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Ischemic stroke and COVID-19 infection — a review of clinical case reports



Despite the availability of vaccines, COVID-19 remains of global concern with seasonal peak in cases across the globe and considering its link to brain pathologies such as stroke. Our aim was to characterize the presence of comorbidities and how the time of COVID-19 infection relative to stroke onset impacts outcomes.


We reviewed 68 cases of COVID-19 in hospitalized patients with acute stroke. We searched for published case reports using PubMed and Google Scholar limited to publications written in English from September 2019 to December 2022. We excluded systematic reviews from our search result and categorized individual cases into four groups: COVID-19-induced stroke (CIS, those who had COVID-19 shortly before stroke onset), stroke then COVID-19 (STC, those who had COVID-infection immediately following stroke onset), COVID-19 and stroke (CAS, those who presented with both stroke and COVID-19 infection). The following information was extracted and analyzed from included search reports: age, NIHSS score, type of stroke, mortality, functional outcomes, and comorbidities listed.


Most patients who were reported for admission stroke were of middle age, and only more aged individuals presented with concurrent stroke onset and COVID-19 infection. Hypertension was the most prevalent comorbidity across all four groups, especially among the STC group. The poorest functional outcomes and highest inhospital mortality were observed among the STC group when compared to other groups. The concurrent presentation of stroke and COVID-19 infection had the least impact on functional outcome, but COVID-19 infection during acute stroke hospitalization may worsen clinical outcomes especially among individuals with hypertension.


The association of stroke incidence with acute SARS-CoV-2 virus (i.e., COVID-19) infection has been reported since the early days of the pandemic. In Wuhan, China, an early retrospective case study with data collected between January and February 2020 showed that severe infection with COVID-19 led to a higher prevalence of stroke when compared to milder infections of COVID-19 [1]. Similarly, a recent report showed 52% increased risk of stroke among COVID-19 survivors [2]. One systematic review which aimed at shedding mechanistic insight showed a consensus that acute inflammation during infection may be the pathogenic cause for stroke among individuals who were diagnosed with COVID-19 [3]. Also, activation of the fibrinolytic system, interfering with hemostasis, after COVID-19 infection could occur and may lead to stroke. The virus has an affinity towards ACE2 receptors which interferes with the renin-angiotensin system and increases the likelihood of stroke in COVID-19 patients [4]. While there are potential mechanisms pointing to the incidence of stroke among individuals infected with COVID-19 survivors, underlying causative mechanism(s) remain unaddressed.

Although today the world is less terrified of COVID-19 compared to the early months of its emergence, the regional and seasonal case uptakes across the world are unwavering. In addition, since the global population at risk of stroke is on the rise due to the increasing aging population, the stroke impact of COVID-19 warrants some research consideration and increased understanding. Importantly, it is unclear whether and how poststroke infection with COVID-19 impacts clinical outcomes.

The present review evaluated 68 individual cases of stroke and COVID-19 infections in patients. To determine a research direction, our objective of this study was to explore an association between the risk factors of stroke, clinically relevant outcomes, and the sequence of stroke/COVID-19 incidence by characterizing age distribution, mortality, functional outcome, and the presence of comorbidities/risk factors for stroke among individuals who were hospitalized.


PubMed and Google Scholar were used to search for case reports with the following search terms: Search terms were as follows: COVID-19 and stroke; comorbidities, stroke, and COVID-19; COVID-19 mechanisms; and stroke mechanisms for a period of 2 months. Systematic reviews were excluded from included results. Once the reports were collated, the following variables were extrapolated from the reports: patients’ age, the number of individual patients who were hospitalized for COVID-19 symptoms but developed symptoms of stroke during hospital stay more than 24 h later — termed COVID-induced stroke (CIS) cohorts, the number individuals who presented to the hospital with stroke symptoms but developed COVID-19 infection more than 24 h later, during hospitalization — termed stroke and then COVID (STC) cohorts, the number of patients who presented with concurrent (no more than 24 h apart) COVID-19 infection and stroke symptoms — termed COVID and stroke (CAS) cohorts, the National Institute of Health Stroke Scale (NIHSS) score, type of stroke, mortality, functional outcomes, and listed comorbidities/stroke risk factors reported for each individual (such as hypertension, diabetes, atrial fibrillation, smoking, renal failure and cancer) was accounted for, where possible.

