- Open Access
Prevalence of hypertension and associated risks in hospitalized patients with COVID-19: a meta-analysis of meta-analyses with 1468 studies and 1,281,510 patients
Systematic Reviews volume 11, Article number: 242 (2022)
Since the COVID-19 outbreak, preliminary research has shown that some risk-associated conditions increase death and severe complications of the disease, hypertension being one of them. Thus, numerous meta-analyses have been conducted to explore this issue. Therefore, this umbrella review aims to perform a meta-analysis of the meta-analyses to estimate the prevalence and associated risks of hypertension in patients with COVID-19.
PubMed, Scopus, Web of Knowledge, Embase, and Cochrane databases were searched for the published meta-analyses up to January 1, 2022. Google Scholar, citation check, reference check, and Grey literature were also manually searched. A random-effect model approach was used for analysis.
The overall death rate was estimated at 12%. Hypertension was present in 25% of the patients as a comorbid disease. The overall RR for death, disease severity, and the possibility of ICU admission were estimated at 1.79 [1.68–1.89 with 95% CI], 1.74 [1.66–1.83 with 95% CI], and 1.91 [1.48–2.34 with 95% CI], respectively. The meta-regression results showed that being “male” significantly increases the risk of disease severity and ICU admission.
The results indicated that hypertension is a common comorbid disease in hospitalized patients with COVID-19, which significantly increases mortality risk, the severity of the disease, and the probability of ICU admission.
Systematic review registration
This study has been registered in PROSPERO (CRD42021231844).
COVID-19 is an infectious disease caused by a novel coronavirus. It is a highly contagious disease from Wuhan, Hubei Province, China, and has spread to over 200 countries [1,2,3,4]. The most common symptoms are fever, dry cough, shortness of breath, weakness, and the loss of smell [5, 6]. It can range from a mild infection to acute respiratory distress syndrome (ARDS), similar to severe respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), which emerged in most countries around the world over the last 20 years [1, 2, 7]. COVID-19 rapidly became a worldwide emergency crisis [8, 9].
Based on the results of published studies and reports, a significant number of high-risk individuals and groups, whose mortality risk and severe complications are higher than others, have been identified since the onset of the COVID-19 pandemic [10,11,12,13,14,15,16]. Patients with hypertension belong to one of these high-risk groups [17,18,19]. Since there is an interaction between COVID-19 and Angiotensin-Converting Enzyme 2 (ACE2), it has been suggested that hypertension could play a role in pathogenesis COVID-19. It can either act as a direct clinical predictor of disease severity or aid in disease exacerbation at the end of a defined disease period through acute respiratory distress syndrome (ARDS), systemic inflammatory response syndrome (SIRS), or multiple organ failure (MOF) . Hypertension is one of the most common conditions globally, leading to dangerous complications like acute heart attacks, heart diseases, and strokes. Therefore, healthcare systems face many treatment and caring challenges regarding these complications [21,22,23,24]. The number of patients with hypertension is growing, especially among the elderly population. It is estimated that by 2025, about 29% of the world’s population will have hypertension, and about 1.58 billion of the world’s adult population will suffer from the complications of this condition . After about 2 years since the coronavirus outbreak, many studies have been conducted on the prevalence and effects of hypertension on patients with COVID-19.
Additionally, some researchers started conducting systematic reviews and meta-analyses using the findings of the studies [18, 19, 26, 27]. Although these studies have presented comprehensive and helpful information, it seems that study results differ from one another. On the other hand, due to the large number of these studies, decision-makers and managers face difficulties choosing which study to base their decisions on. Therefore, it appears that by summarizing and conducting a systematic meta-analysis of meta-analyses, not only will this study overcome these challenges, but because of the large sample size, it will also provide more reliable information for decision-makers, policy-makers, healthcare providers, and other readers. Thus, the present study is carried out to estimate the prevalence and severity of hypertension as a risk factor in patients with COVID-19.
The present study is an umbrella review designed and conducted in 2021 to estimate the prevalence and severity of hypertension as a risk factor in patients with COVID-19. Preferred reporting items for systematic reviews and meta-analyses (PRISMA)  was used in this study. All procedures performed in this study are in accordance with the ethical standards of the institutional and national research committee. Institutional review board (IRB) approval has been obtained from the Research Ethics Committee of Tabriz University of Medical Sciences (ethics code IR.TBZMED.REC.1398.223). In addition, the protocol of this study has been registered in PROSPERO (registration code CRD42021231844).
The search strategy in this study was developed and implemented by a highly knowledgeable librarian experienced in the related field (Additional file 1). PubMed, Scopus, Web of Knowledge, Embase, and Cochrane were searched using the relevant MeSH keywords up to January 1, 2022. Subsequently, some of the relevant journals as well as the search engine Google Scholar were manually searched to discover more articles. The articles were screened considering title/abstracts and full texts, respectively. Excluding the studies that met the exclusion criteria, researchers carried out a citation check (through Google Scholar citations), reference check (done manually from the reference list of the articles), and Grey literature search (through the European Association for Gray Literature Exploitation (EAGLE) and the Healthcare Management Information Consortium (HMIC) databases) to enhance the identification of the existing articles.
