Sandbox:SRizvi

Jump to navigation Jump to search



Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1] Associate Editor(s)-in-Chief:

Overview

The Coronavirus disease-2019 (COVID-19), is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 forms a distinct lineage with Bat-SARS-like coronaviruses ( The virus is closely related (96.3%) to bat coronavirus RaTG13, based on phylogenetic analysis) that belong to the order Nidovirales, family Coronaviridae, genus Betacoronavirus, and subgenus Sarbecovirus [1]. Coronaviruses are enveloped, single-stranded RNA viruses that can infect a wide range of hosts including avian, wild, domestic mammalian species, and humans. Coronaviruses are well known for their ability to mutate rapidly, alter tissue tropism, cross the species barrier, and adapt to different epidemiological situations.[2] Six human coronaviruses have been reported since the 1960s; OC43, 229E, NL63, HKU1, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV.

First case of COVID-19 was reported in Wuhan, Hubei province, China, in December 2019, associated with the Huanan Seafood Wholesale Market. On March 11, 2020 the Novel Coronavirus Disease, COVID-19, was declared a pandemic by the World Health Organization


Taxonomy

  • SARS-CoV-2 belong to the order Nidovirale, Family Coronaviridae.
  • Coronaviridae is classified into two subfamilies.
  • Subfamily Torovirinae and Subfamily Coronavirinae
  • Coronavirinae is further classified on the basis of phylogenetic analysis and genome structure into four genera:
    • Alphacoronavirus (αCoV).
    • Betacoronavirus (βCoV).
    • Gammacoronavirus (γCoV).
    • Deltacoronavirus (δCoV), which contain 17, 12, 2, and 7 unique species, respectively (ICTV 2018).
  • CoV-2 falls under Batacoronavirus.

Biology


Structure

Coronaviruses are enveloped, icosahedral symmetric particles, approximately 80–220 nm in diameter containing a non-segmented, single-strand, positive-sense RNA genome of about 26–32 kb in size. [3]

Corona in Latin means crown, and this name was attributed to the virus due to the presence of spike projections from the virus envelope that give it the shape of a crown under the electron microscope; Nido means nest and refers to the ability of the viruses of this order to make a nested set of subgenomic mRNA

ENVELOPE:


Structural Proteins

  • Spike (S) Protein
    • Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Early studies indicate that SARS-CoV-2 uses the SARS-CoV receptor angiotensin-converting enzyme 2 (ACE2) for entry and transmembrane protease serine 2 (TMPRSS2) for S protein priming.[4]
    • The spike (S) glycoprotein is a type I transmembrane glycoprotein that plays an important role in mediating viral infection. The S proteins consist of two subunits, S1 and S2. The S1 subunit binds the cellular receptor through its receptor-binding domain (RBD), followed by conformational changes in the S2 subunit, which allows the fusion peptide to insert into the host target cell membrane.[5]
  • Envelope (E) Protein
    • The CoV envelope (E) protein is a small, integral membrane protein involved in several aspects of the virus’ life cycle, such as assembly, budding, envelope formation, and pathogenesis. Recent studies have expanded on its structural motifs and topology, its functions as an ion-channelling viroporin, and its interactions with both other CoV proteins and host cell proteins. Recombinant CoVs lacking E exhibit significantly reduced viral titres, crippled viral maturation, or yield propagation incompetent progeny, demonstrating the importance of E in virus production and maturation.[6]
  • Membrane (M) Protein
    • The CoV membrane (M) protein is a component of the viral envelope that plays a central role in virus morphogenesis and assembly via its interactions with other viral proteins. M is located among the S proteins in the virus envelope along with small amounts of E and is the primary driver of the virus budding process. During assembly of the authentic virion M interacts with itself, with the nucleocapsid protein N, with E and with the S protein. The M protein has dominant cellular immunogenicity and elicits a strong humoral response which suggests it could serve as a potential target in vaccine design.[7] [8]
  • Nucleocapsid (N) Protein
    • The primary function of the nucleocapsid (N) protein is to package the viral RNA genome within the viral envelope into a ribonucleoprotein (RNP) complex called the capsid. Ribonucleocapsid packaging is a fundamental part of viral self-assembly and replication. Additionally, the N-protein of the SARS-CoV-2 affects host cell responses and may serve regulatory roles during its viral life cycle.

Corona Virus Life Cycle:

Attachment and Entry:

  • The attachment of the virion to the host cell is associated with the interactions between the S protein and its receptor.
  • The sites of receptor binding domains (RBD) within the S1 region of a coronavirus (SARS-CoV-2) S protein is at the C Terminus.[9]
  • SARS-CoV use angiotensin-converting enzyme 2 (ACE2) as their receptor[10]
  • After binding to the receptor, the virus next step is to gain access to the host cell cytosol.
  • This is generally done by cathepsin,TMPRRS2 or some other protease. This is followed by fusion of the viral and cellular membranes.
  • S protein cleavage occurs at two sites within the S2 portion of the protein, with the first cleavage important for separating the RBD (Receptor binding domain) and fusion domains of the S protein [11] and the second for exposing the fusion peptide (cleavage at S2′).
  • Fusion occurs within acidified endosomes.
  • Cleavage at S2′ exposes a fusion peptide that inserts into the membrane, which is followed by joining of two heptad repeats in S2 forming an antiparallel six-helix bundle[12].The formation of this bundle allows for the mixing of viral and cellular membranes, resulting in fusion and ultimately release of the viral genome into the cytoplasm.

RNA Replicase Protein Expression:

  • The next step in the coronavirus lifecycle is the translation of the replicase gene from the virion genomic RNA.