Data and statistical analysis

Patients were classified into three main cohorts based on their stroke-COVID-19 occurrence, i.e., CIS, STC, and CAS as well as based on their age, i.e., young (≤ 49 years old), middle aged (50–69 years old), and aged (≥ 70 years old).


Patient distribution by cohort classification, age, and sex

A total number of 68 cases (46 males and 22 females) were included for data evaluation. The overall observation of all patient data revealed that CIS cohorts had the largest case number with 55 patients (40 males and 15 females), STC cohorts with 7 patients (1 male and 6 females), and CAS cohorts with 6 patients (5 males and 1 female, Fig. 1).

Fig. 1
figure 1

Distribution of stroke type by gender. Female patients had higher proportion of the patients who got stroke and then COVID, whereas male patients had a higher proportion of patient who got COVID and stroke within 24 h

Patient data were grouped into three age categories: young (below 50 years), middle aged (50 ≤ 70 years), and old (> 70 years). Across all three age groups, nearly half (47%) of the patient data were reports on middle-aged patients (32/68). Old patients made up 32% (22/68) of the total population, while 21% (14/68) of the total population were young patients. For some cases, only a range of age (rather than an exact age) could be extrapolated from the original reports. Although CIS had the highest number of patients (n = 55) compared to the other two cohorts, the majority of reported cases were of middle-aged individuals (49.09% (27/55), old patients represented 29.09% (16/55), and 21.82% (12/55) were young patients. For the CIS distribution, 72.7% (40/55) and 27.3% (15/55) were male and female patients respectively. Young adults had 9 males and 3 females, middle-aged patients had 20 males and 7 females, while old patients were 11 males and 5 females. STC and CAS cohorts had comparable sample sizes (i.e., n = 7 and n = 6, respectively). Also, the distribution of all age groups is almost similar. STC cohorts had 14.29% (1/7) of young patients, 42.86% (3/7) of middle-aged patients, and 42.86% (3/7) of old patients, while CAS had 16.7% (1/6) of young patients, 33.3% (3/6) of middle-aged patients, and 50% (3/7) of old patients (Fig. 2). There was only one male (middle aged) among the STC cohorts of seven patients. CAS cohorts had five males (one young adult, two middle aged, and two old) and one (old) female patient (Fig. 2).

Fig. 2
figure 2

Age breakdown among stroke categories. Most of the patients were in the middle age category. Older patients made up a higher proportion of COVID and stroke within 24 h. Middle-aged patients made up a high proportion of COVID followed by stroke cases

Hypertension and diabetes are the prominent comorbidities among cohorts

The majority of the cases recorded at least one comorbidity at 82.09% (55/67). One patient had no comorbidities listed but was not defined as having zero comorbidities so that patient was excluded from comorbidity assessment.

Hypertension was the most frequently reported comorbidity among the patients at 53.73% (36/67) (Fig. 3). STC cohorts have the highest percentage of hypertension reports per case when compared to a similar distribution among CIS and CAS cohorts at 52.73% and 50%, respectively (Fig. 3). The second most reported comorbidity was diabetes at 32.84% (22/67). CIS cohorts have a higher representation at 36.36% when compared to the similar frequency among STC and CAS cohorts at 16.67% (Fig. 3). Atrial fibrillation represents the third most frequently reported comorbidity at 10.45% (7/67) (Fig. 3). CAS cohorts at 16.67% had more cases of atrial fibrillation than CIS cohorts at 10.91% (Fig. 3). There was no report of atrial fibrillation for STC cohorts. Chronic kidney disease and cancer were the other comorbidities reported at 5.97% (4/67) and 2.99% (2/67), respectively. While there were no reports of kidney failure nor cancer for STC and CAS cohorts, only CIS cohorts had a 7.27% and 3.64% of kidney failure and cancer cases, respectively (Fig. 3).