Inclusion and exclusion criteria
All the studies and reports published in English worldwide that had analyzed the prevalence and severity of hypertension as a risk factor in patients with COVID-19 using meta-analysis
The studies without meta-analysis, such as narrative reviews and extensive reviews
The studies which had not to mention the prevalence or effects (disease severity, death, ICU admission) of hypertension
The studies which had mentioned the effects of interventions and medications
The studies and reports that lacked a full text or the ones whose full texts could not be accessed
The articles with poor reporting quality (a score lower than 5 out of 11 in reporting quality assessment)
The articles whose target group was merely the deceased patients
The meta-analyses in which the included studies were not sufficient or the ones with an inappropriate reporting method
Assessment of articles’ reporting quality
The reporting quality of all articles in the full-text screening was assessed by two reviewers independently using the tool for assessment of multiple systematic reviews (AMSTAR) . The responses associated with each item are indicated as “Yes”, “No”, “Cannot be answered”, or “non-applicable” in this tool. The answer of “Yes” was given a score of 1, and the answers of “No”, “Cannot be answered”, or “non-applicable” were given a score of 0. According to this tool, the articles with a score of 1 to 4, 5 to 8, and 9 to 11 are rated as “low quality”, “medium quality”, and “high quality”, respectively. The two reviewers’ agreement gave the final assessment score for each article. Disagreements between the two reviewers were referred to a third assessor.
In order to extract data, a data extraction form was designed manually in Word 2013 Office software. The information form included the following information:
Author, year, first author’s country of affiliation, number of included articles in meta-analysis, latest search date (month), number of the total population reviewed in meta-analysis, target group (mean of age, male %, mortality %), pooled prevalence of hypertension % (95% CI), and risk ratio (RR) for death (I2%), severity (I2%), ICU admission (I2%).
First, the data of five randomly selected articles were extracted to pilot the form with the results of these studies being re-used in the main study; the shortcomings and defects of the initial form were removed. In some cases where the required information was not reported in the articles, the research team calculated it based on the characteristics of the articles included in the meta-analysis. In some other cases, an email was sent to the corresponding author to require the information. In some studies, the number of primary articles included in the systematic reviews differed from those in the quantitative analyses (meta-analyses). Accordingly, the researchers considered the number of articles included in the meta-analysis. The information reported in the articles was the basis for extracting RR data for disease severity and ICU admission. The research team did not make any decisions in this regard. For example, some studies reported ICU admission as a disease severity criterion, while other studies reported it separately.
Data analysis methods
In order to estimate the prevalence of hypertension, mortality rate, and the impact of hypertension on patients with COVID-19, statistical meta-analysis methods and a random model were used. Stata (StataCorp, version 16) was used to perform meta-analysis . Since in some studies RR and in the others odds ratio (OR) was reported, it was decided that OR would be converted to RR in the present research. To do this, the formula presented in Zhang et al.’s study  was used. In order to report the results, forest plot graphs were used, in which the size of each square indicated the sample volume, and the lines drawn on each side of the square showed a 95% confidence interval for each study. The indicator I2 was used to assess the heterogeneity of studies’ results. In this study, I2 lower than 50%, I2 between 50 and 74%, and I2 higher than 75% were considered low heterogeneity, medium heterogeneity, and high heterogeneity, respectively . Meta-regression was carried out based on the mean variables of age (year), male percentage, and the latest reference searching date (month). The date was considered due to the galloping speed of publishing primary articles and subsequent systematic reviews as well as the spread of COVID-19 spread. Also, sub-group analyses were carried out based on the latest date of search (month). Funnel plot graph and Egger’s regression test were used at a significance level of 0.1  to assess publication bias. The Trim and Fill test was used through a linear estimator whenever publication bias was potential.
For assessing the percentage of the overlap of primary studies, corrected covered area (CCA), and covered area (CA) introduced by Pieper et al.  was applied. Overlap was defined as primary studies that were included in more than one meta-analysis.
N: The sum of primary published studies and repeated studies are counted to calculate N
r: Number of rows or index publication
c: Number of columns or reviews
Out of 2523 records found from databases and other sources, 1079 studies were excluded due to duplication and meeting the exclusion criteria. A total of 1072 records were excluded when titles and abstracts were screened. In addition, 328 records were excluded after full-text screening. Finally, 52 meta-analyses were included [26, 35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85] (see Fig. 1 for PRISMA flowchart). Also, the PRISMA checklist is provided in the Additional file 2. The characteristics and results of the included meta-analyses are demonstrated in Additional file 3.
Twenty studies were initially based in China, and six were from the US. Fifty-two meta-analyses were reviewed, including 1468 studies and 1,281,510 patients with COVID-19. The latest date (month) of reference searching varied from the 2nd to the 11th month of 2020, in which most cases belonged to the 3rd and 4th months. The mean age of the patients studied in the articles was 53. In addition, about 60% of the study participants were males.
Mortality rate in patients
In 17 studies with an overall sample size of 741,399 patients, the mortality rate in patients with COVID-19 was reviewed. Meta-analysis showed that the overall mortality rate was 12% [9–16% with 95% CI] (Fig. 2). Heterogeneity assessment results showed high heterogeneity in the results of the studies (for more information, refer to Table 1).
Prevalence of hypertension (as a comorbid disease)
In 36 studies with an overall sample size of 960,963 patients, the prevalence of hypertension as a comorbid disease was reported, and meta-analysis results showed that the overall prevalence percentage was 25% [22–26% with 95% CI] (Fig. 3). Heterogeneity assessment results showed high heterogeneity in the results of the studies (for more information refer to Table 1).
RR for death
In 21 studies with an overall sample size of 548,776 patients, RR for hypertension was reported in the death of patients with COVID-19. Meta-analysis results showed that the overall RR was 1.79 [1.69–1.89 with 95% CI] (Fig. 4). Heterogeneity assessment results showed a medium heterogeneity in the results of the studies. The results of assessing the potential for publication bias showed a high possibility of publication bias in the studies’ findings (for more information, refer to Table 1) (Fig. 5A). Furthermore, the Trim and Fill test results showed that six studies are possibly missing and that with the imputation of these studies and their effect, RR decreases to 1.74 [1.64–1.84 with 95% CI]. The mean I2 of meta-analyses in this section was 58.4%.