Tropism


Natural Reservoir


References

Post heart transplant Arrhythmia's

Overview

Historical Perspective

[Disease name] was first discovered by [name of scientist], a [nationality + occupation], in [year]/during/following [event].

The association between [important risk factor/cause] and [disease name] was made in/during [year/event].

In [year], [scientist] was the first to discover the association between [risk factor] and the development of [disease name].

In [year], [gene] mutations were first implicated in the pathogenesis of [disease name].

There have been several outbreaks of [disease name], including -----.

In [year], [diagnostic test/therapy] was developed by [scientist] to treat/diagnose [disease name].

Classification

There is no established system for the classification of [disease name].

OR

[Disease name] may be classified according to [classification method] into [number] subtypes/groups: [group1], [group2], [group3], and [group4].

OR

[Disease name] may be classified into [large number > 6] subtypes based on [classification method 1], [classification method 2], and [classification method 3]. [Disease name] may be classified into several subtypes based on [classification method 1], [classification method 2], and [classification method 3].

OR

Based on the duration of symptoms, [disease name] may be classified as either acute or chronic.

OR

If the staging system involves specific and characteristic findings and features: According to the [staging system + reference], there are [number] stages of [malignancy name] based on the [finding1], [finding2], and [finding3]. Each stage is assigned a [letter/number1] and a [letter/number2] that designate the [feature1] and [feature2].

OR

The staging of [malignancy name] is based on the [staging system].

OR

There is no established system for the staging of [malignancy name].

Pathophysiology

The exact pathogenesis of [disease name] is not fully understood.

OR

It is thought that [disease name] is the result of / is mediated by / is produced by / is caused by either [hypothesis 1], [hypothesis 2], or [hypothesis 3].

OR

[Pathogen name] is usually transmitted via the [transmission route] route to the human host.

OR

Following transmission/ingestion, the [pathogen] uses the [entry site] to invade the [cell name] cell.

OR

[Disease or malignancy name] arises from [cell name]s, which are [cell type] cells that are normally involved in [function of cells].

OR

The progression to [disease name] usually involves the [molecular pathway].

OR

The pathophysiology of [disease/malignancy] depends on the histological subtype.

Causes

Disease name] may be caused by [cause1], [cause2], or [cause3].

OR

Common causes of [disease] include [cause1], [cause2], and [cause3].

OR

The most common cause of [disease name] is [cause 1]. Less common causes of [disease name] include [cause 2], [cause 3], and [cause 4].

OR

The cause of [disease name] has not been identified. To review risk factors for the development of [disease name], click here.

Differentiating ((Page name)) from other Diseases

[Disease name] must be differentiated from other diseases that cause [clinical feature 1], [clinical feature 2], and [clinical feature 3], such as [differential dx1], [differential dx2], and [differential dx3].

OR

[Disease name] must be differentiated from [[differential dx1], [differential dx2], and [differential dx3].

Epidemiology and Demographics

The incidence/prevalence of [disease name] is approximately [number range] per 100,000 individuals worldwide.

OR

In [year], the incidence/prevalence of [disease name] was estimated to be [number range] cases per 100,000 individuals worldwide.

OR

In [year], the incidence of [disease name] is approximately [number range] per 100,000 individuals with a case-fatality rate of [number range]%.

Patients of all age groups may develop [disease name].

OR

The incidence of [disease name] increases with age; the median age at diagnosis is [#] years.

OR

[Disease name] commonly affects individuals younger than/older than [number of years] years of age.

OR

[Chronic disease name] is usually first diagnosed among [age group].

OR

[Acute disease name] commonly affects [age group].

There is no racial predilection to [disease name].

OR

[Disease name] usually affects individuals of the [race 1] race. [Race 2] individuals are less likely to develop [disease name].

[Disease name] affects men and women equally.

OR

[Gender 1] are more commonly affected by [disease name] than [gender 2]. The [gender 1] to [gender 2] ratio is approximately [number > 1] to 1.

The majority of [disease name] cases are reported in [geographical region].

OR

[Disease name] is a common/rare disease that tends to affect [patient population 1] and [patient population 2].

Risk Factors

There are no established risk factors for [disease name].

OR

The most potent risk factor in the development of [disease name] is [risk factor 1]. Other risk factors include [risk factor 2], [risk factor 3], and [risk factor 4].

OR

Common risk factors in the development of [disease name] include [risk factor 1], [risk factor 2], [risk factor 3], and [risk factor 4].

OR

Common risk factors in the development of [disease name] may be occupational, environmental, genetic, and viral.

Screening

There is insufficient evidence to recommend routine screening for [disease/malignancy].

OR

According to the [guideline name], screening for [disease name] is not recommended.

OR

According to the [guideline name], screening for [disease name] by [test 1] is recommended every [duration] among patients with [condition 1], [condition 2], and [condition 3].

Natural History, Complications, and Prognosis

If left untreated, [#]% of patients with [disease name] may progress to develop [manifestation 1], [manifestation 2], and [manifestation 3].

OR

Common complications of [disease name] include [complication 1], [complication 2], and [complication 3].

OR

Prognosis is generally excellent/good/poor, and the 1/5/10-year mortality/survival rate of patients with [disease name] is approximately [#]%.

Diagnosis

Diagnostic Study of Choice

The diagnosis of [disease name] is made when at least [number] of the following [number] diagnostic criteria are met: [criterion 1], [criterion 2], [criterion 3], and [criterion 4].

OR

The diagnosis of [disease name] is based on the [criteria name] criteria, which include [criterion 1], [criterion 2], and [criterion 3].

