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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 13  |  Issue : 6  |  Page : 1333-1337  

Cardiovascular complications and its impact on outcomes in COVID-19: An original research


1 Department of Cardiology, Rajendra Institute of Medical Science, Ranchi, Jharkhand, India
2 General Physician, Rollz India Waste Management Pvt. Ltd, Ghaziabad, Uttar Pradesh, India
3 Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, AIMST University, Kedah, Malaysia
4 Department of Periodontics, RUHS College of Dental Sciences, Jaipur, Rajasthan, India
5 Department of Periodontics, SMBT Dental College and Postgraduate Centre, Sangamner, Maharashtra, India
6 Department of Pediatric and Preventive Dentistry, SMBT Dental College and Hospital, Sangamner, Maharashtra, India
7 Department of OMFS, Narsinbhai Patel Dental College and Hospital, Sankalchand Patel University, Visnagar, Gujarat, India

Date of Submission05-Mar-2021
Date of Decision06-Apr-2021
Date of Acceptance06-May-2021
Date of Web Publication10-Nov-2021

Correspondence Address:
Rahul V C Tiwari
Department of OMFS, Narsinbhai Patel Dental College and Hospital, Sankalchand Patel University, Visnagar - 384 315, Gujarat
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jpbs.jpbs_143_21

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   Abstract 


Introduction: The viral infection COVID-19 is highly infectious and has claimed many lives till date and is still continuing to consume lives. In the COVID-19, along with pulmonary symptoms, cardiovascular (CV) events were also recorded that have known to significantly contribute to the mortality. In our study, we designed and validated a new risk score that can predict CV events, and also evaluated the effect of these complications on the prognosis in COVID-19 patients. Materials and Methods: A retrospective, multicenter, observational study was done among 1000 laboratory-confirmed COVID-19 patients between June 2020 and December 2020. All the data of the clinical and laboratory parameters were collected. Patients were randomly divided into two groups for testing and validating the hypothesis. The identification of the independent risk factors was done by the logistic regression analysis method. Results: Of all the types of the clinical and laboratory parameters, ten “independent risk factors” were identified associated with CV events in Group A: male gender, older age, chronic heart disease, cough, lymphocyte count <1.1 × 109/L at admission, blood urea nitrogen >7 mmol/L at admission, estimated glomerular filtration rate <90 ml/min/1.73 m2 at admission, activated partial thromboplastin time >37 S, D-dimer, and procalcitonin >0.5 mg/L. In our study, we found that CV events were significantly related with inferior prognosis (P < 0.001). Conclusions: A new risk scoring system was designed in our study, which may be used as a predictive tool for CV complications among the patients with COVID-19 infection.

Keywords: Cardiovascular events, COVID-19, scoring system


How to cite this article:
Kumar P, Tiwari K, Pendyala SK, Jaiswal RK, Chacko NL, Srivastava E, Tiwari RV. Cardiovascular complications and its impact on outcomes in COVID-19: An original research. J Pharm Bioall Sci 2021;13, Suppl S2:1333-7

How to cite this URL:
Kumar P, Tiwari K, Pendyala SK, Jaiswal RK, Chacko NL, Srivastava E, Tiwari RV. Cardiovascular complications and its impact on outcomes in COVID-19: An original research. J Pharm Bioall Sci [serial online] 2021 [cited 2022 Jun 26];13, Suppl S2:1333-7. Available from: https://www.jpbsonline.org/text.asp?2021/13/6/1333/329979




   Introduction Top


The viral infection COVID-19 is highly infectious and has claimed many lives till date and is still continuing to consume lives.[1] It is assumed to be affecting the respiratory system, and may lead to the cascade of events and eventual death in few. To date (January 2021), 10.6 million cases have been recorded in India with 152,000 deaths and with 95 million infected around the world.[1],[2],[3],[4] In the COVID-19, along with pulmonary symptoms, cardiovascular (CV) events were also recorded that have known to significantly contribute to the mortality.[4],[5],[6],[7],[8],[9] There have been very few studies conducted to note the association between the CV risk factors and outcome in COVID-19 patients. In our study, we designed and validated a new risk score that can predict CV events, and also evaluated the effect of these complications related to the outcome in these patients.


   Materials and Methods Top


We conducted a multicenter, retrospective, observational study among 1000 COVID-19 patients (who were confirmed by reverse transcription–polymerase chain reaction) between June 2020 and December 2020. The data were collected from COVID care centers and hospitals. Patients were randomly separated into two groups: Group A (500) to formulate the risk scoring and Group B (500) to validate the new scoring system. The exclusion criteria were as follows: (1) <18 years old, (2) pregnancy, and (3) recent/known CV event. Demographics, vital signs, symptoms and signs, comorbidities, and laboratory examination data were collected. CV complications were deliberated only when these were seen: (1) acute myocardial infarction (AMI), (2) acute myocardial injury, (3) de novo arrhythmia, (4) new or worsening HF, and (5) deep vein thrombosis. Statistical investigation was done using IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp. IBM Corp. Released 2016. Suitable tests were applied for comparison. P < 0.05 was measured to be significant statistically.