RR for disease severity
In 30 studies with an overall sample size of 568,503 patients, RR for hypertension in the disease severity of patients with COVID-19 was reported. Meta-analysis results showed that the overall RR was 1.74 [1.66–1.83 with 95% CI] (Fig. 6). Heterogeneity assessment results showed a low heterogeneity in the results of the studies. The results of assessing the potential for publication bias showed a high possibility of publication bias in the studies’ findings (for more information, refer to Table 1) (Fig. 5B). Furthermore, the Trim and Fill test results showed that six studies are possibly missing, and with the imputation of these studies and their effect, RR decreases to 1.68 [1.63–.74 with 95% CI]. The mean I2 of meta-analyses in this section was 49.6%.
RR for ICU admission
In five studies with an overall sample size of 43079 patients, RR for hypertension in the patients with COVID-19 hospitalized in ICU was reported. Meta-analysis results showed that the overall RR was 1.91 [1.48–2.34 with 95% CI] (Fig. 7). Heterogeneity assessment results showed a medium heterogeneity in the results of the studies. The results of assessing the potential for publication bias showed a very low possibility of publication bias in the studies results (for more information, refer to Table 1) (Fig. 5C). The mean of I2 of meta-analyses in this section was 36.1%.
Meta-regression results with a random model, based on the patients’ mean age (year), male percentage, and the latest reference searching date (month), showed that among these variables, only the male percentage significantly estimates RR for disease severity and ICU admission. Furthermore, a 1% increase in the ratio of male proportion causes the RR value for disease severity to increase by almost 0.03 in contrast to RR for ICU admission, which decreases by almost 0.13. None of these variables were significant predictors of patient deaths (Table 2).
Results of articles reporting quality assessment
One study was excluded for low reporting quality (lower than 5 out of 11). The reporting quality was medium (5 to 8) in 19 and high (9 to 11) in 31 studies. The median reporting quality score was 9 (with a mean of 8.6 out of 11) (Additional file 4).
Results of overlap assessment
The overlap calculation results indicate a slight percent of overlap (CA 4.24% and CCA 2.44%) (Additional file 5).
The results of 52 meta-analyses of 1468 articles with 1281510 COVID-19 patients were reviewed. The overall mortality rate in patients with COVID-19 was estimated at 12%. It was estimated that hypertension was a comorbid disease in 25% of the patients. The overall RR for hypertension in the death of patients with COVID-19, disease severity, and probability of ICU admission was estimated at 1.79 [1.68–1.89 with 95% CI], 1.74 [1.66–1.83 with 95% CI], and 1.91 [1.48–2.34 with 95% CI], respectively. In general, reporting quality of the articles was assessed as appropriate.
After studying the latest date of article search, it was revealed that the latest search in meta-analyses was conducted on the 11th month of 2020. In other words, the results of the articles published after the 11th month did not undergo systematic review and meta-analysis (or they have not been published yet). Considering high speed and large amount of the articles published on this subject, fast changes in prevalence, complications, and other aspects of COVID-19, and consequent changes in the study results, it seems that the results of the new studies have to be gathered and reported using meta-analysis, just like the first months after coronavirus outbreak. During this period, plenty of articles and evidence were rapidly published, and different researchers gathered, assessed, combined and reported their results in the form of meta-analyses. However, this should not cause researchers and editors-in-chief to neglect the quality of meta-analyses, for the researchers may not have enough time to conduct high quality studies. Given the pressures to rapidly publish articles on COVID-19, editors-in-chief and reviewers might neglect the quality.
According to the current study results, the overall mortality rate in patients with COVID-19 was 12%. According to the latest update of WHO statistics (4:14 pm CET, December 29 2021), 281,808,270 cases have been confirmed as testing positive for COVID-19, 5,411,759 of whom have died, so the mortality percentage is about 1.92 . However, the studies that calculated the mortality rate of hospitalized patients have reported a figure close to the present study [87,88,89,90]. Nevertheless, some significant changes are seen in the mortality rate in different studies, the reason for which can be the type of treatment and medical services, demographic features of patients, various risk factors in different countries, and the advances obtained over time on the treatment. The critical point, in this regard, is to remove the mistakes and ambiguities of calculations, timely and appropriate reporting, and transparency of statistics, which the countries must consider to have proper decision-making and planning.
The study results revealed that a high percentage of patients with COVID-19 (25%) had hypertension as a comorbid disease. Likewise, the results of most studies undergoing meta-analysis showed that hypertension is the most common comorbid disease in patients with COVID-19. One of the probable reasons could be the prevalence of hypertension in society, especially among adults. Similarly, according to global evidence and reports, the prevalence of hypertension among people worldwide is high and closer to the results of this study (among the hospitalized patients with COVID-19) [91,92,93,94,95]. Considering the high prevalence of hypertension in society and its high risk in the mortality and unpleasant complications of COVID-19, serious and immediate interventions must be carried out to control hypertension in patients beside preventing hypertensive patients from contracting COVID-19 since the simultaneity of these two issues, suffering from hypertension and COVID-19, has unpleasant clinical complications, and it can have negative social and economic effects on patients, healthcare systems, and governments .