Fig. 3
figure 3

Distribution of comorbidities among categories of stroke. The largest proportion of patients had hypertension among all categories. This was followed by diabetes and then atrial fibrillation or afib

Although smoking is not a comorbidity of stroke, it predicts cardiovascular disease and stroke, particularly due to its association with increased platelet activation and aggregation and circulating fibrinogen. Smoking was reported for some patients at 5.97% (4/67) with STC and CAS cohorts having comparable distribution at 16.67%, while smoking was recorded for 3.64% of CIS cohorts.

COVID exacerbates stroke outcomes but does not impact mortality rates

Across all three cohorts, 41 of the 68 cases had records of functional outcome measured by NIHSS score. NIHSS score was higher among STC cohorts 22 ± 9.70 when compared to CIS cohorts (17.03 ± 8.81) and CAS cohorts (8.33 ± 5.51) (Fig. 4). However, while STC cohorts experienced the highest frequency of mortality at 57.14%, 50% mortality was recorded for CAS cohorts, and 43.64% mortality was recorded for CIS cohorts (Fig. 5).

Fig. 4
figure 4

NIHSS score among categories. Patients with stroke followed by COVID had the highest NIHSS scores on average

Fig. 5
figure 5

Mortality rate among categories of stroke. Stroke followed by COVID had the highest rate of mortality among the categories


With the largest category by a large margin being CIS, it shows that the typical presentation of COVID-19 and stroke in this case series is a patient being hospitalized for COVID-19 and then developing stroke symptoms later. However, with the other two categories still having seven and six patients respectively in the case series, those etiologies for stroke and COVID-19 cannot wholly be disregarded. According to this distribution, the age groups in this series skew more towards patients above 50 which is also a common risk factor for COVID-19-induced stroke. One meta-analysis of over 27,676 patients found that the average age of among the 103 COVID patients with ischemic stroke was 68.8 compared to 54.4 for those with COVID and no stroke [5]. Another analysis of 21,073 patients from the American Heart Association COVID-19 Cardiovascular Disease Registry showed that among the 140 patients with COVID, 67% were male and 33% female which is similar to the gender distribution among the 68 cases [6]. The mortality rate for 68 patients was 47.69% (31/68). In the other studies, this value was 19.4% among the Cerner Real-World Data and 37.5% for the AHA data [5, 6]. There is a greater mortality among the cases than the data from the two meta-analyses which may indicate that this dataset consists of more severe episodes of strokes and COVID-19. This is further supported by the average NIHSS score being 16.87 for our dataset and median of 11 for AHA data [6].

A general data sheet per category of stroke-COVID-19 occurrence was created that had the data of all 68 patients with data listed above. Then we created data sheets for the individual categories CIS, STC, and CAS. Finally, we created charts that compared all the categories together and looked at distribution of comorbidities among categories of stroke, gender breakdown among categories of stroke, and age breakdown among categories of stroke.

The comorbidity data for all 68 cases was first analyzed and recorded under the general category. In the Cerner data, hypertension was 84.5%, diabetes was 56.3%, and atrial fibrillation was 28.2%.

Prevalence of stroke in the United States

In the “AHA Report on Heart Disease and Stroke Statistics,” the annual estimate for prevalence of stroke was more than 795,000 people in the United States with 610,000 being first or new strokes [7]. A total of 87% of strokes were ischemic strokes, and this led to a total for stroke-related costs amounting to US $53 billion between 2017 and 2018 [7]. Risk of first stroke is twice as common in African Americans than for Caucasians [7]. Risk of stroke increases with age; however, 38% people hospitalized with stroke were less than 65 years old [7]. The 2017 NIS data showed a mortality rate of stroke at 3.1% [8].

World economic and social burden of stroke

In terms of global data, in 2017, there were 24.1 million stroke cases. This led 15.7 million additional disability-adjusted life years (DALYs) and 700,00 more stroke-related deaths compared to 2016 data [9, 10].

