Interplay between climate, pollution and COVID-19 on ST-elevation myocardial infarction in a large metropolitan region

BACKGROUND

Collective risk factors such as climate and pollution impact on the risk of acute cardiovascular events, including ST-elevation myocardial infarction (STEMI). There is limited data however on the precise temporal and independent association between these factors and STEMI, and the potentially interacting role of government policies against Coronavirus disease 2019 (COVID-19), especially for Latin America.

METHODS

We retrospectively collected aggregate data on daily STEMI admissions at 10 tertiary care centers in the Buenos Aires metropolitan area, Argentina, from January 1, 2017 to November 30, 2020. Daily measurements for temperature, humidity, atmospheric pressure, wind direction, wind speed, and rainfall, as well as carbon monoxide (CO), nitrogen dioxide, and particulate matter <10 µm (PM10), were retrieved. Exploratory analyses focused on key COVID-19-related periods (e.g. first case, first lockdown), and Stringency Index quantifying the intensity of government policy response against COVID-19.

RESULTS

A total of 1498 STEMI occurred over 1430 days, for an average of 0.12 STEMI per center (decreasing from 0.130 in 2018 to 0.102 in 2020, P=0.016). Time series analysis showed that lower temperature and higher concentration of CO and PM10 were all significantly associated with an increased rate of STEMI (all P<0.05), whereas COVID-19 outbreak, lockdown, and stringency of government policies were all inversely associated with STEMI (all P<0.05). Notably, environmental features impacted as early as 28 days before the event (all P<0.05), even if same or prior day associations proved stronger (all P<0.05). Multivariable analysis suggested that maximum temperature (P=0.001) and PM10 (P=0.033) were the strongest predictor of STEMI, even after accounting for COVID-19-related countermeasures (P=0.043).

CONCLUSIONS

Lower temperature and higher concentrations of CO and PM10 are associated with significant increases in the rate of STEMI in a large Latin American metropolitan area. The reduction in STEMI cases seen during the COVID-19 pandemic is at least in part mediated by improvements in pollution, especially reductions in PM10.

Cluster analysis of weather and pollution features and its role in predicting acute cardiac or cerebrovascular events

BACKGROUND

Despite mounting evidence, the impact of the interplay between weather and pollution features on the risk of acute cardiac and cerebrovascular events has not been entirely appraised. The aim of this study was to perform a comprehensive cluster analysis of weather and pollution features in a large metropolitan area, and their association with acute cardiac and cerebrovascular events.

METHODS

Anonymized data on acute myocardial infarction (AMI) and acute cerebrovascular events were obtained from 3 tertiary care centers from a single large metropolitan area. Weather and pollution data were obtained averaging measurements from several city measurement stations managed by the competent regional agency for enviromental protection, and from the Metereological Center of Italian Military Aviation. Unsupervised machine learning was performed with hierarchical clustering to identify specific days with distinct weather and pollution features. Clusters were then compared for rates of acute cardiac and cerebrovascular events with Poisson models.

RESULTS

As expected, significant pairwise correlations were found between weather and pollution features. Building upon these correlations, hierarchical clustering, from a total of 1169 days, generated 4 separate clusters: mostly winter days with low temperatures and high ozone concentrations (cluster 1, N.=60, 5.1%), days with moderately high temperatures and low pollutants concentrations (cluster 2, N.=419, 35.8%), mostly summer and spring days with high temperatures and high ozone concentrations (cluster 3, N.=673, 57.6%), and mostly winter days with low temperatures and low ozone concentrations (cluster 4, N.=17, 1.5%). Overall cluster-wise comparisons showed significant differences in adverse cardiac and cerebrovascular events (P<0.001), as well as in cerebrovascular events (P<0.001) and strokes (P=0.001). Between-cluster comparisons showed that cluster 1 was associated with an increased risk of any event, cerebrovascular events, and strokes in comparison to cluster 2, cluster 3 and cluster 4 (all P<0.05), as well as AMI in comparison to cluster 3 (P=0.047). In addition, cluster 2 was associated with a higher risk of strokes in comparison to cluster 4 (P=0.030). Analysis adjusting for season confirmed the increased risk of any event, cerebrovascular events and strokes for cluster 1 and cluster 2.

