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  • Review
  • Open Access

9 October 2020

“Acute Myocardial Infarction in the Time of COVID-19”: A Review of Biological, Environmental, and Psychosocial Contributors

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1
Institute of Clinical Physiology, National Research Council, 56124 Pisa, Italy
2
Ospedale del Cuore G Pasquinucci Fondazione Toscana Gabriele Monasterio di Massa, via Aurelia Sud, 54100 Massa, Italy
*
Author to whom correspondence should be addressed.
This article belongs to the Section Health Communication and Informatics

Abstract

Coronavirus disease 2019 (COVID-19) has quickly become a worldwide health crisis. Although respiratory disease remains the main cause of morbidity and mortality in COVID patients, myocardial damage is a common finding. Many possible biological pathways may explain the relationship between COVID-19 and acute myocardial infarction (AMI). Increased immune and inflammatory responses, and procoagulant profile have characterized COVID patients. All these responses may induce endothelial dysfunction, myocardial injury, plaque instability, and AMI. Disease severity and mortality are increased by cardiovascular comorbidities. Moreover, COVID-19 has been associated with air pollution, which may also represent an AMI risk factor. Nonetheless, a significant reduction in patient admissions following containment initiatives has been observed, including for AMI. The reasons for this phenomenon are largely unknown, although a real decrease in the incidence of cardiac events seems highly improbable. Instead, patients likely may present delayed time from symptoms onset and subsequent referral to emergency departments because of fear of possible in-hospital infection, and as such, may present more complications. Here, we aim to discuss available evidence about all these factors in the complex relationship between COVID-19 and AMI, with particular focus on psychological distress and the need to increase awareness of ischemic symptoms.

1. Introduction

At the end of 2019, the new coronavirus SARS-CoV-2 was identified as the cause of an acute respiratory infection and cause of a worldwide pandemic. At the moment, there are many unclear issues related to the pathogenesis of the infection and the reasons underlying the extremely different clinical course, from asymptomatic to severe clinical manifestations, often carried out in a very short time period. The virus enters in several cell types, including cardiomyocytes following proteolytic cleavage of its S protein by a serine protease, and binding to the transmembrane angiotensin-converting enzyme 2 (ACE2) [1]. Moreover, whether it seems that pre-existing cardiovascular (CV) risk factors and disease may increase COVID-19 susceptibility, it has been also observed that patients with CV disease may experience more severe symptoms of infection [2]. In fact, the virus can worsen underlying CV lesions, precipitate de novo acute CV events, such as acute myocardial infarction (AMI), and induce CV chronic damage [3,4]. Thus, while the focus may be on the pulmonary system, it is important to be aware of the CV implications, which can be a significant determinant for complications and mortality associated with this virus.
Nonetheless, despite these common features and interactive factors, a significant decrease in patient admissions to intensive coronary unit (ICU) has been observed following containment measures, suggesting that other determinants may reduce the capacity to quickly manage acute patients who are simultaneously or not infected with COVID-19 [5,6,7,8].
Hence, we aim here to discuss how, besides common pathophysiological mechanisms linking COVID to CV disease and favoring acute events, other factors (e.g., fear of contagion, difficulty in contacting general practitioners, attention focused on COVID-19 patients, and a massive flow of health information and disparate viewpoints) may account for the unexpected and paradoxical decrease in AMI during lockdown, unlikely caused by a real decrease in the incidence of CV events. These reflections will help us to face a possible second COVID-19 pandemic wave or other outbreaks.

3. COVID-related Fear and Distress

Fear, defined as “an unpleasant emotion or thought that you have when you are frightened or worried by something dangerous, painful, or bad that is happening or might happen” (Cambridge Dictionary), involves biological adaptive responses motivating a range of positive behaviors aimed at reducing the risk (e.g., social distancing, hand hygiene), if not chronic or out of proportion. In fact, the possible prospect of getting sick, the prolonged isolation and adverse economic effects, the personal and family infection fear, the uncertainty of future and crisis duration, and the overload of (mis)information may generate negative and harmful fear [98,99,100]. A study conducted in a large Chinese general population detected an elevated stress level, anxiety, and depression (8.1%, 28.8%, and 16.5%, respectively) during the COVID outbreak onset, and remained unchanged at the epidemic peak, four weeks later [101]. Similarly, approximately 25% of 7143 Chinese students experienced anxiety during the COVID-19 epidemic [102]. This symptom may be even increased in subjects with CV disease and comorbidities, where mood alterations and/or lockdown may worsen lifestyle habits and cause poor therapy adherence [103].
In addition, healthcare professionals may develop distress after facing stressful emergencies, due to the risk of infection, overwork, isolation, and fewer family contacts that may negatively affect their attention and decision making ability, indirectly worsening patient care [104,105,106].
Psychometric tools have been developed and validated to evaluate COVID-19 fear [107,108]. The COVID-19 Peritraumatic Distress Index is a self-report questionnaire that investigates anxiety, depression, specific phobias, cognitive change, compulsive behavior, physical symptoms, and social context [6]. Data obtained in 52,730 subjects using this tool evidenced that nearly 35% of the Chinese population suffered from psychological distress, in particular female participants [6].
The Fear of COVID-19 Scale (FCV-19S) is obtained by a questionnaire of seven items (total score ranges between 7 and 35, a higher sum score indicating a higher COVID-19 fear), validated and applied in different general populations (both Asian and European), which highlighted significant associations of fear with stress, anxiety, and depression [99,109,110,111]. The presence of chronic disease is related to COVID-19 fear, and females have significantly higher fear rates than males [112].
Nevertheless, these questionnaires have not yet been tested in CV patients. We administered the FCV-19S questionnaire in 30 CV outpatients and compared these results with those published relating to the general Italian population [111]. Preliminary results, which must certainly be confirmed in a larger sample, suggested higher scores in CV risk patients for both emotional (item 4) and symptomatic fear expression (items 3 and 6) (Table 2).
Table 2. Mean of the items of the Italian Fear of COVID-19 test, in a general population and in cardiovascular outpatients.
In particular, AMI patients may underestimate symptoms and not promptly refer to hospital, vanquishing recommended strategies based on intervention responsiveness and incurring complications due to an evolving AMI.

