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

Short-term exposure to ambient temperature variability and myocardial infarction hospital admissions: A nationwide case-crossover study in Sweden

BACKGROUND

Climate change threatens human health and general welfare via multiple dimensions. However, the associations of short-term exposure to temperature variability, a crucial aspect of climate change, with myocardial infarction (MI) hospital admissions remains unclear.

METHODS AND FINDINGS

This population-based nationwide study employed a time-stratified, case-crossover design to investigate the association between ambient temperature variability and MI hospital admissions among 233,617 patients recorded in the SWEDEHEART registry in Sweden between 2005 and 2019. High-resolution (1 × 1 km) daily mean ambient temperature was assigned to patients' residential areas. Temperature variability was calculated as the difference between the same-day (as the MI event) ambient temperature and the average temperature over the preceding 7 days. An upward temperature shift represents a rise in the current day's temperature relative to the 7-day average, while a downward temperature shift indicates a corresponding decrease. A conditional logistic regression model with distributed lag non-linear model was applied to estimate the association between ambient temperature variability and total MI (encompassing all MI types), ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) hospital admissions at lag 0-6 days. Potential effect modifiers, such as sex, history of diseases, and season, were also examined. The patients had an average age of 70.6 years, and 34.5% of them were female. Our study found that an upward temperature shift was associated with increased risks of total MI (encompassing all MI types), STEMI, and NSTEMI hospital admissions at lag 0 day, with odds ratios (OR, 95% confidence intervals [CIs]) of 1.009 (1.005, 1.013; p < 0.001), 1.014 (1.006, 1.022; p < 0.001), and 1.007 (1.001, 1.012; p = 0.014) per 1 °C increase, respectively. These associations attenuated and became non-significant over lags 1-6 days. Furthermore, a downward temperature shift was associated with increased risks of hospital admissions for total MI (encompassing all MI types) at a lag of 2 days with an OR (95% CI): 1.003 (1.001, 1.005; p = 0.014), and for STEMI at lags 2 and 3 days with ORs (95% CI): 1.006 (1.002, 1.010; p = 0.001) and 1.005 (1.001, 1.008; p = 0.011), per 1 °C decrease, respectively. Conversely, higher downward temperature shifts were associated with decreased risks of total MI (encompassing all MI types) and NSTEMI at lag 0 day. No significant associations were observed at other lag days for downward temperature shifts. Males and patients with diabetes had higher MI hospitalization risks from upward temperature shift exposure, while downward temperature shift exposure in cold seasons posed greater MI hospitalization risks. A methodological limitation was the use of ambient temperature variability as a proxy for personal exposure, which, while practical for large-scale studies, may not precisely reflect individual temperature exposure.

CONCLUSIONS

This nationwide study contributes insights that short-term exposures to higher temperature variability-greater upward or downward temperature shifts-are associated with an increased risk of MI hospitalization. Our finding highlights the cardiovascular health threats posed by higher temperature variability, which are anticipated to increase in frequency and intensity due to climate change.

Relationship between temperature and acute myocardial infarction: a time series study in Xuzhou, China, from 2018 to 2020

BACKGROUND

It is widely known that the incidence rate and short-term mortality of acute myocardial infarctions (AMIs) are generally higher during the winter months. The goal of this study was to determine how the temperature of the environment influences fatal acute myocardial infarctions in Xuzhou.

METHODS

This observational study used the daily meteorological data and the data on the cause of death from acute myocardial infarction in Xuzhou from January 1, 2018, to December 31, 2020. After controlling meteorological variables and pollutants, the distributed nonlinear lag model (DLNM) was used to estimate the correlation between temperature and lethal AMI.

RESULTS

A total of 27,712 patients with fatal AMI were enrolled. 82.4% were over the age of 65, and 50.9% were men. Relative to the reference temperature (15 ℃), the 30-day cumulative RRs of the extremely cold temperature (- 2 ℃) for the general population, women, and people aged 65 years and above were 4.66 (95% CI: 1.76, 12.30), 15.29 (95% CI: 3.94, 59.36), and 7.13 (95% CI: 2.50, 20.35), respectively. The 30-day cumulative RRs of the cold temperature (2 ℃) for the general population, women, and people aged 65 years and above were 2.55 (1.37, 4.75), 12.78 (2.24, 5.36), and 3.15 (1.61, 6.16), respectively. No statistically significant association was observed between high temperatures and the risk of fatal AMI. The influence of the cold effect (1st and 10th) was at its peak on that day, and the entire cold effect persisted for 30 days. Temperature extremes had an effect on the lag patterns of distinct age and gender stratifications.

