Indexed in MEDLINE, SCI & KoreaMed
pISSN 1011-8934   eISSN 1598-6357
Open Access, Peer-reviewed, Weekly
    J Korean Med Sci. 2023 Mar 20;38(11):e93. English.
    Published online Mar 08, 2023.
    https://doi.org/10.3346/jkms.2023.38.e93
    © 2023 The Korean Academy of Medical Sciences.
    Original Article

    Comorbidities in the COVID-19 Pandemic: Scopus-Based Bibliometric Analysis

    Yuliya Fedorchenko,1,* and Olena Zimba2,3,4,*
      • 1Department of Pathophysiology, Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine.
      • 2Department of Clinical Rheumatology and Immunology, University Hospital in Krakow, Krakow, Poland.
      • 3National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland.
      • 4Department of Internal Medicine N2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.
    • Address for Correspondence: Yuliya Fedorchenko, MD. Department of Pathophysiology, Ivano-Frankivsk National Medical University, Halytska Str. 2, Ivano-Frankivsk 76018, Ukraine. Email: juliakozubash@gmail.com

      *Yuliya Fedorchenko and Olena Zimba contributed equally to this work.
    Received January 05, 2023; Accepted February 16, 2023.

    This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

    Abstract

    Background

    Comorbidities attract enormous attention amid the coronavirus disease 2019 (COVID-19) pandemic. Mapping knowledge based on these clinical conditions is increasingly important since the pandemic is still raging and primarily affecting subjects with chronic diseases and comorbidities. Clinical presentation and complications of COVID-19 are still hot topics which are explored in numerous evidence-based publications. The aim of this study was to analyze Scopus-indexed COVID-19 papers covering comorbidities.

    Methods

    Searches through the Scopus database were performed on September 19, 2022 using the following keywords: “Diabetes mellitus” OR “Cardiovascular Diseases” OR “Rheumatic Diseases” OR “Obesity” OR “Malignancies” AND “COVID-19.” All retrieved articles were analyzed using the following categories: document type, authorship, keywords, journal, citation score, country of origin, and language. Using the software tool VOSviewer version 1.6.18, we visualized the network of authors and keywords co-occurrence of the most prevalent comorbidities reported in connection with COVID-19.

    Results

    Reports on COVID-19 and diabetes mellitus (DM) were most frequently published (n = 12,282). The US was the most productive country (n = 3,005) in the field of COVID-19 and comorbidities. There were 1,314 documents on COVID-19 and rheumatic diseases which is the least number in comparison with other comorbidities (COVID-19 and DM: 12,282, COVID-19 and cardiovascular disease: 9,911, COVID-19 and obesity: 7,070, and COVID-19 and malignancies: 1,758).

    Conclusion

    This mapping of COVID-19-related documents in connection with comorbidities may prioritize future research directions.

    Keywords
    COVID-19; Comorbidities; Bibliometric Analysis; Scopus

    INTRODUCTION

    The coronavirus disease 2019 (COVID-19) pandemic has enormously affected all spheres of human life and activity. As of September 28, 2022, 621,342,894 COVID-19 cases have been registered worldwide, with a death toll of 6,543,203.1 The USA leads the ranking of countries with the highest number of cases, followed by India and France.1 Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as the most dreadful cytokine-mediated complication of the disease, contributing to high mortality and requiring powerful anti-cytokine therapies.

    Rapid spread of the novel coronavirus and its continuing mutation activity have led to the emergence of new virus strains, requiring new approaches to COVID-19 vaccinations and therapies.2 The complexity of the novel coronavirus and systemic manifestations of the infection have all been reflected in diverse fundamental and clinical research directions.3 The deluge of COVID-19 reports and uncontrolled flow of related public discussions on open communication channels have created a new challenge for the global community–misinformation.4

    One of the most debated and variably interpreted topics relates to comorbidities which confound COVID-19 course and exaggerate healthcare burden in the pandemic.5 Subjects with chronic comorbid conditions and exhausted immune responses are often more severely affected by the novel coronavirus than those without the burden of background clinical conditions.6 Despite the availability of numerous reports on comorbidities in COVID-19, questions of combined therapies, continuing clinical monitoring, and prevention of associated complications still remain unanswered.7, 8, 9

    This bibliometric study is a snapshot Scopus-based analysis that aims to map publication activity and research directions in the field of COVID-19 and comorbidities. This is an attempt to explore scientific facts and perspectives on pathogenesis, clinical course, and outcomes of COVID-19 in subjects with the burden of common chronic background diseases.