The results showed that, in general, hypertension increases these patients’ risk of death, risk of developing another severe disease, and the risk of ICU admission by 79%, 74%, and 91%, respectively. According to the previous studies, various reasons are mentioned for the effects of hypertension on patients with COVID-19, including higher neutrophil-lymphocyte ratio [97, 98], and higher D-dimer levels , and higher C-reactive protein . Furthermore, there is ample evidence that patients treated with ACE (angiotensin-converting enzyme) inhibitors are at a higher risk of death and severe complications than others [20, 101,102,103]. Although the available evidence cannot claim with certainty regarding the impact and the reasons for the adverse effects of hypertension on patients with COVID-19, it appears that a strong and large body of evidence confirms the high risk of mortality and severity of COVID-19 in hypertensive patients, as the results of this study with a large sample size indicated. Therefore, it is essential to pay special attention to this group of people by quarantining, social distancing, regularly controlling blood pressure, using highly effective masks, prioritizing receiving confirmed vaccines, and other controlling actions.
Meta-regression results showed that being male significantly increases disease severity and ICU admission. As a result, it is considered a risk factor, while it has a negative and insignificant effect on the death caused by COVID-19. Many studies and reports indicate a high risk of unpleasant complications and a high mortality rate among males [104,105,106,107]. Unlike most previously published studies [108,109,110], the present study could not show age as a risk factor determining death and disease severity. One of the main reasons the findings of this study are not in line with the findings of other studies could be the participants’ low mean age. In this study, the participants’ mean age was 53 years. However, in most published articles and reports, ages over 65 have been introduced as the leading risk factor for death [111,112,113,114]. On the other hand, considering the lack of information in some articles and the means reported in meta-analyses being close, it was impossible to group the means of age.
According to the results of text reviews and to the best of our knowledge, the present study is innovatively combining the results of the published meta-analyses on the prevalence and risk of hypertension in patients with COVID-19 (including the data from 1468 articles with 1,281,510 patients) for the first time. It provides transparent and comprehensive information for the decision-makers, healthcare providers, and other readers. Still, this study had some major limitations. The readers must pay attention to them while reading, interpreting, using the study results, and making cautious conclusions. One of the most important limitations concerns searching in English both in this study and in most other reviewed studies. The results could differ once published in other languages (especially Chinese) in the analysis. Another limitation of this study was that although the percentage of overlap of primary studies was negligible, removing repeated studies in the published meta-analyses was not possible because the researchers intended to use a combination of meta-analyses results. Furthermore, heterogeneity assessment results showed potential for publication bias, though the Trim and Fill test results indicated that its effect would not be significant if such bias occurs. However, it is recommended that the results be interpreted cautiously.
The meta-analysis of meta-analyses consisting of 1468 articles with 1281510 patients with COVID-19 indicated that hypertension is a prevalent disease among hospitalized patients with COVID-19, which significantly increases the risk of death, and disease severity, and ICU admission. Therefore, it is essential to pay attention to this group of people by quarantining, social distancing, regularly controlling blood pressure, using highly effective masks, prioritizing receiving confirmed vaccines, and other controlling actions. However, the readers must be cautious in interpreting and using the study results.
Availability of data and materials
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request (email@example.com).
Angiotensin-converting enzyme 2
Acute respiratory distress syndrome
Coronavirus disease 2019
Intensive care unit
Multiple organ failure
Systemic inflammatory response syndrome
World Health Organization
Iyengar K, Bahl S, Raju V, Vaish A. Challenges and solutions in meeting up the urgent requirement of ventilators for COVID-19 patients. Diabetes Metab Syndr. 2020;14(4):499–501.
Gralinski LE, Menachery VD. Return of the Coronavirus: 2019-nCoV. Viruses. 2020;12(2):135.
Li B-Z, Cao NW, Zhou HY, Chu XJ, Long Y. Strong policies control the spread of COVID-19 in China. J Med Virol. 2020;92(10):1980–7.
Mohseni M, Mousavi Isfahani H, Fardid M, Asadi H, Hasoumi M, Azami-Aghdash S. Role of nation's culture on COVID-19 prevention. Int J Soc Psychiatry. 2021;67(7):961-2. https://doi.org/10.1177/0020764020973706.
Moghanibashi-Mansourieh A. Assessing the anxiety level of Iranian general population during COVID-19 outbreak. Asian J Psychiatr. 2020;51:102076.
Guarnotta V, Ferrigno R, Martino M, Barbot M, Isidori AM, Scaroni C, et al. Glucocorticoid excess and COVID-19 disease. Rev Endocr Metab Disord. 2021;22(4):703-14. https://doi.org/10.1007/s11154-020-09598-x.
Abdelhafiz AS, Mohammed Z, Ibrahim ME, Ziady HH, Alorabi M, Ayyad M, et al. Knowledge, Perceptions, and Attitude of Egyptians Towards the Novel Coronavirus Disease (COVID-19). J Community Health. 2020;45(5):881-90. https://doi.org/10.1007/s10900-020-00827-7.
WHO. Home/Emergencies/Diseases/ Coronavirus disease 2019/Coronavirus disease (COVID-19) Pandemic WHO: WHO; 2020. Available from: https://www.who.int/
Iezadi S, Azami-Aghdash S, Ghiasi A, Rezapour A, Pourasghari H, Pashazadeh F, et al. Effectiveness of the non-pharmaceutical public health interventions against COVID-19; a protocol of a systematic review and realist review. PLoS One. 2020;15(9):e0239554.
Emami A, Javanmardi F, Pirbonyeh N, Akbari A. Prevalence of underlying diseases in hospitalized patients with COVID-19: a systematic review and meta-analysis. Arch Acad Emerg Med. 2020;8(1):e35.
Khorshid M, Saber A-A, Ahmad K, Rahim K-Z. The main issues and challenges older adults face in the SARS-CoV-2 pandemic: a scoping review of literature. Iran J Public Health. 2020;49(12):2295.