4. AMI during COVID pandemic: Fall in Admission and Delayed Access to Hospital Care

Healthcare practitioners all over the world have noticed a significant “AMI fall” during the COVID period. The number of emergency department visits in two major northern Italy referral hospitals (21 February–6 April) showed an inverse trend with daily COVID-19 mortality [113]. In Austria, a reduction of 40% in AMI admission was observed during March 2020 [114]. Data collected in the period January–March 2020 from nine high-volume USA centers, evidenced a 40% fall in the number of cardiac STEMI catheterizations [115]. The decrease was significant for STEMI (26.5%) and NSTEMI (65.1%), both in North Italy and in Central/South Italy [116]. Moreover, in a single large center in northern Italy, data obtained in March 2020 compared to March 2019 showed a significant reduction of 30% for STEMI, 66% for NSTEMI, and 50% for severe bradyarrhythmia [5]. These findings were confirmed by our experience, as we assessed a significant decline in STEMI admissions to the ICU-Cardiology Department of Ospedale del Cuore-Massa between 1 January and 10 June 2020, with respect to data collected in the same period in 2019 (Figure 1, panel A). Notably, in relation to fear, no patient with COVID-19 lab-confirmed infection was found between those admitted to our hospital, all swab-tested, until 10 June 2020.
Figure 1. Comparison between 1 January–10 June 2019 versus 2020 segment elevation myocardial infarction admissions to the Ospedale del Cuore-Massa.
These data are worrying considering the result obtained in a small number of Chinese AMI patients (n = 7), which showed a great delay in the “symptom onset to first medical contact” time after control measure implementation, when compared to 2018–2019 (5 h versus an hour and a half) [117].
Table 3 shows key time points in STEMI care in the COVID period compared to pre-/post- outbreak periods (Ospedale del Cuore-Massa). Additionally, in our experience, the major difference was in the time from “symptom onset to first medical contact”.
Table 3. Key time points (in minutes) in STEMI care (Ospedale del Cuore-Massa) before and after COVID-19 outbreak.

5. Discussion

The focus on the COVID-19 pandemic, which has significantly tested the health care system globally, has let the guard down against psychological effects in the general population and people with chronic diseases.
The heart–brain axis shows close interaction, as depression and anxiety are related to a higher risk of CV events and mortality [118,119,120,121,122]. Nevertheless, in this COVID-19 period, psychological load does not seem associated with CV disease exacerbation, but rather with a fall in hospital admissions. In particular, incorrect communication may have generated the fear of possible in-hospital contamination, avoiding regular checks, delaying the diagnosis of acute events, and referral to ICU units (Figure 2).
Figure 2. Potential determinants in the relationships between SARS-CoV-2 infection and acute myocardial infarction.
Global measures and media–health communication may have generated fear of possible in-hospital contamination, avoiding regular checks by doctors, whereas consulting cardiologists and regular drug intake can become difficult, delaying acute event diagnosis and worsening acute CVD consequences, and causing subsequent delay in referral to an integrated critical care unit. Health workers, which are potentially exposed to the pathogen and highly stressed, did not receive mental health assistance during the pandemic, and this may indirectly affect care quality (Figure 2) [123]. Furthermore, patients may suffer a lack of attention because contact with primary care professionals might be difficult due to reduction in non-urgent activity. Accordingly, it has been observed that non-COVID-19 hospital admissions significantly decrease during the outbreak, likely due, almost in part, to changes in health care decisions and/or delays in hospital access [124]. Additionally, out-of-hospital deaths could be increased, in numbers that are very complex to quantify, in terms of cardiac arrests, unexplained deaths, heart failure, and other non-COVID clinical causes, beyond the cardiovascular one [125]. Health communication is a critical tool to handle uncertainty and fear, reduce risky behavior, as well as encourage people to overcome the crisis [126]. Instead, inaccurate or unambiguous information can increase distress and elicit harmful social reactions, such as discrimination, anger, and aggressive behaviors [127]. The information about the putative relationship between environmental pollution and COVID infection is an emblematic example, which may attract immediate attention towards a recognized “enemy”, willingly identified as the co-culprit of the outbreak. In this case, the risks of oversimplification by inaccurate information—including the pitfall of meaningless correlation—should be taken into account [68].
In this scenario, the cardiology community should attempt every effort to reduce possible “collateral” damage through multiple actions:
  • Attention to vulnerable subjects (e.g., elderly, frail people, patients at high CV risk);
  • Correct information to patients on the delayed hospital access risks;
  • Epidemiological monitoring;
  • Strategies aimed to reduce distress;
  • Workload for healthcare professionals based on health specialty;
  • Multidisciplinary team including intensive care specialists, laboratorists, psychologists, and cardiologists;
  • Teleconsultations and telemonitoring to monitor high-risk patients;
  • Electronic devices/apps to help patients in their personal disease management;
  • Warning receipt in case of alarming data;
  • Regular, clear, and reliable information on pandemic to patients.

6. Conclusions

The relationship between COVID-19 and AMI is supported by many clues (Figure 2). An increased risk of AMI is likely related to COVID-19 infection, due to the inflammatory response and hypercoagulability. Accordingly, abnormalities of cardiac troponins are the most common finding in COVID-19-affected patients. Patients with pre-existing CV disease and CV comorbidities may exhibit higher vulnerability to COVID-19 and a worse clinical outcome.
The relationship of air pollution with COVID-19 needs to be established, and together with an adequate collection of health data, environmental and demographic information are crucial for studying possible associations between exposure to atmospheric pollutants, diffusion, and severity of COVID-19. Importantly, although PM and nitrogen oxides are recognized as exacerbating risk factors for ACS, their levels were reduced due to the lockdown. In northern Italy, these decreases reached values of up to 58% and 38%, respectively, for nitric oxide and NO2, whereas PM10 and PM2.5 showed a smaller decrease since they are affected by secondary emissions even from long distances [127]. While it is plausible that the observed drop in concentrations of air pollutants may have contributed to a reduction in hospital admissions for AMI, this hypothesis, and the risk quantification, remains to be demonstrated by etiological design studies based on short-term exposure assessment.
Moreover, therapies under investigation for COVID-19 infection can have significant CV side effects.
However, at this point, it is particularly important to assess the role of psychological issues, such as distress and fear. In particular, it will be interesting to understand whether a patient’s fear may reduce AMI presentation, provoking a delay in appropriate and timely revascularization in the short-term, as well as long-term increased morbidity and mortality. Moreover, it is always possible that other (also actually unknown) reasons may affect the decrease in the incidence of AMI during the lockdown. As an example, it was recently hypothesized that increase in sleep duration in the time of COVID may positively impact overall health and beneficially contribute to the observed AMI reduction [128].
In this context, every effort must be directed to clear and reliable information for general audience patients, avoiding the spread of inconsistent or distorted news that can generate fear or false optimism. As the pandemic continues, public campaigns to raise awareness of ischemic symptoms should be reinforced, as the indirect effects of the COVID-19 pandemic on non-COVID diseases can be even more catastrophic than the infection itself.