Current issues with COVID

The most recent WHO report at the time of writing of this article showed that global cases remained stable between September 12 and 18, 2022. A total of 3.2 million new cases were reported, and 9800 deaths were reported [11]. As of September 18, there have been 609 million confirmed cases and 6.5 million deaths globally [11]. There were decreases or stable numbers in the amount of COVID cases across all six WHO regions [11]. The most prevalent variant is a descendent of the Omicron variant BA.5 with 76.6% global prevalence and next is BA.4.X with 7.5% prevalence. There are six Omicron variants that are being monitored due to various mutations that are affecting the spike protein, receptor-binding domain [11]. The current data on the vaccines continues to show continued reduction in vaccine effectiveness against the Omicron variant against severe disease, symptomatic disease, and infection compared to initial COVID strains [11].

Inflammatory cascade of COVID

There is evidence that suggests COVID induces a hypercoagulable state in the body, which can be seen with elevated D-dimer, fibrinogen, factor VIII, von Willebrand factor, decreased antithrombin, and TEG results [12]. There are other factors that may contribute to the hypercoagulable state in severe COVID hospitalizations (immobilization, mechanical ventilation, central venous access devices, and nutritional deficiencies) [12]. However, this discussion will focus more on the connection between COVID-induced inflammation and thrombosis. In the COVID-induced pro-inflammatory state, there have been high levels of C-reactive protein, lactate dehydrogenase, ferritin, IL-6, and D-dimer levels reported [13]. Current research believes that COVID-19 enters the alveolar epithelium through the ACE2 receptors and initiates the pro-inflammatory response [14]. There are many parts of the pro-inflammatory response that there is ongoing literature with regard to COVID.

First, there is evidence of localized intravascular coagulopathy in the pulmonary vasculature due to the severe alveolar inflammation which progresses to a more systemic form later [14, 15]. This is also correlated with many COVID-19 patients meeting the threshold for disseminated intravascular coagulopathy [14, 16].

Next, there is evidence of excessive cytokine release in younger patients with severe illness and no preexisting conditions. In these patients, cytokines could cause thrombosis by activation neutrophils, monocytes, and endothelium [14].

Endotheliitis is another proposed mechanism for the pro-thrombotic state in COVID. Endothelial activation has been seen in COVID patients and can be caused by cytokines, complement, or direct infection of endothelial cells by SARS-CoV-2 [17]. The evidence of endothelitiis in COVID patients is supported by elevated levels VWF and FVIII [14, 18].

Some studies of ICU patients with COVID-19 have shown increased populations of CD14 + and CD16 + monocytes that produce IL-6 and TNF-alpha in the blood [19, 20]. Specifically, monocytes could induce a pro-thrombotic state through upregulating the expression of tissue factor (TF) which could induce a coagulation cascade via PAR signaling [19, 21].

Neutrophil extracellular traps (NETs) are extracellular fibers made up of DNA from neutrophils that bind to pathogens. In one study, patients and especially hospitalized and ventilated patients were found to have elevated cell-free DNA, myeloperoxidase-DNA, and citrullinated histones which suggests elevated NETs in these patients [22]. This is relevant to a pro-thrombotic state due to recent literature linking NETs to pulmonary disease and thrombo-inflammation, and NETs might be an underlying cause of the cytokine storm associated with COVID-19 infection [19, 23].

In COVID-19 patients, research has shown complement hyper-activation and association with increased C5a and severe disease [24]. Complement over-activation may be a causative agent of cytokine storm as well. Biopsy findings in patients have shown hyaline thrombi in the lungs and the skin with a complement deposit [19, 25].