CONCLUSION

According to this study, the risk of fatal AMI increases significantly in cold weather but not in hot weather. Women above the age of 65 are particularly sensitive to severe weather events. The influence of frigid weather on public health should also be considered.

Primary Prevention of Coronary and Other Cardiovascular Diseases: A Focused Review

In 2022, the Japan Atherosclerosis Society (JAS) updated its prevention guidelines, the "Japan Atherosclerosis Society (JAS) Guidelines for Prevention of Atherosclerotic Cardiovascular Diseases 2022" (JAS2022GL), expanding its scope from coronary artery disease (CAD) to atherosclerotic cardiovascular diseases (ASCVDs), including atherothrombotic stroke. The following year, the Japanese Circulation Society (JCS) updated its guidelines for primary prevention entitled "JCS 2023 Guideline on the Primary Prevention of Coronary Artery Disease" (JCS2023GL). Since those publications, scientific advancements in relevant fields have continued. This review article outlines the current recommendations provided by the guidelines, provides background information supporting these recommendations, introduces scientific findings subsequent to prior publications, and discusses future directions on select topics for the primary prevention of CVD. The topics covered in this review are traditional risk factors, including dyslipidemia and hypertension, the application of comprehensive risk stratification or risk scoring systems, patient-specific topics, salt and alcohol, and environmental factors. These topics were deliberate and selected by the authors, who were involved in the compilation of either or both JAS2022GL and JCS2023GL. This review not only emphasizes the pivotal role of continuously updated guidelines in shaping clinical practice but also stresses the urgent need for ongoing research to bridge existing knowledge and practice gaps.

Seasonal dynamics of myocardial infarctions in regions with different types of a climate: a meta-analysis

BACKGROUND

It is known that cardiovascular events (CVE) occur more often in winter than in summer. However, dependence of myocardial infarction (MI) risk of on various meteorological factors is still not fully understood. Also, the dependence of the seasonal dynamics of MI on gender and age has not yet been studied. The purpose of our meta-analysis is to reveal dependence of the circannual dynamics of MI hospitalizations on gender, age, and characteristics of a region's climate.

MAIN BODY

Using Review Manager 5.3, we performed a meta-analysis of 26 publications on the seasonal dynamics of MI. In our meta-analysis, the relative MI risk was higher in colder compared to warmer seasons. Old age insignificantly increased the seasonal MI risk; gender did not affect the seasonal dynamics of MI, but MI was more common in men than in women. The severity of the seasonal dynamics of MI risk depended on the climate of the region. In a climate with a small amplitude of circannual fluctuations in air temperature, atmospheric pressure, and partial oxygen density in the air, as well as in regions where air humidity is higher in winter than in summer, an increase in MI risk in winter compared to summer was significant. It was not significant in regions with opposite climatic tendencies.

CONCLUSIONS

Based on the results of our studies, it can be concluded that a decrease in air temperature increases in MI risk; in addition, hypoxia in the hot season can provoke CVE associated with ischemia.

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.

Incidence of cardiovascular events when watching intense football matches - sex differences

INTRODUCTION

FIFA World Cup represent one of the world's greatest phenomena. The spectators watch the matches of national teams with great emotional involvement. It is well documented fact that emotional stress can be a trigger of unwanted cardiovascular (CV) event.

AIM

The aim of this retrospective study was to determine whether there had been an increase in the number of the emergency admissions for CVD in the Emergency Room and Clinic for Cardiovascular Diseases of the Sestre milosrdnice University Hospital Centre during and after the matches that the Croatian national team played in the FIFA World Cup 2018.

METHODS

The hospital's database was examined for the dates when Croatia played its matches, plus two more days after each match. An unexposed period that included the same dates in 2017 and 2019 was formed.

RESULTS

1093 cases were assessed. The incidence of CV admissions during the exposed period was 1.15 (95% confidence interval [CI]; 1.02 to 1.31) times higher than during the unexposed period. There was a 1.30 (95% CI; 1.1 to 1.54) times higher incidence in women compared to the unexposed period. Arrhythmias and angina pectoris were the CVDs that occurred more frequently in the exposed period.

CONCLUSION

This study showed that watching Croatian national team's matches and cheering represented an additional risk for a CV incident, especially in women.