OR

The diagnosis of [disease name] is based on the [definition name] definition, which includes [criterion 1], [criterion 2], and [criterion 3].

OR

There are no established criteria for the diagnosis of [disease name].

History and Symptoms

The majority of patients with [disease name] are asymptomatic.

OR

The hallmark of [disease name] is [finding]. A positive history of [finding 1] and [finding 2] is suggestive of [disease name]. The most common symptoms of [disease name] include [symptom 1], [symptom 2], and [symptom 3]. Common symptoms of [disease] include [symptom 1], [symptom 2], and [symptom 3]. Less common symptoms of [disease name] include [symptom 1], [symptom 2], and [symptom 3].

Physical Examination

Patients with [disease name] usually appear [general appearance]. Physical examination of patients with [disease name] is usually remarkable for [finding 1], [finding 2], and [finding 3].

OR

Common physical examination findings of [disease name] include [finding 1], [finding 2], and [finding 3].

OR

The presence of [finding(s)] on physical examination is diagnostic of [disease name].

OR

The presence of [finding(s)] on physical examination is highly suggestive of [disease name].

Laboratory Findings

An elevated/reduced concentration of serum/blood/urinary/CSF/other [lab test] is diagnostic of [disease name].

OR

Laboratory findings consistent with the diagnosis of [disease name] include [abnormal test 1], [abnormal test 2], and [abnormal test 3].

OR

[Test] is usually normal among patients with [disease name].

OR

Some patients with [disease name] may have elevated/reduced concentration of [test], which is usually suggestive of [progression/complication].

OR

There are no diagnostic laboratory findings associated with [disease name].

Electrocardiogram

There are no ECG findings associated with [disease name].

OR

An ECG may be helpful in the diagnosis of [disease name]. Findings on an ECG suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

X-ray

There are no x-ray findings associated with [disease name].

OR

An x-ray may be helpful in the diagnosis of [disease name]. Findings on an x-ray suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

OR

There are no x-ray findings associated with [disease name]. However, an x-ray may be helpful in the diagnosis of complications of [disease name], which include [complication 1], [complication 2], and [complication 3].

Echocardiography or Ultrasound

There are no echocardiography/ultrasound findings associated with [disease name].

OR

Echocardiography/ultrasound may be helpful in the diagnosis of [disease name]. Findings on an echocardiography/ultrasound suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

OR

There are no echocardiography/ultrasound findings associated with [disease name]. However, an echocardiography/ultrasound may be helpful in the diagnosis of complications of [disease name], which include [complication 1], [complication 2], and [complication 3].

CT scan

There are no CT scan findings associated with [disease name].

OR

[Location] CT scan may be helpful in the diagnosis of [disease name]. Findings on CT scan suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

OR

There are no CT scan findings associated with [disease name]. However, a CT scan may be helpful in the diagnosis of complications of [disease name], which include [complication 1], [complication 2], and [complication 3].

MRI

There are no MRI findings associated with [disease name].

OR

[Location] MRI may be helpful in the diagnosis of [disease name]. Findings on MRI suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

OR

There are no MRI findings associated with [disease name]. However, a MRI may be helpful in the diagnosis of complications of [disease name], which include [complication 1], [complication 2], and [complication 3].

Other Imaging Findings

There are no other imaging findings associated with [disease name].

OR

[Imaging modality] may be helpful in the diagnosis of [disease name]. Findings on an [imaging modality] suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

Other Diagnostic Studies

There are no other diagnostic studies associated with [disease name].

OR

[Diagnostic study] may be helpful in the diagnosis of [disease name]. Findings suggestive of/diagnostic of [disease name] include [finding 1], [finding 2], and [finding 3].

OR

Other diagnostic studies for [disease name] include [diagnostic study 1], which demonstrates [finding 1], [finding 2], and [finding 3], and [diagnostic study 2], which demonstrates [finding 1], [finding 2], and [finding 3].

Treatment

Medical Therapy

There is no treatment for [disease name]; the mainstay of therapy is supportive care.

OR

Supportive therapy for [disease name] includes [therapy 1], [therapy 2], and [therapy 3].

OR

The majority of cases of [disease name] are self-limited and require only supportive care.

OR

[Disease name] is a medical emergency and requires prompt treatment.

OR

The mainstay of treatment for [disease name] is [therapy].

OR The optimal therapy for [malignancy name] depends on the stage at diagnosis.

OR

[Therapy] is recommended among all patients who develop [disease name].

OR

Pharmacologic medical therapy is recommended among patients with [disease subclass 1], [disease subclass 2], and [disease subclass 3].

OR

Pharmacologic medical therapies for [disease name] include (either) [therapy 1], [therapy 2], and/or [therapy 3].

OR

Empiric therapy for [disease name] depends on [disease factor 1] and [disease factor 2].

OR

Patients with [disease subclass 1] are treated with [therapy 1], whereas patients with [disease subclass 2] are treated with [therapy 2].

Surgery

Surgical intervention is not recommended for the management of [disease name].

OR

Surgery is not the first-line treatment option for patients with [disease name]. Surgery is usually reserved for patients with either [indication 1], [indication 2], and [indication 3]

OR

The mainstay of treatment for [disease name] is medical therapy. Surgery is usually reserved for patients with either [indication 1], [indication 2], and/or [indication 3].

OR

The feasibility of surgery depends on the stage of [malignancy] at diagnosis.

OR

Surgery is the mainstay of treatment for [disease or malignancy].

Primary Prevention

There are no established measures for the primary prevention of [disease name].

OR

There are no available vaccines against [disease name].