Author Contributions

Conceptualization, C.V.; methodology, C.V.; investigation, C.V.,.K.C; data curation, F.G., C.V..; writing—original draft preparation, F.G., K.C., A.M., C.V.; writing—review and editing, F.G., E.B., F.B., C.V.; visualization, K.C., A.M., E.B., A.E., S.B., F.B.; supervision, F.G., C.V.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. South, A.M.; Diz, D.I.; Chappell, M.C. COVID-19, ACE2, and the cardiovascular consequences. Am. J. Physiol. Heart Circ. Physiol. 2020, 318, H1084–H1090. [Google Scholar] [CrossRef]
  2. Guzik, T.J.; Mohiddin, S.A.; Dimarco, A.; Patel, V.; Savvatis, K.; Marelli-Berg, F.M.; Madhur, M.S.; Tomaszewski, M.; Maffia, P.; D’Acquisto, F.; et al. COVID-19 and the cardiovascular system: Implications for risk assessment, diagnosis, and treatment options. Cardiovasc. Res. 2020. [Google Scholar] [CrossRef]
  3. Bansal, M. Cardiovascular Disease and COVID-19. Diabetes Metab. Syndr. 2020, 14, 247–250. [Google Scholar] [CrossRef] [PubMed]
  4. Long, B.; Brady, W.J.; Koyfman, A.; Gottlieb, M. Cardiovascular Complications in COVID-19. Am. J. Emerg. Med. 2020, 38, 1504–1507. [Google Scholar] [CrossRef] [PubMed]
  5. Toniolo, M.; Negri, F.; Antonutti, M.; Masè, M.; Facchin, D. Unpredictable Fall of Severe Emergent Cardiovascular Diseases Hospital Admissions during the COVID-19 Pandemic: Experience of a Single Large Center in Northern Italy. J. Am. Heart Assoc. 2020, e017122. [Google Scholar] [CrossRef] [PubMed]
  6. Qiu, J.; Shen, B.; Zhao, M.; Wang, Z.; Xie, B.; Xu, Y. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: Implications and policy recommendations. Gen. Psychiatr. 2020, 33, e100213. [Google Scholar] [CrossRef] [PubMed]
  7. Bayham, J.; Fenichel, E.P. Impact of school closures for COVID-19 on the US health-care workforce and net mortality: A modelling study. Lancet Public Health 2020, 5, e271–e278. [Google Scholar] [CrossRef]
  8. Nicola, M.; Alsafi, Z.; Sohrabi, C.; Kerwan, A.; Al-Jabir, A.; Iosifidis, C.; Agha, M.; Agha, R. The socio-economic implications of the coronavirus pandemic (COVID-19): A review. Int. J. Surg. 2020, 78, 185–193. [Google Scholar] [CrossRef]
  9. Ye, Q.; Wang, B.; Mao, J. The Pathogenesis and Treatment of the ‘Cytokine Storm’ in COVID-19. J. Infect 2020, 80, 607–613. [Google Scholar] [CrossRef]
  10. Huang, C.; Wang, Y.; Li, X.; Ren, L.; Zhao, J.; Hu, Y.; Zhang, L.; Fan, G.; Xu, J.; Gu, X.; et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020, 395, 497–506. [Google Scholar] [CrossRef]
  11. Miossec, P. Understanding the cytokine storm during COVID-19: Contribution of preexisting chronic inflammation. Eur. J. Rheumatol. 2020. [Google Scholar] [CrossRef] [PubMed]
  12. Maeder, M.; Fehr, T.; Rickli, H.; Ammann, P. Sepsis-associated myocardial dysfunction: Diagnostic and prognostic impact of cardiac troponins and natriuretic peptides. Chest 2006, 129, 1349–1366. [Google Scholar] [CrossRef] [PubMed]
  13. Libby, P. The Heart in COVID19: Primary Target or Secondary Bystander? JACC Basic Transl. Sci. 2020. [Google Scholar] [CrossRef]
  14. Sinha, P.; Matthay, M.A.; Calfee, C.S. Is a “Cytokine Storm” Relevant to COVID-19? JAMA Intern. Med. 2020. [Google Scholar] [CrossRef] [PubMed]
  15. Kox, M.; Waalders, N.J.B.; Kooistra, E.J.; Gerretsen, J.; Pickkers, P. Cytokine Levels in Critically Ill Patients With COVID-19 and Other Conditions. JAMA 2020. [Google Scholar] [CrossRef]
  16. Gast, M.; Rauch, B.H.; Nakagawa, S.; Haghikia, A.; Jasina, A.; Haas, J.; Nath, N.; Jensen, L.; Stroux, A.; Böhm, A.; et al. Immune system-mediated atherosclerosis caused by deficiency of long non-coding RNA MALAT1 in ApoE-/-mice. Cardiovasc. Res. 2019, 115, 302–314. [Google Scholar] [CrossRef]
  17. Gast, M.; Rauch, B.H.; Haghikia, A.; Nakagawa, S.; Haas, J.; Stroux, A.; Schmidt, D.; Schumann, P.; Weiss, S.; Jensen, L.; et al. Long noncoding RNA NEAT1 modulates immune cell functions and is suppressed in early onset myocardial infarction patients. Cardiovasc. Res. 2019, 115, 1886–1906. [Google Scholar] [CrossRef]
  18. Liu, P.P.; Blet, A.; Smyth, D.; Li, H. The Science Underlying COVID-19: Implications for the Cardiovascular System. Circulation 2020. [Google Scholar] [CrossRef]
  19. Levi, M.; van der Poll, T.; Büller, H.R. Bidirectional relation between inflammation and coagulation. Circulation 2004, 109, 2698–2704. [Google Scholar] [CrossRef]
  20. Stoneham, S.M.; Milne, K.M.; Nuttal, E.; Frew, G.H.; Sturrock, B.R.; Sivaloganathan, H.; Ladikou, E.E.; Drage, S.; Phillips, B.; Chevassut, T.J.; et al. Thrombotic risk in COVID-19: A case series and case-control study. Clin. Med. (Lond) 2020. [Google Scholar] [CrossRef]
  21. Li, B.; Yang, J.; Zhao, F.; Zhi, L.; Wang, X.; Liu, L.; Bi, Z.; Zhao, Y. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin. Res. Cardiol. 2020, 109, 531–538. [Google Scholar] [CrossRef] [PubMed]
  22. Wu, Z.; McGoogan, J.M. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA 2020. [Google Scholar] [CrossRef] [PubMed]
  23. Wang, A.; Zhao, W.; Xu, Z.; Gu, J. Timely blood glucose management for the outbreak of 2019 novel coronavirus disease (COVID-19) is urgently needed. Diabetes Res. Clin. Pract. 2020, 162, 108118. [Google Scholar] [CrossRef] [PubMed]
  24. Zhou, J.; Tan, J. Letter to the Editor: Diabetes patients with COVID-19 need better blood glucose management in Wuhan, China. Metabolism 2020, 107, 154216. [Google Scholar] [CrossRef] [PubMed]