    METHODS

    Searches through the Scopus database were employed on September 24, 2022 in line with previously published recommendations on comprehensive literature coverage.10 The following Medical Subject Heading (MeSH) keywords were used to retrieve and analyze tagged titles, abstracts, and keywords: “diabetes mellitus,” “cardiovascular diseases,” “rheumatic diseases,” “obesity,” “malignancies,” and “COVID-19.”

    We used the Scopus database as the largest platform of peer-reviewed literature. Its user-friendly analytical tools allow visualizing the scientific context of big data.11 In the current study, the retrieved records were analyzed in view of their document type, authorship, source, citations, scientific area, country of origin, and indexed keywords. We retrieved and analyzed English only articles, most of which are openly accessible. All retrieved original articles, reviews, case reports, case series, letters, editorials, notes, errata on COVID-19 and accompanying pathologies and reports of pathogenic links between SARS-CoV-2 infection and other pathologies were covered. Conference papers, short surveys, and book chapters were excluded from analyses.

    Currently available network visualization tools are widely used to reveal the most active (hot) topics in established and emerging scientific directions. As such, we have explored keywords and authors co-occurrence using the VOSviewer software (version 1.6.18). Related visualizations are depicted in Fig. 1. Nodes represent authors or keywords while lines convey interaction between them. Node size expresses the frequency of occurrence. Coloring helps to distinguish separate groups with stronger or weaker interactions. To make conceptualization more concise and transparent, we used a limited number of keywords and authors to convey the most representative ones (the minimum number for keyword occurrence is set at 10 and for authors occurrence—at 5).

    Fig. 1
    Depiction of interplay between COVID-19 and comorbid diseases. (A-E) Visualization of authors' network (1) and keywords' network (2) in COVID-19 and DM (A1, A2), COVID-19 and CVD (B1, B2), COVID-19 and RD (C1, C2), COVID-19 and obesity (D1, D2), and COVID-19 and malignancies.
    COVID-19 = coronavirus disease 2019, DM = diabetes mellitus, CVD = cardiovascular disease, RD = rheumatic disease.

    RESULTS

    COVID-19 and diabetes mellitus (DM)

    Top 5 journals in the field of COVID-19 and Diabetes Mellitus were Diabetes Metab Syndr Clin Res Rev (n = 203), PLOS One (n = 200), Diabetes Res Clin Pract (n =165), J Clin Med (n = 152), and J Med Virol (n = 129).

    Top 5 countries with high publication activity were the USA (n = 3,005), the UK (n = 1,152), India (n = 1,110), Italy (n = 1,108), and China (n = 1,036).

    Original articles (n = 8,247, 70.7%) were the most common documents followed by reviews (13.1%), letters (10.1%), notes (3.5%), editorials (2.5%), and errata (0.1%).

    Top 5 authors in this field were the following scholars: Khunti, K (n = 45), Misra, A (n = 39), Pal, R (n = 27), Pranata, R (n = 26), and Cariou, B (n = 19).

    The co-occurrence keywords network visualization map in COVID-19 and DM was presented in Fig. 1 A2 and can be summarized into categories representing 4 research scopes. The most frequently seen keywords are following: “Human” (n = 13,665), “Coronavirus Disease 2019” (n = 12,475), “COVID-19” (n = 11,299), “Diabetes Mellitus” (n = 10,555), “Humans” (n = 9,411), “Article” (n = 9,121), Male (n = 8,604), Female (n = 8,513), “Adult” (n = 8,081), and “Hypertension” (n = 7,290).