OR

Effective measures for the primary prevention of [disease name] include [measure1], [measure2], and [measure3].

OR

[Vaccine name] vaccine is recommended for [patient population] to prevent [disease name]. Other primary prevention strategies include [strategy 1], [strategy 2], and [strategy 3].

Secondary Prevention

There are no established measures for the secondary prevention of [disease name].

OR

Effective measures for the secondary prevention of [disease name] include [strategy 1], [strategy 2], and [strategy 3].

References

  1. Zhou, Peng; Yang, Xing-Lou; Wang, Xian-Guang; Hu, Ben; Zhang, Lei; Zhang, Wei; Si, Hao-Rui; Zhu, Yan; Li, Bei; Huang, Chao-Lin; Chen, Hui-Dong; Chen, Jing; Luo, Yun; Guo, Hua; Jiang, Ren-Di; Liu, Mei-Qin; Chen, Ying; Shen, Xu-Rui; Wang, Xi; Zheng, Xiao-Shuang; Zhao, Kai; Chen, Quan-Jiao; Deng, Fei; Liu, Lin-Lin; Yan, Bing; Zhan, Fa-Xian; Wang, Yan-Yi; Xiao, Geng-Fu; Shi, Zheng-Li (2020). "A pneumonia outbreak associated with a new coronavirus of probable bat origin". Nature. 579 (7798): 270–273. doi:10.1038/s41586-020-2012-7. ISSN 0028-0836.
  2. Decaro N, Mari V, Elia G, Addie DD, Camero M, Lucente MS, Martella V, Buonavoglia C (January 2010). "Recombinant canine coronaviruses in dogs, Europe". Emerging Infect. Dis. 16 (1): 41–7. doi:10.3201/eid1601.090726. PMC 2874359. PMID 20031041.
  3. Weiss SR, Navas-Martin S (December 2005). "Coronavirus pathogenesis and the emerging pathogen severe acute respiratory syndrome coronavirus". Microbiol. Mol. Biol. Rev. 69 (4): 635–64. doi:10.1128/MMBR.69.4.635-664.2005. PMC 1306801. PMID 16339739.
  4. Zhou, Peng; Yang, Xing-Lou; Wang, Xian-Guang; Hu, Ben; Zhang, Lei; Zhang, Wei; Si, Hao-Rui; Zhu, Yan; Li, Bei; Huang, Chao-Lin; Chen, Hui-Dong; Chen, Jing; Luo, Yun; Guo, Hua; Jiang, Ren-Di; Liu, Mei-Qin; Chen, Ying; Shen, Xu-Rui; Wang, Xi; Zheng, Xiao-Shuang; Zhao, Kai; Chen, Quan-Jiao; Deng, Fei; Liu, Lin-Lin; Yan, Bing; Zhan, Fa-Xian; Wang, Yan-Yi; Xiao, Geng-Fu; Shi, Zheng-Li (2020). "A pneumonia outbreak associated with a new coronavirus of probable bat origin". Nature. 579 (7798): 270–273. doi:10.1038/s41586-020-2012-7. ISSN 0028-0836.
  5. Nieva, José; Carrasco, Luis (2015). "Viroporins: Structures and functions beyond cell membrane permeabilization". Viruses. 7 (10): 5169–5171. doi:10.3390/v7102866. ISSN 1999-4915.
  6. Schoeman, Dewald; Fielding, Burtram C. (2019). "Coronavirus envelope protein: current knowledge". Virology Journal. 16 (1). doi:10.1186/s12985-019-1182-0. ISSN 1743-422X.
  7. Siu, Y. L.; Teoh, K. T.; Lo, J.; Chan, C. M.; Kien, F.; Escriou, N.; Tsao, S. W.; Nicholls, J. M.; Altmeyer, R.; Peiris, J. S. M.; Bruzzone, R.; Nal, B. (2008). "The M, E, and N Structural Proteins of the Severe Acute Respiratory Syndrome Coronavirus Are Required for Efficient Assembly, Trafficking, and Release of Virus-Like Particles". Journal of Virology. 82 (22): 11318–11330. doi:10.1128/JVI.01052-08. ISSN 0022-538X.
  8. Tooze J, Tooze S, Warren G (March 1984). "Replication of coronavirus MHV-A59 in sac- cells: determination of the first site of budding of progeny virions". Eur. J. Cell Biol. 33 (2): 281–93. PMID 6325194.
  9. Kubo H, Yamada YK, Taguchi F (September 1994). "Localization of neutralizing epitopes and the receptor-binding site within the amino-terminal 330 amino acids of the murine coronavirus spike protein". J. Virol. 68 (9): 5403–10. PMC 236940. PMID 7520090.
  10. Zhou, Peng; Yang, Xing-Lou; Wang, Xian-Guang; Hu, Ben; Zhang, Lei; Zhang, Wei; Si, Hao-Rui; Zhu, Yan; Li, Bei; Huang, Chao-Lin; Chen, Hui-Dong; Chen, Jing; Luo, Yun; Guo, Hua; Jiang, Ren-Di; Liu, Mei-Qin; Chen, Ying; Shen, Xu-Rui; Wang, Xi; Zheng, Xiao-Shuang; Zhao, Kai; Chen, Quan-Jiao; Deng, Fei; Liu, Lin-Lin; Yan, Bing; Zhan, Fa-Xian; Wang, Yan-Yi; Xiao, Geng-Fu; Shi, Zheng-Li (2020). "A pneumonia outbreak associated with a new coronavirus of probable bat origin". Nature. 579 (7798): 270–273. doi:10.1038/s41586-020-2012-7. ISSN 0028-0836.
  11. Belouzard S, Chu VC, Whittaker GR (April 2009). "Activation of the SARS coronavirus spike protein via sequential proteolytic cleavage at two distinct sites". Proc. Natl. Acad. Sci. U.S.A. 106 (14): 5871–6. doi:10.1073/pnas.0809524106. PMC 2660061. PMID 19321428.
  12. Knuhtsen S, Holst JJ, Schwartz TW, Jensen SL, Nielsen OV (May 1987). "The effect of gastrin-releasing peptide on the endocrine pancreas". Regul. Pept. 17 (5): 269–76. doi:10.1016/0167-0115(87)90284-9. PMID 2885899.