  25. Iqbal, A.; Prince, L.R.; Novodvorsky, P.; Bernjak, A.; Thomas, M.R.; Birch, L.; Lambert, D.; Kay, L.J.; Wright, F.J.; Macdonald, I.A.; et al. Effect of Hypoglycemia on Inflammatory Responses and the Response to Low-Dose Endotoxemia in Humans. J. Clin. Endocrinol. Metab. 2019, 104, 1187–1199. [Google Scholar] [CrossRef]
  26. Simonnet, A.; Chetboun, M.; Poissy, J.; Raverdy, V.; Noulette, J.; Duhamel, A.; Labreuche, J.; Mathieu, D.; Pattou, F.; Jourdain, M.; et al. High Prevalence of Obesity in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Requiring Invasive Mechanical Ventilation. Obesity (Silver Spring) 2020, 28, 1195–1199. [Google Scholar] [CrossRef] [PubMed]
  27. Guan, W.-J.; Ni, Z.-Y.; Hu, Y.; Liang, W.H.; Ou, C.Q.; He, J.X.; Liu, L.; Shan, H.; Lei, C.L.; Hui, D.S.C.; et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med. 2020, 382, 1708–1720. [Google Scholar] [CrossRef]
  28. Beaney, T.; Burrell, L.M.; Castillo, R.R.; Charchar, F.J.; Cro, S.; Damasceno, A.; Kruger, R.; Nilsson, P.M.; Prabhakaran, D.; Ramirez, A.J.; et al. The MMM Investigators. May Measurement Month 2018: A pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension. Eur. Heart J. 2019, 40, 2006–2017. [Google Scholar] [CrossRef]
  29. Kreutz, R.; Algharably, E.A.E.-H.; Azizi, M.; Dobrowolski, P.; Guzik, T.; Januszewicz, A.; Persu, A.; Prejbisz, A.; Riemer, T.G.; Wang, J.G.; et al. Hypertension, the renin-angiotensin system, and the risk of lower respiratory tract infections and lung injury: Implications for COVID-19. Cardiovasc. Res. 2020. [Google Scholar] [CrossRef]
  30. Grasselli, G.; Zangrillo, A.; Zanella, A.; Antonelli, M.; Cabrini, L.; Castelli, A.; Cereda, D.; Coluccello, A.; Foti, G.; Fumagalli, R.; et al. COVID-19 Lombardy ICU Network. Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. JAMA 2020, 323, 1574–1581. [Google Scholar] [CrossRef]
  31. Gebhard, C.; Regitz-Zagrosek, V.; Neuhauser, H.K.; Morgan, R.; Klein, S.L. Impact of sex and gender on COVID-19 outcomes in Europe. Biol. Sex Differ. 2020, 11, 29. [Google Scholar] [CrossRef] [PubMed]
  32. Chatre, C.; Roubille, F.; Vernhet, H.; Jorgensen, C.; Pers, Y.-M. Cardiac Complications Attributed to Chloroquine and Hydroxychloroquine: A Systematic Review of the Literature. Drug Saf. 2018, 41, 919–931. [Google Scholar] [CrossRef] [PubMed]
  33. Stevenson, A.; Kirresh, A.; Conway, S.; White, L.; Ahmad, M.; Little, C. Hydroxychloroquine use in COVID-19: Is the risk of cardiovascular toxicity justified? Open Heart 2020, 7, e001362. [Google Scholar] [CrossRef] [PubMed]
  34. Saha, B.K.; Bonnier, A.; Chong, W. Antimalarials as antivirals for COVID-19: Believe it or not! Am. J. Med. Sci. 2020. [Google Scholar] [CrossRef]
  35. Lam, S.; Lombardi, A.; Ouanounou, A. COVID-19: A review of the proposed pharmacological treatments. Eur. J. Pharmacol. 2020, 886, 173451. [Google Scholar] [CrossRef]
  36. Somer, M.; Kallio, J.; Pesonen, U.; Pyykkö, K.; Huupponen, R.; Scheinin, M. Influence of hydroxychloroquine on the bioavailability of oral metoprolol. Br. J. Clin. Pharmacol. 2000, 49, 549–554. [Google Scholar] [CrossRef]
  37. Driggin, E.; Madhavan, M.V.; Bikdeli, B.; Chuich, T.; Laracy, J.; Biondi-Zoccai, G.; Brown, T.S.; Der Nigoghossian, C.; Zidar, D.A.; Haythe, J.; et al. Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic. J. Am. Coll. Cardiol. 2020, 75, 2352–2371. [Google Scholar] [CrossRef]
  38. WHO. The Use of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) in Patients with COVID-19. Available online: https://www.who.int/publications-detail-redirect/the-use-of-non-steroidal-anti-inflammatory-drugs-(nsaids)-in-patients-with-covid-19 (accessed on 28 June 2020).
  39. Vaduganathan, M.; Vardeny, O.; Michel, T.; McMurray, J.J.V.; Pfeffer, M.A.; Solomon, S.D. Renin-Angiotensin-Aldosterone System Inhibitors in Patients with Covid-19. N. Engl. J. Med. 2020, 382, 1653–1659. [Google Scholar] [CrossRef]
  40. Bassendine, M.F.; Bridge, S.H.; McCaughan, G.W.; Gorrell, M.D. COVID-19 and comorbidities: A role for dipeptidyl peptidase 4 (DPP4) in disease severity? J. Diabetes 2020. [Google Scholar] [CrossRef]
  41. Hamanaka, R.B.; Mutlu, G.M. Particulate Matter Air Pollution: Effects on the Cardiovascular System. Front Endocrinol. (Lausanne) 2018, 9, 680. [Google Scholar] [CrossRef]
  42. Argacha, J.F.; Collart, P.; Wauters, A.; Kayaert, P.; Lochy, S.; Schoors, D.; Sonck, J.; de Vos, T.; Forton, M.; Brasseur, O.; et al. Air pollution and ST-elevation myocardial infarction: A case-crossover study of the Belgian STEMI registry 2009-2013. Int. J. Cardiol. 2016, 223, 300–305. [Google Scholar] [CrossRef] [PubMed]
  43. Akbarzadeh, M.A.; Khaheshi, I.; Sharifi, A.; Yousefi, N.; Naderian, M.; Namazi, M.H.; Safi, M.; Vakili, H.; Saadat, H.; Alipour Parsa, S.; et al. The association between exposure to air pollutants including PM10, PM2.5, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide concentration and the relative risk of developing STEMI: A case-crossover design. Environ. Res. 2018, 161, 299–303. [Google Scholar] [CrossRef]