    COVID-19 and cardiovascular diseases (CVDs)

    Top 5 journals in the field of COVID-19 and CVDs were J Clin Med (n = 134), Int J Environ Res Public Health (n = 114), PLOS One (n = 107), Front Immunol (n = 99), and Eur Heart J (n = 80).

    Top 5 countries were the USA (n = 2,626), Italy (n = 1,308), the UK (n = 1,015), China (n = 875), and India (n = 582).

    Original articles (58.5%) were the most frequent documents followed by reviews (25.7%), letters (8%), editorials (4.3%), notes (3.3%), and errata (0.2%).

    Top 5 authors in this field were Harky, A (n = 22), Banerjee, A (n = 20), Khunti, K (n = 19), Metra, M (n = 19), and Lavie, C (n = 18).

    The co-occurrence keywords network visualization map in COVID-19 and CVDs were presented in Fig. 1 B2 and can be summarized into 4 clusters with different colors (red, green, blue, and yellow).

    The most frequently seen keywords are the following: “Human” (n = 3,152), “Coronavirus Disease 2019” (n = 12,475), “COVID-19” (n = 3,035), “Coronavirus Disease 2019” (n = 2,573), “Humans” (n = 2,151), “Article” (n = 1,858), “Cardiovascular Disease” (n = 1,693), “Male” (n = 1,645), “Female” (n = 1,604), “Adult” (n = 1,476), “SARS-CoV-2” (n = 1,472), and “Major Clinical Study” (n = 1,052).

    COVID-19 and rheumatic diseases (RDs)

    Top 5 journals in the field of COVID-19 and RDs were Ann Rheum Dis (n = 157), Rheumatol Int (n = 61), Clin Rheumatol (n = 57), Lancet Rheumatol (n = 53), and RMD Open (n = 32).

    Top 5 countries were the USA (n = 288), Italy (n = 190), the UK (n = 158), Germany (n = 110), and France (n = 99).

    Original articles were the most frequent documents (n = 648, 55.3%) followed by reviews (18.9%), letters (16.5%), notes (4.9%), editorials (3.4%), and errata (1%).

    Top 5 authors were Robinson, PC (n = 37), Wallace, ZC (n = 33), Sparks, JA (n = 33), Yazdany, J (n = 33), and Schulze-Koops, H (n = 24).

    The co-occurrence keywords network visualization map in COVID-19 and RDs were presented in Fig. 1 C2 and can be summarized into 5 clusters with different colors (red, green, blue, yellow, and violet).

    The most frequently seen keywords are the following: “Human” (n = 494), “COVID-19” (n = 459), “Coronavirus Disease 2019” (n = 384), “Rheumatic Disease” (n = 354), “Humans” (n = 351), “Female” (n = 305), “Article” (n = 289), “Male” (n = 285), “Adult” (n = 276), and “SARS-CoV-2” (n = 255).

    COVID-19 and obesity

    Top 5 journals in the field of COVID-19 and obesity were Nutrients (n = 137), Int J Environ Res Public Health (n = 113), PLOS One (n = 110), Obesity (n = 95), and Obes Surg (n = 94).

    Top 5 countries were the USA (n = 2,151), Italy (n = 761), the UK (n = 714), Spain (n = 445), and France (n = 403).

    Original articles were the most frequent documents (n = 4,445, 67%) followed by reviews (17%), letters (9.3%), notes (3.3%), editorials (3%), and errata (0.4%).

    Top 5 authors in this field were Khunti, K (n = 19), Lavie, CJ (n = 17), Mahawar, K (n = 14), Arena, R (n = 13), Giustina, A (n = 13).

    The co-occurrence keywords network visualization map in COVID-19 and obesity were presented in Fig. 1 D2 and can be summarized into 5 clusters with different colors (red, green, blue, yellow, and violet).