Finally, the effects of COVID-19 on the renin angiotensin system (RAS) are significant as well. COVID-19 uses its S-glycoprotein to bind to ACEII receptors in the lung alveolar epithelial cells. This receptor is the homologue of ACE which is key component of RAS. ACE cleaves angiotensin I to generate angiotensin II (ANG II) which then binds to angiotensin type 1 receptor (AT1R). The overall effect is vasoconstriction and increased blood pressure. ACEII, however, inactivates angiotensin II and vice versa which leads to the overall effect of vasodilation. After COVID-19 binds to ACE2, it leads to the internalization of that receptor. This takes away its key role in regulating angiotensin II levels and leads to overactivation of the angiotensin type 1 receptor causing hypertension and lung injury [19, 26]. The angiotensin type 1 receptor has also been implicated in cytokine storm because it stimulates IL-6 release. ANGII and its activation of AT1R are implicated in hypercoagulability by being inducers of tissue factor and plasminogen activator. This may also explain why people with comorbidities fare worse with COVID-19 infections due to the fact that they already have lower baseline ACEII levels which is worsened by infection [19, 27].

Stroke and COVID

The body’s inflammatory response to COVID-19 has many avenues with which it promotes a hypercoagulable state. It is interesting to further explore how that hypercoagulable state leads to stroke etiologies.

One molecule of interest that has also been seen as a therapeutic target is the nod-like receptor family pyrin domain-containing 3 inflammasome (NLRP3) which is overactivated in COVID-19. This receptor interacts with the viral viroporin protein 3a and leads to an inflammatory cascade that releases the cytokines interleukin-1β (IL-1β), interleukin-18 (IL-18), pathogen-associated molecular patterns (PAMPs), and damage-associated molecular patterns (DAMPs) [19]. In stroke, the NLRP3 inflammasome activates the immune system as well and contributes to promoting further plaque instability by increasing macrophages, neutrophils, lymphocytes, and vascular smooth muscle cells [28]. Activation of NLRP3 is greater because the NLRP3 is basally activated in patients who are immunocompromised and have diabetes and obesity [29]. This inflammasome could be implicated in the contribution of such risk factors for higher rates of stroke in COVID-19 patients. Some pharmacological therapies that may have benefits in patients that target NLRP3 include statins and colchicine [30, 31].

Proteolytic enzymes such as matrix metalloproteinases and cathepsin cysteine proteases are secreted by macrophages in response to inflammation, and they cause damage to the extracellular matrix which could lead to thromboembolism [32]. Another interesting biomarker that provides evidence for the connection between stroke and COVID-19 is the presence of increased expression lectin-like oxidized lipoprotein 1 receptor (LOX-1) in COVID-19 patients. The expression of this receptor is correlated with increased reactive oxygen species and has been shown in models to increase the risk of stroke and restenosis [33]. NETs which were mentioned in the introduction as a part of the pathogenesis of stroke also could play a role in COVID-19-induced stroke. Autopsy studies of patients with COVID-19 have shown the presence of NET-containing microthrombi [34]. The balance between coagulation and fibrinolysis is disrupted in COVID-19 promoting a pro-thrombotic state. Increased D-dimer levels and fibrinogen along with heparin resistance and the failure of other thrombolytic treatments have been observed in COVID-19 patients suggesting that the virus promotes fibrinolytic shutdown [35,36,37,38]. Biomarkers of anticoagulation like protein C, protein S, and antithrombin were also found to be lower in COVID-19 [39].

COVID, stroke, and comorbidities

The interplay between stroke and COVID-19 is exemplified by the coexistence of comorbidities. Diabetes mellitus patients have been shown to be at increased risk for stroke and COVID-19 complication. The mechanism behind the increased risk for COVID-19 comorbidities includes increased ACE-2 expression, increased furin, impaired T-cell function, and increased IL-6 [40,41,42,43,44]. ACE-2 and IL-6 are both mechanisms that have been mentioned above in increasing the hypercoagulable state in the COVID-19 patients as well. Hypertension is also a common comorbidity of COVID-19 and stroke patients. The impact of hypertension on increased ACE-2 expression might contribute to increasing the risk of stroke in patients with hypertension who are diagnosed with COVID-19 as well.