Jeong IK, Yoon KH, Lee MK. Diabetes and COVID-19: global and regional perspectives. Diabetes Res Clin Pract. 2020;166:108303.
Ferrero P, Piazza I, Ciuffreda M. COVID-19 in adult patients with CHD: a matter of anatomy or comorbidities? Cardiol Young. 2020;30(8):1196–8.
Ejaz H, Alsrhani A, Zafar A, Javed H, Junaid K, Abdalla AE, et al. COVID-19 and comorbidities: deleterious impact on infected patients. J Infect Public Health. 2020;13(12):1833–9.
Guerrero-Fernández de Alba I, Orlando V, Monetti VM, Mucherino S, Gimeno-Miguel A, Vaccaro O, et al. Comorbidity in an older population with type-2 diabetes mellitus: identification of the characteristics and healthcare utilization of high-cost patients. Front Pharmacol. 2020;11:586187.
Kamyshnyi A, Krynytska I, Matskevych V, Marushchak M, Lushchak O. Arterial Hypertension as a Risk Comorbidity Associated with COVID-19 Pathology. International Journal of Hypertension. 2020;2020:7. Article ID 8019360. https://doi.org/10.1155/2020/8019360.
Das BB. COVID-19 and pulmonary hypertension in children: what do we know so far? Medicina (Kaunas, Lithuania). 2020;56(12):716.
Del Pinto R, Ferri C. The role of immunity in fabry disease and hypertension: a review of a novel common pathway. High Blood Press Cardiovasc Prev. 2020;27(6):539–46.
Deravi N, Fathi M, Vakili K, Yaghoobpoor S, Pirzadeh M, Mokhtari M, et al. SARS-CoV-2 infection in patients with diabetes mellitus and hypertension: a systematic review. Rev Cardiovasc Med. 2020;21(3):385–97.
Fang L, Karakiulakis G, Roth M. Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? Lancet Respir Med. 2020;8(4):e21.
Jin C, Ji S, Xie T, Höxtermann S, Fuchs W, Lu X, et al. Severe dyslipidemia and immune activation in HIV patients with dysglycemia. HIV Clin Trials. 2016;17(5):189–96.
Hwong WY, Bots ML, Selvarajah S, Aziz ZA, Sidek NN, Spiering W, et al. Use of antihypertensive drugs and ischemic stroke severity–is there a role for angiotensin-II? PLoS One. 2016;11(11):e0166524.
Niiranen TJ, Kalesan B, Hamburg NM, Benjamin EJ, Mitchell GF, Vasan RS. Relative contributions of arterial stiffness and hypertension to cardiovascular disease: the Framingham Heart Study. J Am Heart Assoc. 2016;5(11):e004271.
Proietti M, Mairesse GH, Goethals P, Scavee C, Vijgen J, Blankoff I, et al. Cerebrovascular disease, associated risk factors and antithrombotic therapy in a population screening cohort: Insights from the Belgian Heart Rhythm Week programme. Eur J Prev Cardiol. 2017;24(3):328–34.
Devi P, Rao M, Sigamani A, Faruqui A, Jose M, Gupta R, et al. Prevalence, risk factors and awareness of hypertension in India: a systematic review. J Hum Hypertens. 2013;27(5):281–7.
de Almeida-Pititto B, Dualib PM, Zajdenverg L, Dantas JR, de Souza FD, Rodacki M, et al. Severity and mortality of COVID 19 in patients with diabetes, hypertension and cardiovascular disease: a meta-analysis. Diabetol Metab Syndr. 2020;12:75.
Devaux CA, Rolain JM, Raoult D. ACE2 receptor polymorphism: susceptibility to SARS-CoV-2, hypertension, multi-organ failure, and COVID-19 disease outcome. J Microbiol Immunol Infect. 2020;53(3):425–35.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
Shea BJ, Grimshaw JM, Wells GA, Boers M, Andersson N, Hamel C, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7(1):1–7.
Yin T, Li Y, Ying Y, Luo Z. Prevalence of comorbidity in Chinese patients with COVID-19: systematic review and meta-analysis of risk factors. BMC Infect Dis. 2021;21(1):200.
Zhang J, Kai FY. What’s the relative risk?: a method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998;280(19):1690–1.
Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.
Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.
Pieper D, Antoine SL, Mathes T, Neugebauer EA, Eikermann M. Systematic review finds overlapping reviews were not mentioned in every other overview. J Clin Epidemiol. 2014;67(4):368–75.
Wang Z, Deng H, Ou C, Liang J, Wang Y, Jiang M, et al. Clinical symptoms, comorbidities and complications in severe and non-severe patients with COVID-19: a systematic review and meta-analysis without cases duplication. Medicine. 2020;99(48):e23327.
Zhou Y, Yang Q, Chi J, Dong B, Lv W, Shen L, et al. Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: a systematic review and meta-analysis. Int J Infect Dis. 2020;99:47–56.
Hu Y, Sun J, Dai Z, Deng H, Li X, Huang Q, et al. Prevalence and severity of corona virus disease 2019 (COVID-19): a systematic review and meta-analysis. J Clin Virol. 2020;127:104371.
Li X, Guan B, Su T, Liu W, Chen M, Bin Waleed K, et al. Impact of cardiovascular disease and cardiac injury on in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis. Heart. 2020;106(15):1142–7.
Wang X, Fang X, Cai Z, Wu X, Gao X, Min J, et al. Comorbid chronic diseases and acute organ injuries are strongly correlated with disease severity and mortality among COVID-19 patients: a systemic review and meta-analysis. Research (Washington, DC). 2020;2020:2402961.