  44. Brook, R.D.; Rajagopalan, S.; Pope, C.A.; Brook, J.R.; Bhatnagar, A.; Diez-Roux, A.V.; Holguin, F.; Hong, Y.; Luepker, R.V.; Mittleman, M.A.; et al. American Heart Association Council on Epidemiology and Prevention, Council on the Kidney in Cardiovascular Disease, and Council on Nutrition, Physical Activity and Metabolism. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation 2010, 121, 2331–2378. [Google Scholar] [CrossRef] [PubMed]
  45. Sacks, J.D.; Stanek, L.W.; Luben, T.J.; Johns, D.O.; Buckley, B.J.; Brown, J.S.; Ross, M. Particulate matter-induced health effects: Who is susceptible? Environ. Health Perspect. 2011, 119, 446–454. [Google Scholar] [CrossRef] [PubMed]
  46. Nuvolone, D.; Balzi, D.; Chini, M.; Scala, D.; Giovannini, F.; Barchielli, A. Short-term association between ambient air pollution and risk of hospitalization for acute myocardial infarction: Results of the cardiovascular risk and air pollution in Tuscany (RISCAT) study. Am. J. Epidemiol. 2011, 174, 63–71. [Google Scholar] [CrossRef]
  47. Chen, C.; Zhu, P.; Lan, L.; Zhou, L.; Liu, R.; Sun, Q.; Ban, J.; Wang, W.; Xu, D.; Li, T. Short-term exposures to PM2.5 and cause-specific mortality of cardiovascular health in China. Environ. Res. 2018, 161, 188–194. [Google Scholar] [CrossRef] [PubMed]
  48. Zheng, M.; Zhang, Y.; Feng, W.; Chen, Y.; Huan, L.; Ye, S.; Wu, J.; Huang, J.; Liao, Y.; Guo, P.; et al. Short-term exposure to ambient air pollution and acute myocardial infarction attack risk. J Public Health (Berl.) 2019. [Google Scholar] [CrossRef]
  49. Setti, L.; Passarini, F.; De Gennaro, G.; Di Gilio, A.; Palmisani, J.; Buono, P.; Fornari, G.; Perrone, M.G.; Piazzalunga, A.; Barbieri, P.; et al. Relazione Circa L’effetto Dell’inquinamento da Particolato Atmosferico e la Diffusione di Virus Nella Popolazione 2020. Available online: https://www.simaonlus.it/wpsima/wp-content/uploads/2020/03/COVID19_Position-Paper_Relazione-circa-l%E2%80%99effetto-dell%E2%80%99inquinamento-da-particolato-atmosferico-e-la-diffusione-di-virus-nella-popolazione.pdf (accessed on 3 July 2020).
  50. Zhou, M.; He, G.; Fan, M.; Wang, Z.; Liu, Y.; Ma, J.; Ma, Z.; Liu, J.; Liu, Y.; Wang, L.; et al. Smog episodes, fine particulate pollution and mortality in China. Environ. Res. 2015, 136, 396–404. [Google Scholar] [CrossRef]
  51. Mo, Z.; Fu, Q.; Zhang, L.; Lyu, D.; Mao, G.; Wu, L.; Xu, P.; Wang, Z.; Pan, X.; Chen, Z.; et al. Acute effects of air pollution on respiratory disease mortalities and outpatients in Southeastern China. Sci. Rep. 2018, 8, 3461. [Google Scholar] [CrossRef]
  52. Nenna, R.; Evangelisti, M.; Frassanito, A.; Scagnolari, C.; Pierangeli, A.; Antonelli, G.; Nicolai, A.; Arima, S.; Moretti, C.; Papoff, P.; et al. Respiratory syncytial virus bronchiolitis, weather conditions and air pollution in an Italian urban area: An observational study. Environ. Res. 2017, 158, 188–193. [Google Scholar] [CrossRef]
  53. Horne, B.D.; Joy, E.A.; Hofmann, M.G.; Gesteland, P.H.; Cannon, J.B.; Lefler, J.S.; Blagev, D.P.; Korgenski, E.K.; Torosyan, N.; Hansen, G.I., 3rd; et al. Short-Term Elevation of Fine Particulate Matter Air Pollution and Acute Lower Respiratory Infection. Am. J. Respir. Crit. Care Med. 2018, 198, 759–766. [Google Scholar] [CrossRef] [PubMed]
  54. Xie, J.; Teng, J.; Fan, Y.; Xie, R.; Shen, A. The short-term effects of air pollutants on hospitalizations for respiratory disease in Hefei, China. Int. J. Biometeorol. 2019, 63, 315–326. [Google Scholar] [CrossRef] [PubMed]
  55. Phosri, A.; Ueda, K.; Phung, V.L.H.; Tawatsupa, B.; Honda, A.; Takano, H. Effects of ambient air pollution on daily hospital admissions for respiratory and cardiovascular diseases in Bangkok, Thailand. Sci. Total Environ. 2019, 651, 1144–1153. [Google Scholar] [CrossRef] [PubMed]
  56. Ciencewicki, J.; Jaspers, I. Air pollution and respiratory viral infection. Inhal. Toxicol. 2007, 19, 1135–1146. [Google Scholar] [CrossRef]
  57. Zhao, H.; Li, W.; Gao, Y.; Li, J.; Wang, H. Exposure to particular matter increases susceptibility to respiratory Staphylococcus aureus infection in rats via reducing pulmonary natural killer cells. Toxicology 2014, 325, 180–188. [Google Scholar] [CrossRef]
  58. Conticini, E.; Frediani, B.; Caro, D. Can atmospheric pollution be considered a co-factor in extremely high level of SARS-CoV-2 lethality in Northern Italy? Environ. Pollut. 2020, 261, 114465. [Google Scholar] [CrossRef]
  59. Yang, Z.; Hao, J.; Huang, S.; Yang, W.; Zhu, Z.; Tian, L.; Lu, Y.; Xiang, H.; Liu, S. Acute effects of air pollution on the incidence of hand, foot, and mouth disease in Wuhan, China. Atmos. Environ. 2020, 225, 117358. [Google Scholar] [CrossRef]
  60. Cui, Y.; Zhang, Z.-F.; Froines, J.; Zhao, J.; Wang, H.; Yu, S.-Z.; Detels, R. Air pollution and case fatality of SARS in the People’s Republic of China: An ecologic study. Environ. Health 2003, 2, 15. [Google Scholar] [CrossRef]
  61. Ye, Q.; Fu, J.-F.; Mao, J.-H.; Shang, S.-Q. Haze is a risk factor contributing to the rapid spread of respiratory syncytial virus in children. Environ. Sci. Pollut. Res. Int. 2016, 23, 20178–20185. [Google Scholar] [CrossRef]
  62. Contini, D.; Costabile, F. Does Air Pollution Influence COVID-19 Outbreaks? Atmosphere 2020, 11, 377. [Google Scholar] [CrossRef]
  63. Sun, J.; Zhou, T. Health Risk Assessment of China’s Main Air Pollutants. BMC Public Health 2017, 17, 212. [Google Scholar] [CrossRef] [PubMed]