    The most frequently seen keywords are the following: “Human” (n = 2,541), “COVID-19” (n = 2,468), “Obesity” (n = 2,246), “Coronavirus Disease 2019” (n = 2,067), “Humans” (n = 1,806), “Article” (n = 1,667), “Female” (n = 1,621), “Male” (n = 1,537), “Adult” (n = 1,481), and “SARS-CoV-2” (n = 1,293).

    COVID-19 and malignancies

    Top 5 journals in the field of COVID-19 and malignancies were Cancers (n = 29), Front Oncol (n = 29), Br J Haematol (n = 26), Eur J Cancer (n = 25), and Cancer Cell (n = 20).

    Top 5 countries were the USA (n = 468), Italy (n = 221), the UK (n = 181), India (n = 127), and China (n = 111).

    Original articles were the most frequent documents (70.8%) followed by reviews (17.2%), letters (8.4%), notes (2.2%), editorials (1.2%), and errata (0.2%).

    Top 5 authors were Halmos, B (n = 12), Van Hemelrijck, M (n = 12), Bruna, R (n = 11), Corradini, P (n = 11), and Passamonti, F (n = 11).

    The co-occurrence keywords network visualization map in COVID-19 and malignancies were presented in Fig. 1 E2 and can be summarized into 5 clusters with different colors (red, green, blue, yellow, and violet).

    The most frequently seen keywords are the following: “Human” (n = 719), “COVID-19” (n = 692), “Coronavirus Disease 2019” (n = 599), “Humans” (n = 536), “Article” (n = 465), “SARS-CoV-2” (n = 426), “Female” (n = 416), “Male” (n = 406), “Adult” (n = 389), and “Hematologic Malignancy” (n = 319).

    DISCUSSION

    Patients with chronic health conditions comprise a vulnerable group for adverse clinical outcomes in SARS-CoV-2 infection.8 A retrospective, multicenter cohort study (n = 191) reported that about 48% of COVID-19 patients had comorbidities, including arterial hypertension (n = 58, 3%), DM (n = 36, 2%), and coronary heart diseases (CHDs) (n = 15, 8%).9 COVID-19 seems to be more frequent among older men with accompanying diseases, resulting in complicated or fatal outcomes.12

    Examining the influence of comorbidities on the course and consequences of COVID-19 is crucially important.

    Knowledge of pathogenic mechanisms of SARS-CoV-2 infection in subjects with comorbid pathologies would be helpful for risk stratification, organization of health services, and personalization of the services.

    The most common clinical findings typically encountered in COVID patients with comorbidities are shown in Table 1.

    Table 1
    Peculiarities of comorbidities in COVID-19

    COVID-19 and DM

    Compared to other comorbidities, subjects with DM seem to be at a greater risk of severe COVID-19.13 Hyperglycemia with hemoglobin glycosylation may trigger the overly production of pro-inflammatory cytokines, oxygen radicals, underlying severe COVID-19 in DM.14 The resultant inflammatory response increases the invading potential of infectious agents and exhausts the immune system. Thus, tight blood glucose monitoring is a prerequisite for treating COVID-19 in subjects with new-onset DM.15

    A retrospective study analyzed the course of SARS-CoV-2 in new-onset DM compared to the same in preexisting DM.16 Notably, new-onset DM presented with a more pronounced hyperglycemia at the beginning of COVID-19 and more frequently progressed into life-threatening conditions at the hospital admission.16 It is believed that hypoglycemic medications, such as glucagon-like peptide-1 agonists, thiazolidinediones, and sodium-glucose co-transporter-2 inhibitors, stimulate angiotensin-converting enzyme 2 (ACE-2) receptor overexpression, enabling SARS-CoV-2 entry into the host cells.17, 18 Overall, insulin-dependent conditions increase the risk of COVID-19 pneumonia compared to conditions treatable with oral antidiabetic agents.19

    Another challenging factor is the combination of DM with arterial hypertension which adds to ACE-2 overexpression.20 Chronic subclinical inflammation in DM is yet another aggravating factor presenting with elevated neutrophil and lowered lymphocyte counts and contributing to cytokine storm syndromes.15, 21 COVID-19 in patients with DM often presents with high proinflammatory markers, including lactate dehydrogenase, C-reactive protein (CRP), ferritin, and D-dimer.15, 21 Clinical characteristics of COVID-19 and DM combination include high chest computer tomography scores suggestive of severe lung involvement.21 Finally, exposure to the infection in DM rarely stimulates production of anti-SARS-CoV-2 antibodies, predisposing these individuals to reinfections.