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

Introduction: Cardiovascular disease is one of the leading causes of mortality worldwide. Acute myocardial infarction (AMI) is associated with weather change. The study aimed to investigate if weather change was among the risk factors of coronary artery disease to influence AMI occurrence in Taiwan and to generate a model to predict the probabilities of AMI in specific weather and clinical conditions.

Method: This observational study utilized the National Health Insurance Research Database and daily weather reports from Taiwan Central Weather Bureau to evaluate the discharge records of patients diagnosed with AMI from various hospitals in Taiwan between January 1, 2008 and December 31, 2011. Generalized additive models (GAMs) were used to estimate the effective parameters on the trend of the AMI incidence rate with respect to the weather and health factors in the time-series data and to build a model for predicting AMI probabilities.

Results: A total of 40,328 discharges were listed. The minimum temperature, maximum wind speed, and antiplatelet therapy were negatively related to the daily AMI incidence; however, a drop of 1° when the air temperature was below 15°C was associated with an increase of 1.6% of AMI incidence. By using the meaningful parameters including medical and weather factors, an estimated GAM was built. The model showed an adequate correlation in both internal and external validation.

Conclusion: An increase in AMI occurrence in colder weather has been evidenced in the study, but the influence of wind speed remains uncertain. Our analysis demonstrated that the novel GAM model can predict daily onset rates of AMI in specific weather conditions.

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

This study aimed to explore the application value of emission computed tomography (ECT) imaging technology based on filtered back projection reconstruction algorithm (FBP) in cardiac function examination after percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI). Eighty patients with myocardial infarction diagnosed by medical history, electrocardiograph (ECG), and myocardial enzyme admitted to hospital from February 2018 to February 2019 were selected as the research objects. All patients underwent PCI seven days after the onset of myocardial infarction. ECT was performed for all patients before and after surgery. In addition, all ECT images were processed by the FBP reconstruction algorithm. On this basis, preoperative and postoperative cardiac surgery function and ischemia of the patients were diagnosed. Then, the diagnostic results were compared with the results of coronary angiography and echocardiogram. The results showed that all patients had a total of 541 segments before PCI surgery. ECT examination revealed 294 abnormal segments of the ventricular wall, with a total score of 585 points. A total of 100 segments were scored with 1 point, a total of 194 segments were scored with 2 points, and a total of 50 segments were scored with 3 points. After PCI, the number of abnormal segments was reduced to 58, with a total score of 193. There were 6 segments with a score of 1, 44 segments with a score of 2, and 5 segments with a score of 3. The left ventricular diastolic volume (EDV), left ventricular systolic volume (ESV), stroke volume (CO), and ejection fraction (EF) of the patients before the operation were 148 ± 16 mL, 77 ± 14.5 mL, 4.29 ± 0.37 L/min, and 41.9 ± 8%, respectively. The EDV, ESV, CO, and EF of the patients after surgery were 132 ± 16 mL, 62 ± 13 mL, 4.89 ± 0.71, and 53 ± 6%, respectively. Significant changes occurred in various systolic function parameters before and after surgery, P < 0.05. The standardized regression coefficients of the three groups were 0.32, 0.41, and 0.47, respectively, P < 0.05, which indicated that the greater the coronary artery stenosis rate, the higher the diagnostic coincidence rate of left anterior descending limb (LAD), left circumflex branch (LCX), and left coronary artery (RCA). The conformity of ECT imaging in the LCX group for diagnosis of myocardial ischemia was higher than that of UCG, P < 0.05. To sum up, the ECT technology based on the FBP reconstruction algorithm had a good application prospect in the diagnosis of cardiac function recovery in AMI patients after PCI.

Short-term effect of multi-pollutant air quality indexes and PM2.5 on cardiovascular hospitalization in Hamadan, Iran: a time-series analysis