Template:WikiDoc Sources




ACUTE MYOCARDIAL INJURY:


Overview

Acute myocardial injury may be defined across studies as any of the following

Coronavirus disease 2019 (COVID-19) is a rapidly expanding global pandemic which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) , resulting in significant morbidity and mortality. Some hospitalized patients can develop an acute COVID-19 myocardial injury, which can manifest with a variety of clinical presentations but often presents as an acute cardiac injury with cardiomyopathy, ventricular arrhythmias, and hemodynamic instability, acute coronary syndrome, cardiogenic shock. patents with preexisting cardiovascular disease have higher morbidity and mortality.

Historical Perspective

  • One of the first reports of myocardial injury associated with SARS-CoV-2 was a study of 41 patients diagnosed with COVID-19 in Wuhan, China, wherein 5 patients (12%) had a high-sensitivity troponin I above the threshold of 28 pg/mL [5]

Classification

There is no established system for the classification of Acute myocardial injury.

Pathophysiology

  • The pathophysiology of myocardial injury include,
    • Hyperinflammation and cytokine storm mediated through pathologic T-cells and monocytes leading to myocarditis[6]
    • Respiratory failure and hypoxemia resulting in damage to cardiac myocytes[7]
    • Down regulation of ACE2 expression and subsequent protective signaling pathways in cardiac myocytes
    • Hypercoagulability and development of coronary microvascular thrombosis[8]
    • Diffuse endothelial injury and ‘endotheliitis’ in several organs, including the heart as a direct consequence of SARS-CoV-2 viral involvement and/or resulting from host inflammatory response.[9]
    • inflammation and/or stress causing coronary plaque rupture or supply-demand mismatch leading to myocardial ischemia/infarction.[10]
    • Electrolyte imbalances and adverse medication effects may disproportionately challenge a diseased heart, with special consideration for the regimen of hydroxychloroquine and azithromycin treatment due to the potential for QTc prolongation [11]
    • Direct invasion of the cardiac tissue by COVID-19.[12]

Hyperinflammation and cytokine storm:

  • Immune dysregulation, including T cell and immune signaling dysfunction, recognized as an important factor in the pathogenesis of vascular disease, may also adversely affect the body's response to SARS-CoV-2 infection[13]
  • The role of CD4(+)CD25(+)FOXP3(+) regulatory T (TREG) cells in the modulation of inflammation and immunity has received increasing attention. Given the important role of TREG cells in the induction and maintenance of immune homeostasis and tolerance, dysregulation in the generation or function of TREG cells can trigger abnormal immune responses and lead to pathology.
  • Evidence from experimental and clinical studies has indicated that TREG cells might have an important role in protecting against cardiovascular disease, in particular atherosclerosis and abdominal aortic aneurysm.
  • The role of TREG cells is evident in the pathogenesis of a number of cardiovascular diseases, including atherosclerosis, hypertension, ischaemic stroke, abdominal aortic aneurysm, Kawasaki disease, pulmonary arterial hypertension, myocardial infarction and remodelling, postischaemic neovascularization, myocarditis and dilated cardiomyopathy, and heart failure.[14]

Role of ACE Receptor :

  • ACE-2 is a membrane-bound aminopeptidate receptor expressed on the epithelial cells of the lungs, intestines, kidneys and blood vessels. It has important immune and cardiovascular roles. Angiotensin-converting enzyme (ACE) cleaves angiotensin I to generate angiotensin II (Ang II), which binds to and activates AT1R, thus promoting vasoconstriction.
  • ACE-2 cleaves angiotensin II and generates angiotensin 1–7, a powerful vasodilator acting through Mas receptors.
  • SARS-CoV-2 has a spike protein receptor-binding domain, similar to SARS-CoV-1, which interacts with the ACE-2 receptor and acts as the primary functional receptor for pathogenicity and human-to-human transmission.[15] Furthermore, SARS-CoV-2 binding to ACE-2 leads to its down regulation and increases angiotensin II,a pro-inflammatory factor in the lung.
  • This subsequently leads to lower amount of angiotensin 1–7. Thus loss of protective signaling pathway in cardiac myocytes. The detrimental effect of ACE-2 downregulation would impede cardioprotective effects of angiotensin 1–7 leading to increased TNFα production, other cytokines release that can result in acute respiratory syndrome, acute cardiac injury and multiorgan dysfunction.[16]

Causes

  • Acute respiratory distress syndrome. (ARDS)
  • Pneumonia.
  • Hypercoagulability and plaque rupture.
  • Hyperinflammation and cytokine storm.
  • Electrolyte imbalances and adverse medication effects
  • Direct invasion of the cardiac tissue by COVID-19.
  • Myocarditis and myocyte necrosis.