Tian W, Jiang W, Yao J, Nicholson CJ, Li RH, Sigurslid HH, et al. Predictors of mortality in hospitalized COVID-19 patients: a systematic review and meta-analysis. J Med Virol. 2020;92(10):1875–83.
Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging. 2020;12(7):6049–57.
Chidambaram V, Tun NL, Haque WZ, Majella MG, Sivakumar RK, Kumar A, et al. Factors associated with disease severity and mortality among patients with COVID-19: a systematic review and meta-analysis. PLoS One. 2020;15(11):e0241541.
Jain V, Yuan JM. Predictive symptoms and comorbidities for severe COVID-19 and intensive care unit admission: a systematic review and meta-analysis. Int J Public Health. 2020;65(5):533–46.
Wu T, Zuo Z, Kang S, Jiang L, Luo X, Xia Z, et al. Multi-organ dysfunction in patients with COVID-19: a systematic review and meta-analysis. Aging Dis. 2020;11(4):874–94.
Sales-Peres SHC, de Azevedo-Silva LJ, Bonato RCS, Sales-Peres MC, Pinto A, Santiago Junior JF. Coronavirus (SARS-CoV-2) and the risk of obesity for critically illness and ICU admitted: meta-analysis of the epidemiological evidence. Obes Res Clin Pract. 2020;14(5):389–97.
Pranata R, Lim MA, Huang I, Raharjo SB, Lukito AA. Hypertension is associated with increased mortality and severity of disease in COVID-19 pneumonia: a systematic review, meta-analysis and meta-regression. J Renin Angiotensin Aldosterone Syst. 2020;21(2):1470320320926899.
Mahumud RA, Kamara JK, Renzaho AMN. The epidemiological burden and overall distribution of chronic comorbidities in coronavirus disease-2019 among 202,005 infected patients: evidence from a systematic review and meta-analysis. Infection. 2020;48(6):813–33.
Ssentongo P, Ssentongo AE, Heilbrunn ES, Ba DM, Chinchilli VM. Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: a systematic review and meta-analysis. PLoS One. 2020;15(8):e0238215.
Espinosa OA, Zanetti ADS, Antunes EF, Longhi FG, Matos TA, Battaglini PF. Prevalence of comorbidities in patients and mortality cases affected by SARS-CoV2: a systematic review and meta-analysis. Rev Inst Med Trop Sao Paulo. 2020;62:e43.
Mudatsir M, Fajar JK, Wulandari L, Soegiarto G, Ilmawan M, Purnamasari Y, et al. Predictors of COVID-19 severity: a systematic review and meta-analysis. F1000Research. 2020;9:1107.
Gold MS, Sehayek D, Gabrielli S, Zhang X, McCusker C, Ben-Shoshan M. COVID-19 and comorbidities: a systematic review and meta-analysis. Postgrad Med. 2020;132(8):749–55.
Meng M, Zhao Q, Kumar R, Bai C, Deng Y, Wan B. Impact of cardiovascular and metabolic diseases on the severity of COVID-19: a systematic review and meta-analysis. Aging. 2020;12(22):23409–21.
Khan MMA, Khan MN, Mustagir MG, Rana J, Islam MS, Kabir MI. Effects of underlying morbidities on the occurrence of deaths in COVID-19 patients: a systematic review and meta-analysis. J Glob Health. 2020;10(2):020503.
Momenzadeh M. Prevalence of diabetes, hypertension and cardiovascular disease in patients with COVID-19: a systematic review and meta-analysis. EurAsian J BioSci. 2020;14(1):2195–200.
Lu L, Zhong W, Bian Z, Li Z, Zhang K, Liang B, et al. A comparison of mortality-related risk factors of COVID-19, SARS, and MERS: a systematic review and meta-analysis. J Infect. 2020;81(4):e18–25.
Xu L, Mao Y, Chen G. Risk factors for 2019 novel coronavirus disease (COVID-19) patients progressing to critical illness: a systematic review and meta-analysis. Aging. 2020;12(12):12410–21.
Miller LE, Bhattacharyya R, Miller AL. Diabetes mellitus increases the risk of hospital mortality in patients with Covid-19: systematic review with meta-analysis. Medicine. 2020;99(40):e22439.
Nandy K, Salunke A, Pathak SK, Pandey A, Doctor C, Puj K, et al. Coronavirus disease (COVID-19): A systematic review and meta-analysis to evaluate the impact of various comorbidities on serious events. Diabetes Metab Syndr. 2020;14(5):1017–25.
Zhang J, Wu J, Sun X, Xue H, Shao J, Cai W, et al. Association of hypertension with the severity and fatality of SARS-CoV-2 infection: a meta-analysis. Epidemiol Infect. 2020;148:e106.
Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis. 2020;94:91–5.
Hu J, Wang Y. The Clinical Characteristics and Risk Factors of Severe COVID-19. Gerontology. 2021;67(3):255-66. https://doi.org/10.1159/000513400.
Li J, He X, Yuan Y, Zhang W, Li X, Zhang Y, et al. Meta-analysis investigating the relationship between clinical features, outcomes, and severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia. Am J Infect Control. 2021;49(1):82–9.
Sreenivasan J, Khan MS, Anker SD, Kaul R, Khan SU, Metra M, et al. Cardiovascular risk factors and complications in patients infected with COVID-19: a systematic review. Available at SSRN 3569855. 2020.
Lippi G, Wong J, Henry BM. Hypertension in patients with coronavirus disease 2019 (COVID-19): a pooled analysis. Pol Arch Intern Med. 2020;130(4):304–9.