  64. Zhu, Y.; Xie, J.; Huang, F.; Cao, L. Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China. Sci. Total Environ. 2020, 727, 138704. [Google Scholar] [CrossRef] [PubMed]
  65. Wu, X.; Nethery, R.C.; Sabath, B.M.; Braun, D.; Dominici, F. Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study. medRxiv 2020. [Google Scholar] [CrossRef]
  66. Liang, D.; Shi, L.; Zhao, J.; Liu, P.; Schwartz, J.; Gao, S.; Sarnat, J.; Liu, Y.; Ebelt, S.; Scovronick, N.; et al. Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States. medRxiv 2020. [Google Scholar] [CrossRef] [PubMed]
  67. Ogen, Y. Assessing nitrogen dioxide (NO2) levels as a contributing factor to coronavirus (COVID-19) fatality. Sci. Total Environ. 2020, 726, 138605. [Google Scholar] [CrossRef]
  68. Cori, L.; Bianchi, F. Covid-19 and air pollution: Communicating the results of geographic correlation studies. Epidemiol. Prev. 2020, 44, 120–123. [Google Scholar] [CrossRef]
  69. Sterpetti, A.V. Lessons Learned During the COVID-19 Virus Pandemic. J. Am. Coll. Surg. 2020, 230, 1092–1093. [Google Scholar] [CrossRef]
  70. Setti, L.; Passarini, F.; De Gennaro, G.; Barbieri, P.; Perrone, M.G.; Borelli, M.; Palmisani, J.; Di Gilio, A.; Torboli, V.; Fontana, F.; et al. SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy: First evidence. Environ. Res. 2020, 188, 109754. [Google Scholar] [CrossRef]
  71. Bontempi, E. First data analysis about possible COVID-19 virus airborne diffusion due to air particulate matter (PM): The case of Lombardy (Italy). Environ. Res. 2020, 186, 109639. [Google Scholar] [CrossRef]
  72. Re, S.; Facchini, A. Potential effects of airborne particulate matter on spreading, pathophysiology and prognosis of a viral respiratory infection. E&P Repository 2020, 2, 2020. [Google Scholar]
  73. WHO. Modes of Transmission of Virus Causing COVID-19: Implications for IPC Precaution Recommendations. Available online: https://www.who.int/news-room/commentaries/detail/modes-of-transmission-of-virus-causing-covid-19-implications-for-ipc-precaution-recommendations (accessed on 28 June 2020).
  74. Glencross, D.A.; Ho, T.-R.; Camiña, N.; Hawrylowicz, C.M.; Pfeffer, P.E. Air pollution and its effects on the immune system. Free Radic. Biol. Med. 2020, 151, 56–68. [Google Scholar] [CrossRef] [PubMed]
  75. Bianchi, F.; Cibella, F. Re: Air pollution and Covid19: How to compose the puzzle. BMJ 2020, 368, m627. [Google Scholar]
  76. Ancona, C.; Angelini, P.; Bauleo, L.; Bianchi, F.; Bisceglia, L.; Cadum, E.; Carducci, A.; Clementi, M.L.; Colacci, A.; Di Benedetto, A.; et al. Inquinamento atmosferico e COVID-19. Available online: https://www.scienzainrete.it/articolo/inquinamento-atmosferico-e-covid-19/rete-italiana-ambiente-e-salute/2020-04-13 (accessed on 3 July 2020).
  77. Morawska, L.; Milton, D.K. It is Time to Address Airborne Transmission of COVID-19. Clin. Infect. Dis. 2020, 6, ciaa939. [Google Scholar] [CrossRef]
  78. Frontera, A.; Cianfanelli, L.; Vlachos, K.; Landoni, G.; Cremona, G. Severe air pollution links to higher mortality in COVID-19 patients: The “double-hit” hypothesis. J. Infect. 2020. [Google Scholar] [CrossRef] [PubMed]
  79. Kuba, K.; Imai, Y.; Rao, S.; Gao, H.; Guo, F.; Guan, B.; Huan, Y.; Yang, P.; Zhang, Y.; Deng, W.; et al. A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus–induced lung injury. Nat. Med. 2005, 11, 875–879. [Google Scholar] [CrossRef] [PubMed]
  80. Pope 3rd, A.C.; Hansen, M.L.; Long, R.W.; Nielsen, K.R.; Eatough, N.L.; Wilson, W.E.; Eatough, D.J. Ambient Particulate Air Pollution, Heart Rate Variability, and Blood Markers of Inflammation in a Panel of Elderly Subjects. Environ. Health Perspect 2004, 112, 339–345. [Google Scholar] [CrossRef] [PubMed]
  81. Rich, D.Q.; Kipen, H.M.; Huang, W.; Wang, G.; Wang, Y.; Zhu, P.; Ohman-Strickland, P.; Hu, M.; Philipp, C.; Diehl, S.R.; et al. Association between changes in air pollution levels during the Beijing Olympics and biomarkers of inflammation and thrombosis in healthy young adults. JAMA 2012, 307, 2068–2078. [Google Scholar] [CrossRef]
  82. van Eeden, S.F.; Tan, W.C.; Suwa, T.; Mukae, H.; Terashima, T.; Fujii, T.; Qui, D.; Vincent, R.; Hogg, J.C. Cytokines involved in the systemic inflammatory response induced by exposure to particulate matter air pollutants (PM(10). Am. J. Respir. Crit. Care Med. 2001, 164, 826–830. [Google Scholar] [CrossRef]
  83. Coperchini, F.; Chiovato, L.; Croce, L.; Magri, F.; Rotondi, M. The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system. Cytokine Growth Factor Rev. 2020, 53, 25–32. [Google Scholar] [CrossRef]
  84. Bhaskaran, K.; Wilkinson, P.; Smeeth, L. Cardiovascular Consequences of Air Pollution: What Are the Mechanisms? Heart 2010, 97, 519–520. [Google Scholar] [CrossRef]
  85. Pope, C.A.; Verrier, R.L.; Lovett, E.G.; Larson, A.C.; Raizenne, M.E.; Kanner, R.E.; Schwartz, J.; Villegas, G.M.; Gold, D.R.; Dockery, D.W. Heart rate variability associated with particulate air pollution. Am. Heart J. 1999, 138, 890–899. [Google Scholar] [CrossRef]
  86. Schiavone, M.; Gobbi, C.; Biondi-Zoccai, G.; D’Ascenzo, F.; Palazzuoli, A.; Gasperetti, A.; Mitacchione, G.; Viecca, M.; Galli, M.; Fedele, F.; et al. Acute Coronary Syndromes and Covid-19: Exploring the Uncertainties. J. Clin. Med. 2020, 9. [Google Scholar] [CrossRef] [PubMed]