Air pollutants are the most important environmental factors that contributed to cardiovascular disease (CVD). The present study aimed to investigate the number of hospitalization due to heart failure (HF) and myocardial infarction (MI) following the air pollutant exposure using a time-series regression analysis with a distributed lag model in Hamadan, Iran (2015-2019). A total of 2091 cases of CVD were registered. Based on the findings, the highest health effects on HF hospitalization were observed with air quality health index (AQHI) at lag 9 (RR = 1.043, 95% CI 0.991-1.098), and air quality index (AQI) at lags 2, 7, and 9 (RR = 1.001, 95% CI 0.998-1.002), for an increase in 1 unit of the indexes, and with PM_2.5 at lag 0 (RR = 1.001, 95% CI 0.996-1.004) for 10 μg/m³ increase in PM_2.5 levels. The highest health effects on MI hospitalization were calculated with AQHI at lag 10 (RR = 1.059, 95% CI 1.001-1.121) and AQI at lags 1 and 2 (RR = 1.001, 95% CI 0.998-1.002), for an increase in 1 unit of the indexes, and with PM_2.5 at lag 8 (RR = 1.002, 95% CI 0.997-1.005) for 10 μg/m³ increase in PM_2.5 levels. According to a seasonal classification, results showed that hospitalization in the warm season was higher than that of the cold season. Based on our knowledge, the current study is the first study that investigated the effect of air quality indexes on hospitalization due to HF and MI in Iran. Findings can provide basic information to plan preventive measures for reducing exposure chance and hospitalization rate in high-risk people.

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

BACKGROUND

Illustrating the temporal pattern of acute myocardial infarction (AMI), as a major cause of mortality, may help with disease prevention and better treatment. Therefore, the aim of our study was to investigate the circadian, daily, monthly and seasonal patterns of AMI occurrence in patients with diabetes mellitus, and other likely associated factors.

METHODS

This cross-sectional study was performed on 142 diabetic patients admitted to the Imam Ali cardiovascular hospital, Kermanshah, Iran with a diagnosis of ST-segment elevation myocardial infarction (STEMI) from March 2018 to February 2019. Data were collected using a checklist developed based on the study goals. One-way Analysis of Variance (ANOVA) and Chi-Square test (or Fishers҆ Exact test) were used to assess the differences between subgroups. Multiple logistic regression model was constructed to evaluate independent predictors of the AMI occurrence.

RESULT

Out of the 142 diabetic patients, 90 (63.4%) were male. The mean age of the patients was (mean ± SD) 62.81 ± 10.21 years. Occurrence of STEMI was the most common during winter (p = 0.001). Prior angina, prior congestive heart failure (CHF), prior stroke, High-density lipoprotein (HDL), and Creatine Phosphokinase (CPK) were significantly associated with seasonal pattern of STEMI (p-value < 0.05). Angiotensin receptor blockers (ARBs) use was associated with an increased odds of the AMI occurrence in winter (OR = 8.32; P = 0.027).

CONCLUSION

The present study of Iranian patients with diabetes revealed that AMI occurred more frequently during the winter compared to the other seasons. ARBs use was associated with an increased odd of the AMI occurrence in winter.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40200-021-00813-3.

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

PURPOSE

With the aging population in Japan, the prediction of ambulance transports is needed to save the limited medical resources. Some meteorological factors were risks of ambulance transports, but it is difficult to predict in a classically statistical way because Japan has 4 seasons. We tried to make prediction models for ambulance transports using the deep learning (DL) framework, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with the meteorological and calendarial variables.

MATERIALS AND METHODS

We retrospectively investigated the daily ambulance transports and meteorological data between 2017 and 2019. First, to confirm their association, we performed classically statistical analysis. Second, to test the DL framework's utility for ambulance transports prediction, we made 3 prediction models for daily ambulance transports (total daily ambulance transports more than 5 or not, cardiopulmonary arrest (CPA), and trauma) using meteorological and calendarial factors and evaluated their accuracies by internal cross-validation.

RESULTS

During the 1095 days of 3 years, the total ambulance transports were 5948, including 240 CPAs and 337 traumas. Cardiogenic CPA accounted for 72.3%, according to the Utstein classification. The relation between ambulance transports and meteorological parameters by polynomial curves were statistically obtained, but their r2s were small. On the other hand, all DL-based prediction models obtained satisfactory accuracies in the internal cross-validation. The areas under the curves obtained from each model were all over 0.947.

CONCLUSION

We could statistically make polynomial curves between the meteorological variables and the number of ambulance transport. We also preliminarily made DL-based prediction models. The DL-based prediction for daily ambulance transports would be used in the future, leading to solving the lack of medical resources in Japan.

Impact of Age on Gender Differences in the Acute Myocardial Infarction Onset–Weather Association ― Oita AMI Registry ―

Background: The onset of acute myocardial infarction (AMI) is related to weather conditions, but the impact of age on gender differences in the AMI onset–weather association has not been elucidated.