CONCLUSIONS

Unsupervised machine learning can be leveraged to identify specific days with a unique clustering of adverse weather and pollution features which are associated with an increased risk of acute cardiovascular events, especially cerebrovascular events. These findings may improve collective and individual risk prediction and prevention.

Reduction in emergency access for acute myocardial infarction during the COVID-19 pandemic: a survey from the greater area of Rome

BACKGROUND

On March 9, 2020, the Italian government imposed a national lockdown to tackle the COronaVIrus Disease 19 (COVID-19) pandemic, including stay at home recommendations. The precise impact of COVID-19 scare and lockdown on emergency access for acute myocardial infarction (MI) is still subject to debate.

METHODS

Data on all patients undergoing invasive coronary angiography at 9 hospitals in the greater area of Rome, Italy, between February 19, 2020 and March 29, 2020 were retrospectively collected. Incidence of ST-elevation MI (STEMI), and non-ST-elevation MI (NSTEMI), as well as corresponding percutaneous coronary intervention (PCI), was compared distinguishing two different 20-day time periods (before vs. on or after March 10, 2020).

RESULTS

During the study period, 1068 patients underwent coronary angiography, 142 (13%) with STEMI and 169 (16%) with NSTEMI. The average daily number of STEMI decreased from 4.3 before the lockdown to 2.9 after the lockdown (P=0.021). Similarly, the average daily number of NSTEMI changed from 5.0 to 3.5 (P=0.028). The average daily number of primary PCI changed from 4.2 to 2.9 (P=0.030), while the average daily number of PCI for NSTEMI changed from 3.5 to 2.5 (P=0.087). For STEMI patients, the time from symptom onset to hospital arrival (onset-to-door time less than three hours) showed a significant increase after the lockdown (P=0.018), whereas door-to-balloon time did not change significantly from before to after the lockdown (P=0.609).

CONCLUSIONS

The present study, originally reporting on the trends in STEMI and NSTEMI in the Rome area, highlights that significant decreases in the incidence of both acute coronary syndromes occurred between February 19, 2020 and March 29, 2020, together with increases in time from symptom onset to hospital arrival, luckily without changes in door-to-balloon time.

Excess all-cause mortality during COVID-19 outbreak: potential role of untreated cardiovascular disease

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has rapidly spread globally. Due to different testing strategies, under-detection of positive subjects and COVID-19-related-deaths remains common. Aim of this analysis was to assess the real impact of COVID-19 through the analysis of 2020 Italian all-cause mortality data compared to historical series.

METHODS

We performed a retrospective analysis of 2020 and 2015-2019 all-cause mortality data released by the Italian National Institute for Statistics (ISTAT) for the time period January 1st-March 21st. This preliminary sample included 1084 Italian municipalities showing at least 10 deaths during the above-mentioned timeframe and an increase in mortality of more than 20% as compared to the previous five years (2015-2019), with a resulting coverage of 21% of Italian population. The difference between 2020 observed and expected deaths (mean of weekly deaths in 2015-2019) was computed, together with mortality rate ratio (MRR) for each of the four weeks following detection of the first autochthonous COVID-19 case in Italy (February 23rd, 2020 - March 21st, 2020), as well as for this entire timeframe. Subgroup analysis by age groups was also performed.

RESULTS

Overall MRR was 1.79 [1.75-1.84], with an observed excess mortality of 8750 individuals in the investigated sample, which in itself outweighs Italian Civil Protection report of only 4,825 COVID-19-related deaths across Italy, as of March 21. Subgroup analysis did not show any difference in mortality rate in '0-14 years' age group, while MRRs were significantly increased in older age groups, in particular in patients >75 years (MRR 1.84 [1.79-1.89]). In addition, week-by-week analysis showed a progressive increase in MRR during this period, peaking in the last week (March 15th, 2020 - March 21st, 2020) with an estimated value of 2.65 [2.53-2.78].