Epidemiology and Demographics

  • A summary of 44,672 COVID-19 cases documented by the Chinese Center for Disease Control and Prevention demonstrated a case fatality rate of 10.5% with comorbid CVD ( cardiovascular disease) compared to a 2.4% overall case fatality rate[17]
  • The frequency of myocardial injury (as reflected by elevation in cardiac troponin levels) is variable among hospitalized patients with COVID-19, with reported frequencies of 7 to 28 percent[18] [19]. Some studies have identified greater frequency and magnitude of troponin elevations in hospitalized patients with more severe disease and worse outcomes [20]
  • In a series of 416 patients with COVID-19 who were hospitalized in Wuhan, China, 19.7 percent had high-sensitivity troponin I (hs-TnI) above the 99th percentile upper reference limit on admission [21]. Patients with this marker of myocardial injury were older and had more comorbidities (including chronic heart failure in 14.6 versus 1.5 percent), greater laboratory abnormalities (including higher levels of C-reactive protein, procalcitonin, and aspartate aminotransferase), more lung radiographic abnormalities, and more complications compared with those without myocardial injury. The mortality rate was also higher in those with myocardial injury (51.2 versus 4.5 percent). The risk of death starting from the time of symptom onset was more than four times higher in patients with evidence of myocardial injury on admission.

Risk Factors

A meta-analysis of 6 studies inclusive of 1,527 patients with COVID-19 examined the prevalence of cardio vascular disease (CVD) and reported the prevalence of hypertension, cardiac and cerebrovascular disease, and diabetes to be 17.1%, 16.4%, and 9.7%, respectively [22]

Screening

  • There is insufficient evidence to recommend routine screening for acute myocardial injury in COVID-19 patients.

Natural History, Complications, and Prognosis

  • The disease also contributes to cardiovascular complications, including
    • Acute coronary syndromes
    • Arrhythmias
    • Myocarditis
    • Pericarditis
    • Heart failure
    • Cardiogenic shock
    • Death.
  • Older patients with preexisting cardiovascular comorbidities and diabetes are prone to develop a higher acuity of illness after contracting SARS-CoV-2 associated with higher risk of myocardial injury and a markedly higher short-term mortality rate.[23]

Diagnosis

Diagnostic Study of Choice

  • Cardiac Biomarkers and Acute Cardiac Injury
    • In the recently published retrospective study of 191 COVID-19 patients from two separate hospitals in China, the incidence of elevation in high-sensitivity cardiac troponin I (cTnI) (>28 pg/ml) was 17%, and it was significantly higher among non-survivors (46% versus 1%, p<0.001).10 Furthermore, elevation of this biomarker was noted to be a predictor of in-hospital death (univariable OR 80.07, 95% CI [10.34–620.36], p<0.0001). The most abrupt increase in cTnI in non-survivors was noted beyond day 16 after the onset of disease. In the same study, the incidence of acute cardiac injury was 17% among all-comers, but significantly higher among non-survivors (59% versus 1%, p<0.0001).[24]
    • CK-MB >2.2 ng/mL
    • Guo et al11 provide additional novel insights that TnT levels are significantly associated with levels of C-reactive protein and N-terminal pro-B-type natriuretic peptide (NT-proBNP), thus linking myocardial injury to severity of inflammation and ventricular dysfunction[25]

History and Symptoms

  • Patients with COVID-19 can present with the typical symptoms and signs of SARS-CoV-2 nfection such as fever, cough, dyspnea, and bilateral infiltrates on chest imaging can present with chest pain, dyspnea, dysarrhythmia, and acute left ventricular dysfunction [26] [27]

Physical Examination

Laboratory Findings

Electrocardiogram

  • The electrocardiogram (ECG) can demonstrate a range of findings
    • In some cases mimicking acute coronary syndrome (ACS).
    • The ECG abnormalities result from myocardial inflammation and include non-specific ST segment-T wave abnormalities.
    • T wave inversion.
    • PR segment and ST segment deviations (depression and elevation)

