (AT) and hospital admissions for acute cardiac events. We examined the associations of AT with admissions for acute cardiac events and acute coronary syndrome (ACS), and explored the effect difference between ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction ACS (NSTE-ACS). Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-admission associations. Stratified analyses were performed by gender and age-groups for acute cardiac events. A total of 11,657 acute cardiac events admissions were collected from hospital-based chest pain centers in Beijing, during 2017-2019. The single day effect of low AT (- 11 °C, 2.5th percentile) appeared on the 2nd day and persisted until the 11th day, with estimated relative risk (RR) ranging from 1.44 (95% CI: 1.159, 1.790) to 1.084 (95% CI: 1.022, 1.150) for acute cardiac events and from 1.034 (95% CI: 1.010, 1.059) to 1.006 (95% CI: 1.000, 1.011) for ACS. The single day effect of high AT (34 °C, 97.5th percentile) was only observed on the current day. The cold effect on acute cardiac events was more pronounced among female and older patients. The cumulative effect of high AT on STEMI admissions and low AT on NSTE-ACS reached a peak RR peak of 2.545 (95% CI: 1.016, 6.375) and 3.71 (95% CI: 1.315, 10.469) on lag 0-6 days, respectively. Both high and low ATs were associated with increased risk of acute cardiac events and ACS admissions. STEMI admissions may be more sensitive to high AT while NSTE-ACS to low AT.

Transient increase in blood thrombogenicity may be a critical mechanism for the occurrence of acute myocardial infarction

Although the mechanism for the occurrence of acute myocardial infarction (MI) has been investigated by many pathological and clinical studies, it has not been adequately clarified yet. Although the disruption of vulnerable plaque is a well-known cause of acute MI, there are many silent plaque disruptions detected in the coronary artery by intravascular imaging studies. Therefore, many vulnerable plaques may disrupt and heal without causing acute MI. Some additional mechanisms other than the disruption of vulnerable plaque would be essential for the onset of acute MI. On the other hand, blood thrombogenicity would change dynamically due to circadian rhythms and many other factors. The combination of plaque and blood thrombogenicity would play an important and determinant role for the onset of acute MI.