CONCLUSIONS

The analysis of all-cause mortality data in Italy indicates that reported COVID-19-related deaths are an underestimate of the actual death toll. All-cause death should be seen as the epidemiological indicator of choice to assess the real mortality impact exerted by SARS-CoV-2, given that it also best reflects the toll on frail patient subsets (e.g. the elderly or those with cardiovascular disease).

Impact of weather and pollution on the rate of cerebrovascular events in a large metropolitan area

BACKGROUND

Despite mounting evidence, there is uncertainty on the impact of the interplay between weather and pollution features on the risk of acute cerebrovascular events (CVE). We aimed at appraising role of weather and pollution on the daily risk of CVE.

METHODS

Anonymized data from a hub CVE center in a large metropolitan area were collected and analyzed according to weather (temperature, pressure, humidity, and rainfall) and pollution (carbon monoxide [CO], nitrogen dioxide [NO2], nitrogen oxides [NOX], ozone [O3], and particulate matter [PM]) on the same and the preceding days. Poisson regression and time series analyses were used to appraise the association between environmental features and daily CVE, distinguishing also several subtypes of events.

RESULTS

We included a total of 2534 days, with 1363 days having ≥1 CVE, from 2012 to 2017. Average daily rate was 1.56 (95% confidence interval: 1.49; 1.63) for CVE, with other event rates ranging between 1.42 for stroke and 0.01 for ruptured intracranial aneurysm. Significant associations were found between CVE and temperature, pressure, CO, NO2, NOX, O3, and PM <10 µm (all P<0.05), whereas less stringent associations were found for humidity, rainfall, and PM <2.5 µm. Time series analysis exploring lag suggested that associations were stronger at same-day analysis (lag 0), but even environmental features predating several days or weeks were significantly associated with events. Multivariable analysis suggested that CO (point estimate 1.362 [1.011; 1.836], P=0.042) and NO2 (1.011 [1.005; 1.016], P<0.001) were the strongest independent predictors of CVE.

CONCLUSIONS

Environmental features are significantly associated with CVE, even several days before the actual event. Levels of CO and NO2 can be potentially leveraged for population-level interventions to reduce the burden of CVE.

Interplay between COVID-19, pollution, and weather features on changes in the incidence of acute coronary syndromes in early 2020

BACKGROUND

Coronavirus disease 2019 (COVID-19) has caused an unprecedented change in the apparent epidemiology of acute coronary syndromes (ACS). However, the interplay between this disease, changes in pollution, climate, and aversion to activation of emergency medical services represents a challenging conundrum. We aimed at appraising the impact of COVID-19, weather, and environment features on the occurrence of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) in a large Italian region and metropolitan area.

METHODS AND RESULTS

Italy was hit early on by COVID-19, such that state of emergency was declared on January 31, 2020, and national lockdown implemented on March 9, 2020, mainly because the accrual of cases in Northern Italy. In order to appraise the independent contribution on changes in STEMI and NSTEMI daily rates of COVID-19, climate and pollution, we collected data on these clinical events from tertiary care cardiovascular centers in the Lazio region and Rome metropolitan area. Multilevel Poisson modeling was used to appraise unadjusted and adjusted effect estimates for the daily incidence of STEMI and NSTEMI cases. The sample included 1448 STEMI and 2040 NSTEMI, with a total of 2882 PCI spanning 6 months. Significant reductions in STEMI and NSTEMI were evident already in early February 2020 (all p<0.05), concomitantly with COVID-19 spread and institution of national countermeasures. Changes in STEMI and NSTEMI were inversely associated with daily COVID-19 tests, cases, and/or death (p<0.05). In addition, STEMI and NSTEMI incidences were associated with daily NO2, PM10, and O3 concentrations, as well as temperature (p<0.05). Multi-stage and multiply adjusted models highlighted that reductions in STEMI were significantly associated with COVID-19 data (p<0.001), whereas changes in NSTEMI were significantly associated with both NO2 and COVID-19 data (both p<0.001).

CONCLUSIONS

Reductions in STEMI and NSTEMI in the COVID-19 pandemic may depend on different concomitant epidemiologic and pathophysiologic mechanisms. In particular, recent changes in STEMI may depend on COVID-19 scare, leading to excess all-cause mortality, or effective reduced incidence, whereas reductions in NSTEMI may also be due to beneficial reductions in NO2 emissions in the lockdown phase.