   Results Top


In Group A, 145 (14.5%) patients had CV complications. Nine patients had a new heart failure and 31 patients had a new arrhythmia. Ninety-nine patients among them had acute myocardial injury and six progressed to AMI. Only one patient had deep vein thrombosis. Male gender and the higher age patients with complications were two variables that were both significantly greater than those of patients without complications (P < 0.0010). Significant variations were seen in few variables among the patients with or without CV complications such as cough (P = 0.0021), chronic heart disease (CHD) (P < 0.0013), diabetes mellitus (P = 0.0362), and fever (P = 0.0311). In the patients with CV complications, higher aspartate aminotransferase (P < 0.001), white blood cell (P = 0.001), and neutrophil (P < 0.001) were present, however, lesser lymphocyte counts (P < 0.001), platelet (P = 0.005), and erythrocyte sedimentation rate (P < 0.001) were seen in patients without CV complications [Table 1]. The variables that have P < 0.10 were considered for the logistic regression model analysis. From our observation, ten “independent risk factors” associated with CV complications were identified: male, age ≥60 years, CHD, lymphocyte count ≤1.1 × 109/L at admission, cough, blood urea nitrogen ≥7 mmol/L at admission, estimated glomerular filtration rate (eGFR) ≤90 ml/min/1.73 m2 at admission, activated partial thromboplastin time (APTT) ≥37 S, D-dimer ≥0.5 mg/L, and procalcitonin ≥0.5 mg/L. Hence, final risk scores altered from 0 to 23 for every patient. The cutoff for predicting the CV complication was given as 7.5 [Table 2]. Later, risk score validation was done. In Group B, 17.5% of patients had CV complications. Group A and Group B had similar risk scores. In Group B, we noted that the optimal cutoff value was 7.5 [Table 3].
Table 1: Clinical variables among patients with/without cardiovascular events in Group A

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Table 2: Multivariate analysis of risk factors in cardiovascular complications in Group A

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Table 3: Validity of the novel risk score

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   Discussion Top


Ten risk factors have been identified. We observed that the total score increased from points 0 to 23. The new scoring system is proportionally related to the prognosis of COVID-19 patients in relation to the CV complications. Hence, early forecast of CV complications is significant and fundamental. Our study is similar to the study of Wei et al.[10] where procalcitonin, preexisting CV, age, sickness, and eGFR were associated with AMI. It is accepted that a risk score may help in thorough stratification than a solitary indicator in COVID-19. Along these lines, we enumerated a new scoring system that includes demographic attributes, manifestations, comorbidities, and laboratory assessments. Study participants were classified into two groups. Past examinations have exhibited that in about 10% of patients with COVID-19, myocardial injury happened.[4],[9] In our study among ~16% of the patients, the complex CV events were noted. The CV events may be dependent on many factors such as the characteristics of the population and the disease severity. Male, prolonged APTT, older age, CHD, and raised D-dimer have been broadly affirmed to be associated with CV occasions in the risk score. Similar risk factors also are attributed to pneumonia (community acquired).[11] In our study, few independent risks are identified anew which ought to be dealt with carefully. In the review of Irwin, he stated that the cough may also lead to CV complications.[12] In any case, the effect of cough on patients actually stays to be explained. Diminished lymphocyte counts that may be caused due to systemic inflammatory reaction and immunocompromised are regular in COVID-19 patients.[4],[9] There are few studies, that demonstrates that in severe COVID-19, there are lower levels of T suppressor and helper cells.[13] Due to the impact on the lymphocytes in the COVID, this may lead to various CV complications.[14] The relation between the CV event and the blood urea nitrogen (BUN), eGFR in COVID is imprecise. In any case, our outcomes are reliable with a past investigation of flu. In the study conducted by Nin et al., they uncovered that in H1N1 viral pneumonia, patients with acute kidney injury show more CV dysfunction contrasted to those without.[15] In the clinical setup for the analysis of bacterial diseases, procalcitonin shows a high precision. Inevitably, the bacterial infections are commonly seen in those with the CV complications as there is known immunosuppression. There are few studies that demonstrate the association of procalcitonin and cardiovascular morbidity and mortality.[16]

In the past predictive models for the COVID-19 patients for the ICU admissions, critical illness, and deaths, similar risk factor models to our design have been used. In the study by Gong et al., they developed a “nomogram” wherein BUN and older age were related with serious COVID-19.[17] As compared to the previous predictive models, the area under curve in our risk scores is lower than changed as of 0.80–0.90. Due to the retrospective design plan, some basic data were not noted that might have led to the jeopardized results in the risk score's discriminatory power. At that point, it is conceivable that the endpoint of CV events was more heterogeneous than disease itself. Furthermore, in the included patients, the disease severity of different CV events was not similar. To avoid any bias during the study, the accepted definitions were used to identify the disease in the patients and various doctors were assigned to check the data.