The main point that we can gleam from the data is that among our cases, the narrative that fits most patients for COVID-19 and stroke is that they come to the hospital for COVID and then subsequently develop a stroke. The mechanisms by which COVID induces stroke is not completely understood, but current research is looking into COVID-induced cytokine storms, thrombosis, extrinsic and intrinsic coagulation pathway activation, platelet activation, endothelialitis, and neutrophil extracellular traps (NETs) [45]. Also, among our cases, hypertension was prevalent in more patients than diabetes among all categories. This finding has been corroborated across other case and systemic reviews [5, 46]. Some interesting findings that we could not make conclusions on were the stark gender differences between the STC and CAS categories due to the small number of patients in each category. It would be a future area of study to find larger data sets of these categories to see if the gender differences are holding up with STC being mostly females and CAS being mostly males. If the gender difference holds up in a larger data set, this could be due to gender differences in seeking care [47], or maybe there might be an underlying physiological mechanism involved.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.



Coronavirus disease


COVID-induced stroke


Stroke then COVID


COVID and stroke


National Institute of Health Stroke Scale


Atrial fibrillation


American Heart Association


World Health Organization


National Inpatient Sample


Intensive care unit


Neutrophil extracellular traps




Tissue factor


Von Willebrand factor


Factor VIII


Renin angiotensin system


Angiotensin-converting enzyme


Angiotensin II


Nod-like receptor family pyrin domain-containing 3 inflammasome








Pathogen-associated molecular patterns


Damage-associated molecular patterns


Lectin-like oxidized lipoprotein 1 receptor


  1. Mao L, Jin H, Wang M et al (2020) Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan. China JAMA Neurol 77(6):683–690.

    Article  PubMed  Google Scholar 

  2. Xie Y, Xu E, Bowe B, Al-Aly Z (2022) Long-term cardiovascular outcomes of COVID-19. Nat Med 28(3):583–590.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. South K, McCulloch L, McColl BW, Elkind MS, Allan SM, Smith CJ (2020) Preceding infection and risk of stroke: an old concept revived by the COVID-19 pandemic. Int J Stroke 15(7):722–732.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Wijeratne T, Gillard Crewther S, Sales C, Karimi L (2021) COVID-19 pathophysiology predicts that ischemic stroke occurrence is an expectation, not an exception—a systematic review. Front Neurol 11. Accessed 8 Aug  2022.

  5. Qureshi AI, Baskett WI, Huang W et al (2021) Acute ischemic stroke and COVID-19. Stroke 52(3):905–912.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Shakil SS, Emmons-Bell S, Rutan C et al (2022) Stroke among patients hospitalized with COVID-19: results from the American Heart Association COVID-19 Cardiovascular Disease Registry. Stroke 53(3):800–807.

    Article  CAS  PubMed  Google Scholar 

  7. Tsao CW, Aday AW, Almarzooq ZI et al (2022) Heart Disease and Stroke Statistics—2022 update: a report from the American Heart Association. Circulation 145(8):e153–e639.

    Article  PubMed  Google Scholar 

  8. Ramphul K, Ramphul Y, Sombans S et al (2021) Incidence and mortality rates of acute ischemic stroke in hospitalized patients in the United States. Arch Med Sci Atheroscler Dis 6:e132–e134.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Strilciuc S, Grad DA, Radu C et al (2021) The economic burden of stroke: a systematic review of cost of illness studies. J Med Life 14(5):606–619.

    Article  PubMed  PubMed Central  Google Scholar 

  10. GBD 2016 Stroke Collaborators (2019) Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol 18(5):439–458.

    Article  Google Scholar 

  11. Weekly epidemiological update on COVID-19 - 21 September 2022. Accessed 21 Sept 2022.

  12. Panigada M et al (2020) Hypercoagulability of COVID-19 patients in intensive care unit: A report of thromboelastography findings and other parameters of hemostasis. J Thromb Haemost.

  13. Inflammation and thrombosis - Esmon - 2003 - Journal of Thrombosis and Haemostasis - Wiley Online Library. Accessed  27 Sept 2022.