X-ray

Echocardiography or Ultrasound

CT scan

MRI

Other Imaging Findings

Other Diagnostic Studies

Treatment

Treatment of Acute myocardial injury depends upon the complication the

References

  1. Driggin, Elissa; Madhavan, Mahesh V.; Bikdeli, Behnood; Chuich, Taylor; Laracy, Justin; Biondi-Zoccai, Giuseppe; Brown, Tyler S.; Der Nigoghossian, Caroline; Zidar, David A.; Haythe, Jennifer; Brodie, Daniel; Beckman, Joshua A.; Kirtane, Ajay J.; Stone, Gregg W.; Krumholz, Harlan M.; Parikh, Sahil A. (2020). "Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic". Journal of the American College of Cardiology. 75 (18): 2352–2371. doi:10.1016/j.jacc.2020.03.031. ISSN 0735-1097.
  2. Li, Dongze; Chen, You; Jia, Yu; Tong, Le; Tong, Jiale; Wang, Wei; Liu, Yanmei; Wan, Zhi; Cao, Yu; Zeng, Rui (2020). "SARS-CoV-2-Induced Immune Dysregulation and Myocardial Injury Risk in China: Insights from the ERS-COVID-19 Study". Circulation Research. doi:10.1161/CIRCRESAHA.120.317070. ISSN 0009-7330.
  3. Driggin, Elissa; Madhavan, Mahesh V.; Bikdeli, Behnood; Chuich, Taylor; Laracy, Justin; Biondi-Zoccai, Giuseppe; Brown, Tyler S.; Der Nigoghossian, Caroline; Zidar, David A.; Haythe, Jennifer; Brodie, Daniel; Beckman, Joshua A.; Kirtane, Ajay J.; Stone, Gregg W.; Krumholz, Harlan M.; Parikh, Sahil A. (2020). "Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic". Journal of the American College of Cardiology. 75 (18): 2352–2371. doi:10.1016/j.jacc.2020.03.031. ISSN 0735-1097.
  4. Driggin, Elissa; Madhavan, Mahesh V.; Bikdeli, Behnood; Chuich, Taylor; Laracy, Justin; Biondi-Zoccai, Giuseppe; Brown, Tyler S.; Der Nigoghossian, Caroline; Zidar, David A.; Haythe, Jennifer; Brodie, Daniel; Beckman, Joshua A.; Kirtane, Ajay J.; Stone, Gregg W.; Krumholz, Harlan M.; Parikh, Sahil A. (2020). "Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic". Journal of the American College of Cardiology. 75 (18): 2352–2371. doi:10.1016/j.jacc.2020.03.031. ISSN 0735-1097.
  5. Huang, Chaolin; Wang, Yeming; Li, Xingwang; Ren, Lili; Zhao, Jianping; Hu, Yi; Zhang, Li; Fan, Guohui; Xu, Jiuyang; Gu, Xiaoying; Cheng, Zhenshun; Yu, Ting; Xia, Jiaan; Wei, Yuan; Wu, Wenjuan; Xie, Xuelei; Yin, Wen; Li, Hui; Liu, Min; Xiao, Yan; Gao, Hong; Guo, Li; Xie, Jungang; Wang, Guangfa; Jiang, Rongmeng; Gao, Zhancheng; Jin, Qi; Wang, Jianwei; Cao, Bin (2020). "Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China". The Lancet. 395 (10223): 497–506. doi:10.1016/S0140-6736(20)30183-5. ISSN 0140-6736.
  6. Wei, Haiming; Xu, Xiaoling; Tian, Zhigang; Sun, Rui; Qi, Yingjie; Zhao, Changcheng; Wang, Dongsheng; Zheng, Xiaohu; Fu, Binqing; Zhou, Yonggang (2020). "Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients". National Science Review. 7 (6): 998–1002. doi:10.1093/nsr/nwaa041. ISSN 2095-5138.
  7. Kubasiak, L. A.; Hernandez, O. M.; Bishopric, N. H.; Webster, K. A. (2002). "Hypoxia and acidosis activate cardiac myocyte death through the Bcl-2 family protein BNIP3". Proceedings of the National Academy of Sciences. 99 (20): 12825–12830. doi:10.1073/pnas.202474099. ISSN 0027-8424.
  8. Han, Huan; Yang, Lan; Liu, Rui; Liu, Fang; Wu, Kai-lang; Li, Jie; Liu, Xing-hui; Zhu, Cheng-liang (2020). "Prominent changes in blood coagulation of patients with SARS-CoV-2 infection". Clinical Chemistry and Laboratory Medicine (CCLM). 58 (7): 1116–1120. doi:10.1515/cclm-2020-0188. ISSN 1437-4331.
  9. Tavazzi, Guido; Pellegrini, Carlo; Maurelli, Marco; Belliato, Mirko; Sciutti, Fabio; Bottazzi, Andrea; Sepe, Paola Alessandra; Resasco, Tullia; Camporotondo, Rita; Bruno, Raffaele; Baldanti, Fausto; Paolucci, Stefania; Pelenghi, Stefano; Iotti, Giorgio Antonio; Mojoli, Francesco; Arbustini, Eloisa (2020). "Myocardial localization of coronavirus in COVID‐19 cardiogenic shock". European Journal of Heart Failure. 22 (5): 911–915. doi:10.1002/ejhf.1828. ISSN 1388-9842.
  10. Zhou, Fei; Yu, Ting; Du, Ronghui; Fan, Guohui; Liu, Ying; Liu, Zhibo; Xiang, Jie; Wang, Yeming; Song, Bin; Gu, Xiaoying; Guan, Lulu; Wei, Yuan; Li, Hui; Wu, Xudong; Xu, Jiuyang; Tu, Shengjin; Zhang, Yi; Chen, Hua; Cao, Bin (2020). "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study". The Lancet. 395 (10229): 1054–1062. doi:10.1016/S0140-6736(20)30566-3. ISSN 0140-6736.
  11. Bansal, Manish (2020). "Cardiovascular disease and COVID-19". Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 14 (3): 247–250. doi:10.1016/j.dsx.2020.03.013. ISSN 1871-4021.
  12. Tavazzi, Guido; Pellegrini, Carlo; Maurelli, Marco; Belliato, Mirko; Sciutti, Fabio; Bottazzi, Andrea; Sepe, Paola Alessandra; Resasco, Tullia; Camporotondo, Rita; Bruno, Raffaele; Baldanti, Fausto; Paolucci, Stefania; Pelenghi, Stefano; Iotti, Giorgio Antonio; Mojoli, Francesco; Arbustini, Eloisa (2020). "Myocardial localization of coronavirus in COVID‐19 cardiogenic shock". European Journal of Heart Failure. 22 (5): 911–915. doi:10.1002/ejhf.1828. ISSN 1388-9842.