Methods and Results: We analyzed the Oita AMI Registry and obtained data for 403 enrolled patients. To examine the impact of age, we categorized the patients into 4 groups: young (age ≤65 years) women (n=20); young men (n=123); elderly (age >65 years) women (n=84); and elderly men (n=176). The analyzed meteorological factors were maximum and minimum temperature, intraday temperature difference, average humidity, and average atmospheric pressure. The young women group had a higher minimum temperature (17.7±5.7℃ vs. 13.8±8.2℃, P=0.04), lower intraday temperature difference (7.0±2.6℃ vs. 8.4±2.9℃, P=0.03), higher average humidity (74.5±12.1% vs. 68.1±12.0%, P=0.03), and lower average atmospheric pressure (1,009.5±5.0 hPa vs. 1,012.9±5.8 hPa, P=0.01) than the young men group on the onset day. In the elderly groups, there was no significant difference in meteorological variables except for the intraday temperature difference 2 days before AMI onset.

Conclusions: AMI onset appears to be more sensitive to weather conditions (i.e., minimum temperature, average atmospheric pressure, and average humidity) in young patients than in elderly patients. In particular, young women had AMI on days with low intraday temperature difference and high humidity relative to men.

Meteorological and chronobiological factors and the occurrence of acute aortic dissection

Although a number of studies have demonstrated seasonal variations in acute cardiovascular events, the association between winter and low temperatures and the incidence rate of acute aortic dissection has not been fully elucidated. In this study, we investigated the association between meteorological and chronobiological factors and the occurrence of acute aortic dissection classified by the Stanford type, sex and age. We retrospectively collected 131 patients who had been admitted consecutively to our institution with acute aortic dissection, including 58 type A patients and 73 type B patients, from January 2013 to December 2017. The meteorological data were downloaded from the homepage of the Japan Meteorological Agency. The daily incidence of aortic dissection was higher in winter (10.2%) than in fall (5.3%) (P = 0.04), and a significant winter peak was also observed in the sub-groups of males and type B, while there were no significant differences in the proportions of type A, female, and ≤ 70- and > 70-year-old patients. The maximum, mean and minimum temperatures on the days with aortic dissection were significantly lower than on the days without aortic dissection. Divided into four seasons, lower temperatures were found only in spring. The most significant and greatest difference was observed between the maximum temperature on the day of aortic dissection and that at 2 days earlier. The multivariate logistic regression analysis showed that the difference in the maximum temperature between the day of and 2 days before the incident (odds ratio 0.91; 95% confidence interval 0.87-0.96; P < 0.01) as well as the maximum temperature (odds ratio 0.97; 95% confidence interval 0.95-0.99; P = 0.02) were significantly associated with the incidence of aortic dissection. Cold weather and a sudden decrease in temperature might trigger aortic dissection, although the influence might differ among sub-groups.

Weather fluctuations: predictive factors in the prevalence of acute coronary syndrome

Background: Meteorological parameters and seasonal changes can play an important role in the occurrence of acute coronary syndrome (ACS). However, there is almost no evidence on a national level to suggest the associations between these variables and ACS in Iran. We aim to identify the meteorological parameters and seasonal changes in relationship to ACS.

Methods: This retrospective cross-sectional study was conducted between 03/19/2015 to 03/18/2016 and used documents and records of patients with ACS in Mazandaran ProvinceHeart Center, Iran. The following definitive diagnostic criteria for ACS were used: (1) existence of cardiac enzymes (CK or CK-MB) above the normal range; (2) Greater than 1 mm ST-segment elevation or depression; (3) abnormal Q waves; and (4) manifestation of troponin enzyme in the blood. Data were collected daily, such as temperature (Celsius) changes, wind speed and its direction, rainfall, daily evaporation rate; number of sunny days, and relative humidity were provided by the Meteorological Organization of Iran.

Results: A sample of 2,054 patients with ACS were recruited. The results indicated the highest ACS events from March to May. Generally, wind speed (18 PM) [IRR = 1.051 (95% CI: 1.019 to1.083), P=0.001], daily evaporation [IRR = 1.039 (95% CI: 1.003 to 1.077), P=0.032], daily maximum (P<0.001) and minimum (P=0.003) relative humidity was positively correlated withACS events. Also, negatively correlated variables were daily relative humidity (18 PM) [IRR =0.985 (95% CI: 0.978 to 0.992), P<0.001], and daily minimum temperature [IRR = 0.942 (95%CI: 0.927 to 0.958), P<0.001].

Conclusion: Climate changes were found to be significantly associated with ACS; especially from cold weather to hot weather in March, April and May. Further research is needed to fully understand the specific conditions and cold exposures.