  87. Mills, N.L.; Törnqvist, H.; Gonzalez, M.C.; Vink, E.; Robinson, S.D.; Söderberg, S.; Boon, N.A.; Donaldson, K.; Sandström, T.; Blomberg, A.; et al. Ischemic and thrombotic effects of dilute diesel-exhaust inhalation in men with coronary heart disease. N. Engl. J. Med. 2007, 357, 1075–1082. [Google Scholar] [CrossRef] [PubMed]
  88. Lucking, A.J.; Lundback, M.; Mills, N.L.; Faratian, D.; Barath, S.L.; Pourazar, J.; Cassee, F.R.; Donaldson, K.; Boon, N.A.; Badimon, J.J.; et al. Diesel exhaust inhalation increases thrombus formation in man. Eur. Heart J. 2008, 29, 3043–3051. [Google Scholar] [CrossRef] [PubMed]
  89. Violi, F.; Pastori, D.; Cangemi, R.; Pignatelli, P.; Loffredo, L. Hypercoagulation and Antithrombotic Treatment in Coronavirus 2019: A New Challenge. Thromb. Haemost. 2020, 120, 949–956. [Google Scholar] [CrossRef] [PubMed]
  90. Grahame, T.J.; Schlesinger, R.B. Oxidative stress-induced telomeric erosion as a mechanism underlying airborne particulate matter-related cardiovascular disease. Part Fibre. Toxicol. 2012, 9, 21. [Google Scholar] [CrossRef]
  91. Bouthillier, L.; Vincent, R.; Goegan, P.; Adamson, I.Y.; Bjarnason, S.; Stewart, M.; Guénette, J.; Potvin, M.; Kumarathasan, P. Acute effects of inhaled urban particles and ozone: Lung morphology, macrophage activity, and plasma endothelin-1. Am. J. Pathol. 1998, 153, 1873–1884. [Google Scholar] [CrossRef]
  92. Brook, R.D.; Brook, J.R.; Urch, B.; Vincent, R.; Rajagopalan, S.; Silverman, F. Inhalation of fine particulate air pollution and ozone causes acute arterial vasoconstriction in healthy adults. Circulation 2002, 105, 1534–1536. [Google Scholar] [CrossRef]
  93. Jacquet-Lagrèze, M.; Riad, Z.; Hugon-Vallet, E.; Ferraris, A.; Fellahi, J.-L. Left ventricular dysfunction in COVID-19: A diagnostic issue. Anaesth. Crit. Care Pain. Med. 2020. [Google Scholar] [CrossRef]
  94. Chen, Q.; Xu, L.; Dai, Y.; Ling, Y.; Mao, J.; Qian, J.; Zhu, W.; Di, W.; Ge, J. Cardiovascular manifestations in severe and critical patients with COVID-19. Clin. Cardiol. 2020. [Google Scholar] [CrossRef]
  95. Suwa, T.; Hogg, J.C.; Quinlan, K.B.; Ohgami, A.; Vincent, R.; van Eeden, S.F. Particulate air pollution induces progression of atherosclerosis. J. Am. Coll. Cardiol. 2002, 39, 935–942. [Google Scholar] [CrossRef]
  96. DeMeo, D.L.; Zanobetti, A.; Litonjua, A.A.; Coull, B.A.; Schwartz, J.; Gold, D.R. Ambient air pollution and oxygen saturation. Am. J. Respir. Crit. Care Med. 2004, 170, 383–387. [Google Scholar] [CrossRef] [PubMed]
  97. Huertas, A.; Montani, D.; Savale, L.; Pichon, J.; Tu, L.; Parent, F.; Guignabert, C.; Humbert, M. Endothelial cell dysfunction: A major player in SARS-CoV-2 infection (COVID-19)? Eur. Respir. J. 2020. [Google Scholar] [CrossRef] [PubMed]
  98. Torales, J.; O’Higgins, M.; Castaldelli-Maia, J.M.; Ventriglio, A. The outbreak of COVID-19 coronavirus and its impact on global mental health. Int. J. Soc. Psychiatry 2020, 66, 317–320. [Google Scholar] [CrossRef] [PubMed]
  99. Harper, C.A.; Satchell, L.P.; Fido, D.; Latzman, R.D. Functional Fear Predicts Public Health Compliance in the COVID-19 Pandemic. Int. J. Ment. Health Addict 2020, 1–14. [Google Scholar] [CrossRef]
  100. Ornell, F.; Schuch, J.B.; Sordi, A.O.; Kessler, F.H.P. “Pandemic fear” and COVID-19: Mental health burden and strategies. Braz J. Psychiatry 2020, 42, 232–235. [Google Scholar] [CrossRef] [PubMed]
  101. Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; McIntyre, R.S.; Choo, F.N.; Tran, B.; Ho, R.; Sharma, V.K.; et al. A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain Behav. Immun. 2020, 87, 40–48. [Google Scholar] [CrossRef]
  102. Cao, W.; Fang, Z.; Hou, G.; Han, M.; Xu, X.; Dong, J.; Zheng, J. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020, 287, 112934. [Google Scholar] [CrossRef]
  103. Finset, A.; Bosworth, H.; Butow, P.; Gulbrandsen, P.; Hulsman, R.L.; Pieterse, A.H.; Street, R.; Tschoetschel, R.; van Weert, J. Effective health communication—A key factor in fighting the COVID-19 pandemic. Patient Educ. Couns. 2020, 103, 873–876. [Google Scholar] [CrossRef]
  104. Lee, S.M.; Kang, W.S.; Cho, A.-R.; Kim, T.; Park, J.K. Psychological impact of the 2015 MERS outbreak on hospital workers and quarantined hemodialysis patients. Compr. Psychiatry 2018, 87, 123–127. [Google Scholar] [CrossRef]
  105. Park, J.-S.; Lee, E.-H.; Park, N.-R.; Choi, Y.H. Mental Health of Nurses Working at a Government-designated Hospital During a MERS-CoV Outbreak: A Cross-sectional Study. Arch Psychiatr. Nurs. 2018, 32, 2–6. [Google Scholar] [CrossRef] [PubMed]
  106. Kang, L.; Li, Y.; Hu, S.; Chen, M.; Yang, C.; Yang, B.X.; Wang, Y.; Hu, J.; Lai, J.; Ma, X.; et al. The mental health of medical workers in Wuhan, China dealing with the 2019 novel coronavirus. Lancet Psychiatry 2020, 7, e14. [Google Scholar] [CrossRef]
  107. Ahorsu, D.K.; Lin, C.-Y.; Imani, V.; Saffari, M.; Griffiths, M.D.; Pakpour, A.H. The Fear of COVID-19 Scale: Development and Initial Validation. Int. J. Ment. Health Addict 2020, 1–9. [Google Scholar] [CrossRef] [PubMed]
  108. Taylor, S.; Landry, C.A.; Paluszek, M.M.; Fergus, T.A.; McKay, D.; Asmundson, G.J.G. Development and initial validation of the COVID Stress Scales. J. Anxiety Disord. 2020, 72, 102232. [Google Scholar] [CrossRef]