Barrera FJ, Shekhar S, Wurth R, Moreno-Pena PJ, Ponce OJ, Hajdenberg M, et al. Prevalence of diabetes and hypertension and their associated risks for poor outcomes in Covid-19 patients. J Endocr Soc. 2020;4(9):bvaa102.
Del Sole F, Farcomeni A, Loffredo L, Carnevale R, Menichelli D, Vicario T, et al. Features of severe COVID-19: a systematic review and meta-analysis. Eur J Clin Investig. 2020;50(10):e13378.
Krittanawong C, Virk HUH, Narasimhan B, Wang Z, Narasimhan H, Zhang HJ, et al. Coronavirus disease 2019 (COVID-19) and cardiovascular risk: a meta-analysis. Prog Cardiovasc Dis. 2020;63(4):527–8.
Wong CKH, Wong JYH, Tang EHM, Au CH, Wai AKC. Clinical presentations, laboratory and radiological findings, and treatments for 11,028 COVID-19 patients: a systematic review and meta-analysis. Sci Rep. 2020;10(1):19765.
Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol. 2020;109(5):531–8.
Biswas M, Rahaman S, Biswas TK, Haque Z, Ibrahim B. Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis. Intervirology. 2020;1-12. https://doi.org/10.1159/000512592.
Moazzami B, Chaichian S, Kasaeian A, Djalalinia S, Akhlaghdoust M, Eslami M, et al. Metabolic risk factors and risk of Covid-19: a systematic review and meta-analysis. PLoS One. 2020;15(12):e0243600.
Singh AK, Gillies CL, Singh R, Singh A, Chudasama Y, Coles B, et al. Prevalence of co-morbidities and their association with mortality in patients with COVID-19: a systematic review and meta-analysis. Diabetes Obes Metab. 2020;22(10):1915–24.
Baradaran A, Ebrahimzadeh MH, Baradaran A, Kachooei AR. Prevalence of comorbidities in COVID-19 patients: a systematic review and meta-analysis. Arch Bone Jt Surg. 2020;8(Suppl 1):247–55.
Soeroto AY, Soetedjo NN, Purwiga A, Santoso P, Kulsum ID, Suryadinata H, et al. Effect of increased BMI and obesity on the outcome of COVID-19 adult patients: a systematic review and meta-analysis. Diabetes Metab Syndr. 2020;14(6):1897–904.
Mesas AE, Cavero-Redondo I, Álvarez-Bueno C, Sarriá Cabrera MA, Maffei de Andrade S, Sequí-Dominguez I, et al. Predictors of in-hospital COVID-19 mortality: a comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions. PLoS One. 2020;15(11):e0241742.
Silverio A, Di Maio M, Citro R, Esposito L, Iuliano G, Bellino M, et al. Cardiovascular risk factors and mortality in hospitalized patients with COVID-19: systematic review and meta-analysis of 45 studies and 18,300 patients. BMC Cardiovasc Disord. 2021;21(1):23.
Moula AI, Micali LR, Matteucci F, Lucà F, Rao CM, Parise O, et al. Quantification of death risk in relation to sex, pre-existing cardiovascular diseases and risk factors in COVID-19 patients: let’s take stock and see where we are. J Clin Med. 2020;9(9):2685.
Bae S, Kim SR, Kim MN, Shim WJ, Park SM. Impact of cardiovascular disease and risk factors on fatal outcomes in patients with COVID-19 according to age: a systematic review and meta-analysis. Heart. 2021;107(5):373–80.
Du Y, Zhou N, Zha W, Lv Y. Hypertension is a clinically important risk factor for critical illness and mortality in COVID-19: a meta-analysis. Nutr Metab Cardiovasc Dis. 2021;31(3):745–55.
Honardoost M, Janani L, Aghili R, Emami Z, Khamseh ME. The association between presence of comorbidities and COVID-19 severity: a systematic review and meta-analysis. Cerebrovasc Dis (Basel, Switzerland). 2021;50(2):132–40.
Li X, Zhong X, Wang Y, Zeng X, Luo T, Liu Q. Clinical determinants of the severity of COVID-19: a systematic review and meta-analysis. PLoS One. 2021;16(5):e0250602.
Mishra P, Parveen R, Bajpai R, Samim M, Agarwal NB. Impact of cardiovascular diseases on severity of COVID-19 patients: a systematic review. Ann Acad Med Singap. 2021;50(1):52–60.
Ng WH, Tipih T, Makoah NA, Vermeulen JG, Goedhals D, Sempa JB, et al. Comorbidities in SARS-CoV-2 patients: a systematic review and meta-analysis. mBio. 2021;12(1):e03647–20.
Rahman A, Sathi NJ. Risk factors of the severity of COVID-19: a meta-analysis. Int J Clin Pract. 2021;75(7):e13916.
Wu Y, Li H, Zhang Z, Liang W, Zhang T, Tong Z, et al. Risk factors for mortality of coronavirus disease 2019 (COVID-19) patients during the early outbreak of COVID-19: a systematic review and meta-analysis. Ann Palliat Med. 2021;10(5):5069–83.
WHO Coronavirus Disease (COVID-19) Dashboard 2021 [updated 2021/2/1. Available from: https://covid19.who.int/. Accessed 13 Aug 2022.
Asch DA, Sheils NE, Islam MN, Chen Y, Werner RM, Buresh J, et al. Variation in US Hospital Mortality Rates for Patients Admitted With COVID-19 During the First 6 Months of the Pandemic. JAMA Intern Med. 2021;181(4):471-8. https://doi.org/10.1001/jamainternmed.2020.8193.
Rosenthal N, Cao Z, Gundrum J, Sianis J, Safo S. Risk factors associated with in-hospital mortality in a US national sample of patients with COVID-19. JAMA Netw Open. 2020;3(12):e2029058.