From our study, the designated risk factors can be easily obtained and evaluated. It may help clinicians settle on ideal treatment choices for patients who are at danger of CV complications, and assist scientists in future with investigating the mechanism of the CV event in COVID-19.

There are a few limitations to our investigation. To begin with, it was a retrospective examination that might have had selection bias. The medications and therapies prior to admission may have affect results. There was no long-term follow-up. Impact of SARS-CoV-2 to CV systems in the long run and related risk factors are to be investigated. Larger population research is required to verify our suppositions.


   Conclusions Top


In our study, we designed and corroborated a new risk score that is made of ten risk factors during admission: Senior men, CHD, eGFR ≤90 ml/min/1.73 m2, D-dimer ≥0.5 mg/L, lymphocyte count ≤1.1 × 109/L, cough, fever, procalcitonin ≥0.5 μg/L, BUN ≥7 mmol/L, and APTT ≥37 s. A favorable predictive value for CV complications that can affect the outcome among the COVID-19 patients can be calculated from our risk scores. However, further studies are required.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727-33.  Back to cited text no. 1
    
2.
Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020;382:1199-207.  Back to cited text no. 2
    
3.
COVID-19 Map – Johns Hopkins Coronavirus Resource Center. Available from: https://coronavirus.jhu.edu/map.html. [Last accessed on 2020 Jul 30].  Back to cited text no. 3
    
4.
Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506.  Back to cited text no. 4
    
5.
Driggin E, Madhavan MV, Bikdeli B, Chuich T, Laracy J, Biondi-Zoccai G, et al. Cardiovascular considerations for patients, health care workers, and health systems during the COVID-19 pandemic. J Am Coll Cardiol 2020;75:2352-71.  Back to cited text no. 5
    
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Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention. JAMA 2020;323:1239.  Back to cited text no. 6
    
7.
Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020;46:846-8.  Back to cited text no. 7
    
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Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020;395:1054-62.  Back to cited text no. 8
    
9.
Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020;323:1061-9.  Back to cited text no. 9
    
10.
Wei JF, Huang FY, Xiong TY, Liu Q, Chen H, Wang H, et al. Acute myocardial injury is common in patients with COVID-19 and impairs their prognosis. Heart 2020;106:1154-9.  Back to cited text no. 10
    
11.
Violi F, Cangemi R, Falcone M, Taliani G, Pieralli F, Vannucchi V, et al. Cardiovascular complications and short-term mortality risk in community – Acquired pneumonia. Clin Infect Dis 2017;64:1486-93.  Back to cited text no. 11
    
12.
Irwin RS. Complications of cough: ACCP evidence-based clinical practice guidelines. Chest 2006;129 Suppl 1:54S-8.  Back to cited text no. 12
    
13.
Qin C, Zhou L, Hu Z, Zhang S, Yang S, Tao Y, et al. Dysregulation of immune response in patients with coronavirus 2019 (COVID-19) in Wuhan, China. Clin Infect Dis 2020;71:762-8.  Back to cited text no. 13
    
14.
Nunez J, Minana G, Bodi V, Núñez E, Sanchis J, Husser O, et al. Low lymphocyte count and cardiovascular diseases. Curr Med Chem 2011;18:3226-33.  Back to cited text no. 14
    
15.
Nin N, Lorente JA, Soto L, Ríos F, Hurtado J, Arancibia F, et al. Acute kidney injury in critically ill patients with 2009 influenza A (H1N1) viral pneumonia: An observational study. Intensive Care Med 2011;37:768-74.  Back to cited text no. 15
    
16.
Schiopu A, Hedblad B, Engström G, Struck J, Morgenthaler NG, Melander O. Plasma procalcitonin and the risk of cardiovascular events and death: A prospective population-based study. J Intern Med 2012;272:484-91.  Back to cited text no. 16
    
17.
Gong J, Ou J, Qiu X, Jie Y, Chen Y, Yuan L, et al. A tool for early prediction of severe coronavirus disease 2019 (COVID-19): A multicenter study using the risk nomogram in Wuhan and Guangdong, China. Clin Infect Dis 2020;71:833-40.  Back to cited text no. 17
    



 
 
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  [Table 1], [Table 2], [Table 3]



 

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