  13. Meng, Xiao; Yang, Jianmin; Dong, Mei; Zhang, Kai; Tu, Eric; Gao, Qi; Chen, Wanjun; Zhang, Cheng; Zhang, Yun (2015). "Regulatory T cells in cardiovascular diseases". Nature Reviews Cardiology. 13 (3): 167–179. doi:10.1038/nrcardio.2015.169. ISSN 1759-5002.
  14. Meng, Xiao; Yang, Jianmin; Dong, Mei; Zhang, Kai; Tu, Eric; Gao, Qi; Chen, Wanjun; Zhang, Cheng; Zhang, Yun (2015). "Regulatory T cells in cardiovascular diseases". Nature Reviews Cardiology. 13 (3): 167–179. doi:10.1038/nrcardio.2015.169. ISSN 1759-5002.
  15. Wan, Yushun; Shang, Jian; Graham, Rachel; Baric, Ralph S.; Li, Fang; Gallagher, Tom (2020). "Receptor Recognition by the Novel Coronavirus from Wuhan: an Analysis Based on Decade-Long Structural Studies of SARS Coronavirus". Journal of Virology. 94 (7). doi:10.1128/JVI.00127-20. ISSN 0022-538X.
  16. Zhou, Peng; Yang, Xing-Lou; Wang, Xian-Guang; Hu, Ben; Zhang, Lei; Zhang, Wei; Si, Hao-Rui; Zhu, Yan; Li, Bei; Huang, Chao-Lin; Chen, Hui-Dong; Chen, Jing; Luo, Yun; Guo, Hua; Jiang, Ren-Di; Liu, Mei-Qin; Chen, Ying; Shen, Xu-Rui; Wang, Xi; Zheng, Xiao-Shuang; Zhao, Kai; Chen, Quan-Jiao; Deng, Fei; Liu, Lin-Lin; Yan, Bing; Zhan, Fa-Xian; Wang, Yan-Yi; Xiao, Geng-Fu; Shi, Zheng-Li (2020). "A pneumonia outbreak associated with a new coronavirus of probable bat origin". Nature. 579 (7798): 270–273. doi:10.1038/s41586-020-2012-7. ISSN 0028-0836.
  17. Bodini G, Demarzo MG, Casagrande E, De Maria C, Kayali S, Ziola S, Giannini EG (May 2020). "Concerns related to COVID-19 pandemic among patients with inflammatory bowel disease and its influence on patient management". Eur. J. Clin. Invest. 50 (5): e13233. doi:10.1111/eci.13233. PMC 7235524 Check |pmc= value (help). PMID 32294238 Check |pmid= value (help).
  18. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, Gong W, Liu X, Liang J, Zhao Q, Huang H, Yang B, Huang C (March 2020). "Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China". JAMA Cardiol. doi:10.1001/jamacardio.2020.0950. PMC 7097841 Check |pmc= value (help). PMID 32211816 Check |pmid= value (help).
  19. Lippi G, Lavie CJ, Sanchis-Gomar F (March 2020). "Cardiac troponin I in patients with coronavirus disease 2019 (COVID-19): Evidence from a meta-analysis". Prog Cardiovasc Dis. doi:10.1016/j.pcad.2020.03.001. PMC 7127395 Check |pmc= value (help). PMID 32169400 Check |pmid= value (help).
  20. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, Gong W, Liu X, Liang J, Zhao Q, Huang H, Yang B, Huang C (March 2020). "Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China". JAMA Cardiol. doi:10.1001/jamacardio.2020.0950. PMC 7097841 Check |pmc= value (help). PMID 32211816 Check |pmid= value (help).
  21. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, Gong W, Liu X, Liang J, Zhao Q, Huang H, Yang B, Huang C (March 2020). "Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China". JAMA Cardiol. doi:10.1001/jamacardio.2020.0950. PMC 7097841 Check |pmc= value (help). PMID 32211816 Check |pmid= value (help).
  22. Li, Bo; Yang, Jing; Zhao, Faming; Zhi, Lili; Wang, Xiqian; Liu, Lin; Bi, Zhaohui; Zhao, Yunhe (2020). "Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China". Clinical Research in Cardiology. 109 (5): 531–538. doi:10.1007/s00392-020-01626-9. ISSN 1861-0684.
  23. Guo, Tao; Fan, Yongzhen; Chen, Ming; Wu, Xiaoyan; Zhang, Lin; He, Tao; Wang, Hairong; Wan, Jing; Wang, Xinghuan; Lu, Zhibing (2020). "Cardiovascular Implications of Fatal Outcomes of Patients With Coronavirus Disease 2019 (COVID-19)". JAMA Cardiology. doi:10.1001/jamacardio.2020.1017. ISSN 2380-6583.
  24. Zhou, Fei; Yu, Ting; Du, Ronghui; Fan, Guohui; Liu, Ying; Liu, Zhibo; Xiang, Jie; Wang, Yeming; Song, Bin; Gu, Xiaoying; Guan, Lulu; Wei, Yuan; Li, Hui; Wu, Xudong; Xu, Jiuyang; Tu, Shengjin; Zhang, Yi; Chen, Hua; Cao, Bin (2020). "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study". The Lancet. 395 (10229): 1054–1062. doi:10.1016/S0140-6736(20)30566-3. ISSN 0140-6736.
  25. Guo, Tao; Fan, Yongzhen; Chen, Ming; Wu, Xiaoyan; Zhang, Lin; He, Tao; Wang, Hairong; Wan, Jing; Wang, Xinghuan; Lu, Zhibing (2020). "Cardiovascular Implications of Fatal Outcomes of Patients With Coronavirus Disease 2019 (COVID-19)". JAMA Cardiology. doi:10.1001/jamacardio.2020.1017. ISSN 2380-6583.
  26. Wu, Zunyou; McGoogan, Jennifer M. (2020). "Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China". JAMA. 323 (13): 1239. doi:10.1001/jama.2020.2648. ISSN 0098-7484.
  27. Ruan, Qiurong; Yang, Kun; Wang, Wenxia; Jiang, Lingyu; Song, Jianxin (2020). "Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China". Intensive Care Medicine. 46 (5): 846–848. doi:10.1007/s00134-020-05991-x. ISSN 0342-4642.

COVID 19