  14. Abou-Ismail MY, Diamond A, Kapoor S, Arafah Y, Nayak L (2020) The hypercoagulable state in COVID-19: incidence, pathophysiology, and management. Thromb Res 194:101–115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Fogarty H, Townsend L, Ni Cheallaigh C et al (2020) COVID19 coagulopathy in Caucasian patients. Br J Haematol 189(6):1044–1049.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Tang N, Li D, Wang X, Sun Z (2020) Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost 18(4):844–847.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Monteil V, Kwon H, Prado P et al (2020) Inhibition of SARS-CoV-2 infections in engineered human tissues using clinical-grade soluble human ACE2. Cell 181(4):905-913.e7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Escher R, Breakey N, Lämmle B (2020) Severe COVID-19 infection associated with endothelial activation. Thromb Res 190:62

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Chen IY, Moriyama M, Chang MF, Ichinohe T (2019) Severe acute respiratory syndrome coronavirus viroporin 3a activates the NLRP3 inflammasome. Front Microbiol 10:50

    Article  PubMed  PubMed Central  Google Scholar 

  20. Merad M, Martin JC (2020) Pathological inflammation in patients with COVID-19: a key role for monocytes and macrophages. Nat Rev Immunol 20(6):355–362

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Foley JH, Conway EM (2016) Cross talk pathways between coagulation and inflammation. Circ Res 118(9):1392–1408

    Article  CAS  PubMed  Google Scholar 

  22. Zuo Y, Yalavarthi S, Shi H et al (2020) Neutrophil extracellular traps in COVID-19. JCI Insight. 5(11):e138999

    PubMed  PubMed Central  Google Scholar 

  23. Barnes BJ, Adrover JM, Baxter-Stoltzfus A et al (2020) Targeting potential drivers of COVID-19: neutrophil extracellular traps. J Exp Med. 217(6):e20200652

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gao T, Hu M, Zhang X et al (2020) Highly pathogenic coronavirus N protein aggravates lung injury by MASP-2-mediated complement over-activation. Published online, MedRxiv

    Book  Google Scholar 

  25. Yao XH, Li TY, He ZC et al (2020) A pathological report of three COVID-19 cases by minimal invasive autopsies. Zhonghua Bing Li Xue Za Zhi 49(5):411–417

    CAS  PubMed  Google Scholar 

  26. Zores F, Rebeaud ME (2020) COVID and the renin-angiotensin system: are hypertension or its treatments deleterious? Front Cardiovasc Med 7:71

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Vaughan DE, Lazos SA, Tong K (1995) Angiotensin II regulates the expression of plasminogen activator inhibitor-1 in cultured endothelial cells. A potential link between the renin-angiotensin system and thrombosis. J Clin Invest. 95(3):995–1001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Fann DY, Lee SY, Manzanero S et al (2013) Intravenous immunoglobulin suppresses NLRP1 and NLRP3 inflammasome-mediated neuronal death in ischemic stroke. Cell Death Dis 4(9):e790–e790

    Article  CAS  PubMed  Google Scholar 

  29. Bertocchi I, Foglietta F, Collotta D et al (2020) The hidden role of NLRP3 inflammasome in obesity-related COVID-19 exacerbations: lessons for drug repurposing. Br J Pharmacol 177(21):4921–4930

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Rodrigues-Diez RR, Tejera-Muñoz A, Marquez-Exposito L et al (2020) Statins: could an old friend help in the fight against COVID-19? Br J Pharmacol 177(21):4873–4886

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Albensi BC (2019) What is nuclear factor kappa B (NF-κB) doing in and to the mitochondrion? Front Cell Dev Biol 7:154

    Article  PubMed  PubMed Central  Google Scholar 

  32. de Pereira MP, Lima EG, Serrano Junior CV (2020) Viral infections and atherothrombosis: another caution in the wake of COVID-19? Rev Assoc Médica Bras 66:366–369