Souris M, Gonzalez J-P. COVID-19: spatial analysis of hospital case-fatality rate in France. PLoS One. 2020;15(12):e0243606.
Piroth L, Cottenet J, Mariet AS, Bonniaud P, Blot M, Tubert-Bitter P, et al. Comparison of the characteristics, morbidity, and mortality of COVID-19 and seasonal influenza: a nationwide, population-based retrospective cohort study. Lancet Respir Med. 2021;9(3):251-9. https://doi.org/10.1016/S2213-2600(20)30527-0.
Collaboration NCDRF. Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants. Lancet. 2017;389(10064):37–55.
Danaei G, Finucane MM, Lin JK, Singh GM, Paciorek CJ, Cowan MJ, et al. National, regional, and global trends in systolic blood pressure since 1980: systematic analysis of health examination surveys and epidemiological studies with 786 country-years and 5·4 million participants. Lancet. 2011;377(9765):568–77.
Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223–37.
Mills KT, Bundy JD, Kelly TN, Reed JE, Kearney PM, Reynolds K, et al. Global disparities of hypertension prevalence and control: a systematic analysis of population-based studies from 90 countries. Circulation. 2016;134(6):441–50.
Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005;365(9455):217–23.
Emanuel EJ, Persad G, Upshur R, Thome B, Parker M, Glickman A, et al. Fair allocation of scarce medical resources in the time of Covid-19. N Engl J Med. 2020;382(21):2049–55.
Angkananard T, Anothaisintawee T, McEvoy M, Attia J, Thakkinstian A. Neutrophil lymphocyte ratio and cardiovascular disease risk: a systematic review and meta-analysis. Biomed Res Int. 2018;2018:2703518.
Mertoglu C, Gunay M. Neutrophil-Lymphocyte ratio and Platelet-Lymphocyte ratio as useful predictive markers of prediabetes and diabetes mellitus. Diabetes Metab Syndr Clin Res Rev. 2017;11:S127–S31.
Nwose EU, Richards RS, Jelinek HF, Kerr PG. D-dimer identifies stages in the progression of diabetes mellitus from family history of diabetes to cardiovascular complications. Pathology. 2007;39(2):252–7.
Bisoendial RJ, Boekholdt SM, Vergeer M, Stroes ESG, Kastelein JJP. C-reactive protein is a mediator of cardiovascular disease. Eur Heart J. 2010;31(17):2087–91.
Sanders JM, Monogue ML, Jodlowski TZ, Cutrell JB. Pharmacologic treatments for coronavirus disease 2019 (COVID-19): a review. JAMA. 2020;323(18):1824–36.
Shibata S, Arima H, Asayama K, Hoshide S, Ichihara A, Ishimitsu T, et al. Hypertension and related diseases in the era of COVID-19: a report from the Japanese Society of Hypertension Task Force on COVID-19. Hypertens Res. 2020;43(10):1028–46.
Bourgonje AR, Abdulle AE, Timens W, Hillebrands JL, Navis GJ, Gordijn SJ, et al. Angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 and the pathophysiology of coronavirus disease 2019 (COVID-19). J Pathol. 2020;251(3):228–48.
Galbadage T, Peterson BM, Awada J, Buck AS, Ramirez DA, Wilson J, et al. Systematic review and meta-analysis of sex-specific COVID-19 clinical outcomes. Front Med. 2020;7:348.
Palaiodimos L, Kokkinidis DG, Li W, Karamanis D, Ognibene J, Arora S, et al. Severe obesity, increasing age and male sex are independently associated with worse in-hospital outcomes, and higher in-hospital mortality, in a cohort of patients with COVID-19 in the Bronx, New York. Metabolism. 2020;108:154262.
Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: a systematic literature review and meta-analysis. J Infect. 2020;81(2):e16–25.
Li L-q, Huang T, Wang Y-q, Wang Z-p, Liang Y, Huang T-b, et al. COVID-19 patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol. 2020;92(6):577–83.
Shahid Z, Kalayanamitra R, McClafferty B, Kepko D, Ramgobin D, Patel R, et al. COVID-19 and older adults: what we know. J Am Geriatr Soc. 2020;68(5):926–9.
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(10229):1054–62.
Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA. 2020;323(16):1574–81.
Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239–42.
Zhao Y, Zhao X, Liu Y, Wei Y, Jin G, Shao S, et al. Perceptions, behaviours, barriers and needs of evidence-based medicine in primary care in Beijing: a qualitative study. BMC Fam Pract. 2019;20(1):171.
Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? Lancet. 2020;395(10231):1225–8.
Yue L, Fan X, Peng H. Abilities and barriers to practicing evidence-based nursing for burn specialist nurses. Burns. 2018;44(2):397–404.
This study was funded by the Center for the Development of Interdisciplinary Research in Islamic Sciences and Health Sciences, Tabriz University of Medical Sciences, Tabriz, Iran. The funder had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
Ethics approval and consent to participate
All procedures performed in this study are in accordance with the ethical standards of the institutional and national research committee. Institutional review board (IRB) approval has been obtained from the Research Ethics Committee of Tabriz University of Medical Sciences (ethics code IR.TBZMED.REC.1398.223).
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Khairy, Y., Naghibi, D., Moosavi, A. et al. Prevalence of hypertension and associated risks in hospitalized patients with COVID-19: a meta-analysis of meta-analyses with 1468 studies and 1,281,510 patients. Syst Rev 11, 242 (2022). https://doi.org/10.1186/s13643-022-02111-2
- Comorbid disease
- Risk factor