  109. Sakib, N.; Bhuiyan, A.K.M.I.; Hossain, S.; Al Mamun, F.; Hosen, I.; Abdullah, A.H.; Sarker, M.A.; Mohiuddin, M.S.; Rayhan, I.; Hossain, M.; et al. Psychometric Validation of the Bangla Fear of COVID-19 Scale: Confirmatory Factor Analysis and Rasch Analysis. Int. J. Ment. Health Addict 2020, 1–12. [Google Scholar] [CrossRef]
  110. Reznik, A.; Gritsenko, V.; Konstantinov, V.; Khamenka, N.; Isralowitz, R. COVID-19 Fear in Eastern Europe: Validation of the Fear of COVID-19 Scale. Int. J. Ment. Health Addict 2020, 1–6. [Google Scholar] [CrossRef]
  111. Soraci, P.; Ferrari, A.; Abbiati, F.A.; Del Fante, E.; De Pace, R.; Urso, A.; Griffiths, M.D. Validation and Psychometric Evaluation of the Italian Version of the Fear of COVID-19 Scale. Int. J. Ment. Health Addict 2020, 1–10. [Google Scholar] [CrossRef]
  112. Tzur Bitan, D.; Grossman-Giron, A.; Bloch, Y.; Mayer, Y.; Shiffman, N.; Mendlovic, S. Fear of COVID-19 scale: Psychometric characteristics, reliability and validity in the Israeli population. Psychiatry Res. 2020, 289, 113100. [Google Scholar] [CrossRef]
  113. Mantica, G.; Riccardi, N.; Terrone, C.; Gratarola, A. Non-COVID-19 visits to emergency departments during the pandemic: The impact of fear. Public Health 2020, 183, 40–41. [Google Scholar] [CrossRef]
  114. Metzler, B.; Siostrzonek, P.; Binder, R.K.; Bauer, A.; Reinstadler, S.J. Decline of acute coronary syndrome admissions in Austria since the outbreak of COVID-19: The pandemic response causes cardiac collateral damage. Eur. Heart J. 2020, 41, 1852–1853. [Google Scholar] [CrossRef]
  115. Garcia, S.; Albaghdadi, M.S.; Meraj, P.M.; Schmidt, C.; Garberich, R.; Jaffer, F.A.; Dixon, S.; Rade, J.J.; Tannenbaum, M.; Chambers, J.; et al. Reduction in ST-Segment Elevation Cardiac Catheterization Laboratory Activations in the United States During COVID-19 Pandemic. J. Am. Coll. Cardiol. 2020, 75, 2871–2872. [Google Scholar] [CrossRef] [PubMed]
  116. De Rosa, S.; Spaccarotella, C.; Basso, C.; Calabrò, M.P.; Curcio, A.; Filardi, P.P.; Mancone, M.; Mercuro, G.; Muscoli, S.; Nodari, S.; et al. Società Italiana di Cardiologia and the CCU Academy investigators group. Reduction of hospitalizations for myocardial infarction in Italy in the COVID-19 era. Eur. Heart J. 2020, 41, 2083–2088. [Google Scholar] [CrossRef] [PubMed]
  117. Tam, C.F.; Cheung, K.-S.; Lam, S.; Wong, A.; Yung, A.; Sze, M.; Lam, Y.-M.; Chan, C.; Tsang, T.C.; Tsui, M.; et al. Impact of Coronavirus Disease 2019 (COVID-19) Outbreak on ST-Segment-Elevation Myocardial Infarction Care in Hong Kong, China. Circ. Cardiovasc. Qual. Outcomes 2020, 13, e006631. [Google Scholar] [CrossRef] [PubMed]
  118. Tahsili-Fahadan, P.; Geocadin, R.G. Heart-Brain Axis: Effects of Neurologic Injury on Cardiovascular Function. Circ. Res. 2017, 120, 559–572. [Google Scholar] [CrossRef] [PubMed]
  119. Armbrecht, E.; Shah, A.; Schepman, P.; Shah, R.; Pappadopulos, E.; Chambers, R.; Stephens, J.; Haider, S.; McIntyre, R.S. Economic and humanistic burden associated with noncommunicable diseases among adults with depression and anxiety in the United States. J. Med Econ. 2020, 0, 1–11. [Google Scholar] [CrossRef]
  120. He, C.-J.; Zhu, C.-Y.; Han, B.; Hu, H.-Z.; Wang, S.-J.; Zhai, C.-L.; Hu, H.-L. Association between anxiety and clinical outcomes in Chinese patients with myocardial infarction in the absence of obstructive coronary artery disease. Clin. Cardiol. 2020. [Google Scholar] [CrossRef]
  121. Pimple, P.; Lima, B.B.; Hammadah, M.; Wilmot, K.; Ramadan, R.; Levantsevych, O.; Sullivan, S.; Kim, J.H.; Kaseer, B.; Shah, A.J.; et al. Psychological Distress and Subsequent Cardiovascular Events in Individuals With Coronary Artery Disease. J. Am. Heart Assoc. 2019, 8, e011866. [Google Scholar] [CrossRef]
  122. Stewart, R.A.H.; Colquhoun, D.M.; Marschner, S.L.; Kirby, A.C.; Simes, J.; Nestel, P.J.; Glozier, N.; O’Neil, A.; Oldenburg, B.; White, H.D.; et al. LIPID Study Investigators.. Persistent psychological distress and mortality in patients with stable coronary artery disease. Heart 2017, 103, 1860–1866. [Google Scholar] [CrossRef]
  123. Lu, W.; Wang, H.; Lin, Y.; Li, L. Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study. Psychiatry Res. 2020, 288, 112936. [Google Scholar] [CrossRef]
  124. Birkmeyer, J.D.; Barnato, A.; Birkmeyer, N.; Bessler, R.; Skinner, J. The Impact of The COVID-19 Pandemic On Hospital Admissions In The United States. Health Aff. (Millwood) 2020. [Google Scholar] [CrossRef]
  125. Woolf, S.H.; Chapman, D.A.; Sabo, R.T.; Weinberger, D.M.; Hill, L. Excess Deaths From COVID-19 and Other Causes, March-April 2020. JAMA 2020, 324, 510–513. [Google Scholar] [CrossRef] [PubMed]
  126. Wang, Y.; McKee, M.; Torbica, A.; Stuckler, D. Systematic literature review on the spread of health-related misinformation on social media. Soc. Sci. Med. 2019, 240, 112552. [Google Scholar] [CrossRef] [PubMed]
  127. Folli, S. Covid-19 e qualità dell’aria nel bacino padano. Available online: https://www.snpambiente.it/2020/06/19/covid-19-e-qualita-dellaria-nel-bacino-padano-2/ (accessed on 4 July 2020).
  128. Advani, I.; Gunge, D.; Banks, S.; Mehta, S.; Park, K.; Patel, M.; Malhotra, A.; Crotty Alexander, L.E. Is Increased Sleep Responsible for Reductions in Myocardial Infarction During the COVID-19 Pandemic? Am. J. Cardiol. 2020, 131, 128–130. [Google Scholar] [CrossRef] [PubMed]

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