    Article  Google Scholar 

  33. Sawamura T, Fujita Y, Horiuchi S, Kakino A (2017) LOX-1 in ischemic stroke. J Atheroscler Thromb 24(6):566–568

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Middleton EA, He XY, Denorme F et al (2020) Neutrophil extracellular traps contribute to immunothrombosis in COVID-19 acute respiratory distress syndrome. Blood 136(10):1169–1179

    Article  CAS  PubMed  Google Scholar 

  35. Wright FL, Vogler TO, Moore EE et al (2020) Fibrinolysis shutdown correlation with thromboembolic events in severe COVID-19 infection. J Am Coll Surg 231(2):193-203. e1

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sangalli D, Polonia V, Colombo D et al (2020) A single-centre experience of intravenous thrombolysis for stroke in COVID-19 patients. Neurol Sci 41(9):2325–2329

    Article  PubMed  PubMed Central  Google Scholar 

  37. Abdulkadir T, Ünlübaş Y, Alemdar M, Akyüz E (2020) Coexistence of COVID-19 and acute ischemic stroke report of four cases. J Clin Neurosci 77:227–229

    Article  Google Scholar 

  38. Thachil J, Tang N, Gando S et al (2020) ISTH interim guidance on recognition and management of coagulopathy in COVID-19. J Thromb Haemost 18(5):1023–1026

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ahmed S, Zimba O, Gasparyan AY (2020) Thrombosis in coronavirus disease 2019 (COVID-19) through the prism of Virchow’s triad. Clin Rheumatol 39(9):2529–2543

    Article  PubMed  PubMed Central  Google Scholar 

  40. Singh AK, Gupta R, Ghosh A, Misra A (2020) Diabetes in COVID-19: prevalence, pathophysiology, prognosis and practical considerations. Diabetes Metab Syndr Clin Res Rev 14(4):303–310.

    Article  Google Scholar 

  41. Rao S, Lau A, So HC (2020) Exploring diseases/traits and blood proteins causally related to expression of ACE2, the putative receptor of SARS-CoV-2: a Mendelian randomization analysis highlights tentative relevance of diabetes-related traits. Diabetes Care 43(7):1416–1426

    Article  CAS  PubMed  Google Scholar 

  42. Fernandez C, Rysä J, Almgren P et al (2018) Plasma levels of the proprotein convertase furin and incidence of diabetes and mortality. J Intern Med 284(4):377–387

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Guan WJ, Ni ZY, Hu Y et al (2020) Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 382(18):1708–1720

    Article  CAS  PubMed  Google Scholar 

  44. Maddaloni E, Buzzetti R (2020) Covid-19 and diabetes mellitus: unveiling the interaction of two pandemics. Diabetes Metab Res Rev 36(7):e33213321

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Zakeri A, Jadhav AP, Sullenger BA, Nimjee SM (2021) Ischemic stroke in COVID-19-positive patients: an overview of SARS-CoV-2 and thrombotic mechanisms for the neurointerventionalist. J NeuroInterventional Surg 13(3):202–206.

    Article  Google Scholar 

  46. Nannoni S, de Groot R, Bell S, Markus HS (2021) Stroke in COVID-19: a systematic review and meta-analysis. Int J Stroke Off J Int Stroke Soc 16(2):137–149.

    Article  Google Scholar 

  47. Thompson AE, Anisimowicz Y, Miedema B, Hogg W, Wodchis WP, Aubrey-Bassler K (2016) The influence of gender and other patient characteristics on health care-seeking behaviour: a QUALICOPC study. BMC Fam Pract 17:38.

    Article  PubMed  PubMed Central  Google Scholar 

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The authors declare that no funding sources were used during the study’s design and collection, analysis, interpretation of the data, or in writing the manuscript.

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MM designed the study, collected the data, and participated in the analysis of the data. MM also wrote the initial draft of the manuscript. MP and JP assisted in further interpretation of the data and provided edits for subsequent revisions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to M. Patel.

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Malempati, M., Patel, M. & Patel, J. Ischemic stroke and COVID-19 infection — a review of clinical case reports. Egypt J Intern Med 36, 50 (2024).

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