Excess of cardiovascular deaths during the COVID-19 pandemic in Brazilian capital cities

INTRODUCTION

During the COVID-19 pandemic, excess mortality has been reported, while hospitalisations for acute cardiovascular events reduced. Brazil is the second country with more deaths due to COVID-19. We aimed to evaluate excess cardiovascular mortality during COVID-19 pandemic in 6 Brazilian capital cities.

METHODS

Using the Civil Registry public database, we evaluated total and cardiovascular excess deaths, further stratified in specified cardiovascular deaths (acute coronary syndromes and stroke) and unspecified cardiovascular deaths in the 6 Brazilian cities with greater number of COVID-19 deaths (São Paulo, Rio de Janeiro, Fortaleza, Recife, Belém, Manaus). We compared observed with expected deaths from epidemiological weeks 12-22 of 2020. We also compared the number of hospital and home deaths during the period.

RESULTS

There were 65 449 deaths and 17 877 COVID-19 deaths in the studied period and cities for 2020. Cardiovascular mortality increased in most cities, with greater magnitude in the Northern capitals. However, while there was a reduction in specified cardiovascular deaths in the most cities, the Northern capitals showed an increase of these events. For unspecified cardiovascular deaths, there was a marked increase in all cities, which strongly correlated to the rise in home deaths (r=0.86, p=0.01).

CONCLUSION

Excess cardiovascular mortality was greater in the less developed cities, possibly associated with healthcare collapse. Specified cardiovascular deaths decreased in the most developed cities, in parallel with an increase in unspecified cardiovascular and home deaths, presumably as a result of misdiagnosis. Conversely, specified cardiovascular deaths increased in cities with a healthcare collapse.

Impact of temporary traffic bans on the risk of acute coronary syndromes in a large metropolitan area

BACKGROUND

Strong epidemiologic evidence has highlighted the role of pollution, on top of adverse climate features, as a novel cardiovascular risk factor. However, mechanistic proof that reducing pollution may be beneficial to prevent atherothrombotic events is limited. We aimed at appraising the impact of temporary traffic bans in a large metropolitan area on the risk of acute coronary syndromes.

METHODS

Aggregate and anonymized data from 15 tertiary cardiac care centers were obtained detailing precoronavirus disease 2019 (COVID-19) daily cases of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), including those treated with percutaneous coronary intervention (PCI). Data on pollutants and climate were sought for the same days. Mixed level regression was used to compare the week before vs after the traffic ban (Fortnight analysis), the 3 days before vs. after (Weekly analysis) and the Sunday before vs. after (Sunday analysis).

RESULTS

A total of 8 days of temporary traffic bans were included, occurring between 2017 and 2020, totaling 802 STEMI and 1196 NSTEMI in the Fortnight analysis, 382 STEMI and 585 in the Weekly analysis, and 148 STEMI and 210 NSTEMI in the Sunday analysis.Fortnight and Sunday analyses did not disclose a significant impact of traffic ban on STEMI or NSTEMI (all P>0.05). Conversely, Weekly analysis showed non-significant changes for STEMI, but a significant decrease in daily NSTEMI when comparing the 3 days before the traffic ban with the ban day (P=0.043), as well as the 3 days before vs. the 3 days after the ban (P=0.025). No statistically significant effect of traffic ban was found at Fortnight, Weekly or Sunday analyses for daily mean concentrations of benzene, carbon monoxide, nitric oxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter (PM) <2.5 µm or PM <10 µm (all P>0.05). However, minimum daily concentrations showed a significant reduction of ozone during the ban in comparison to the week preceding it (P=0.034), nitric oxide during the ban in comparison to the 3 days preceding it (P=0.046), and an increase in benzene during the ban in comparison to the Sunday before (P=0.039).

CONCLUSIONS

Temporary traffic ban may favorably reduce coronary atherothrombotic events, and in particular NSTEMI, even if not globally and immediately impacting on environmental pollution. Further controlled studies are required to confirm and expand this hypothesis-generating results.