    COVID-19 and CVDs

    The association of SARS-CoV-2 with CVDs is well-established.22, 23 Subjects with severe COVID-19 had higher incidence of arterial hypertension than those with non-severe COVID-19.22 A meta-analysis revealed that the most common comorbid pathologies in COVID-19 were arterial hypertension (17%), cardiac and cerebrovascular diseases (16%), and DM (10%).22 Chen et al.12 reported that approximately 40% of patients infected with SARS-CoV-2 experience CVD or cerebrovascular disease. Cardiac magnetic resonance imaging in subjects who recently recovered from COVID-19 diagnosed new cardiac involvement in 78% of cases and myocardial inflammation in 60% of cases.24

    SARS-CoV-2 infection may trigger new cardiac pathologies and/or exacerbate underlying CVD.25 It may directly and indirectly damage heart and vessels, presenting with acute coronary syndromes, cardiomyopathy, arrhythmias, and cardiogenic shock.26

    Older age, DM, hyperlipidemia, and overexpression of ACE2 may confound severe COVID-19 in patients with CVD.3, 26, 27 Viral dissemination from the respiratory tract to the blood stream may also act as a severity factor.28

    Atrial and ventricular fibrillation, cardiac failure, myocarditis, and pulmonary embolic event have often been reported in COVID-19.29, 30 Accordingly, high-sensitivity cardiac troponin I (hs-cTnI), creatine kinase, N-terminal pro-brain natriuretic peptide (NT-proBNP), and D-dimer should be monitored in severe COVID-19 to timely diagnose cardiac damage.31

    In a recent study, patients with increased troponin T (TnT) at hospitalization due to COVID-19 had poor clinical outcomes; they particularly developed malignant arrhythmias.23 The National Health Commission of China reported that about 12% of individuals with SARS-CoV-2 without established CVD were hospitalized with elevated TnT and cardiac arrest.32 More than half of COVID-19 patients with lethal outcomes also had high hs-cTnI at hospital admission.9

    Arterial and venous thromboembolic events are frequent in COVID-19 during the initial 24 hours of hospital admission.33 The increased number of positive venous thromboembolic imaging tests in COVID-19 warrants monitoring of related risk factors in ambulatory patients.33

    COVID-19 and RDs

    SARS-CoV-2 triggers of Toll-like receptors and complement activation with formation of neutrophilic extracellular traps. All these factors may induce systemic autoimmune reactions in COVID-19.34 In fact, rheumatic patients infected with SARS-CoV-2 are likely to develop generalized microvascular thromboses mediated by complement activation, with a marked elevation of D-dimer.35

    At the beginning of the COVID-19 pandemic, the European Alliance of Associations for Rheumatology (EULAR) reported no evidence of heightened risk of SARS-CoV-2 infection and severe COVID-19 in subjects with inflammatory rheumatic and musculoskeletal diseases.36 However, a survey of 494 RA patients revealed that 40% of them believed that the rheumatic disease and its treatment put them at risk of unfavorable course of COVID-19.37

    Although subjects with RDs presented with the same clinical picture of COVID-19 as those without RDs, they often required mechanical ventilation (adjusted odds ratio [OR], 3.11).38 Increased age (OR, 4.83) and male gender (OR, 1.93) were independently associated with severe COVID-19 in patients with chronic inflammatory arthritis and connective tissue diseases compared to non-rheumatic controls.39

    In the time of the pandemic, subjects with RDs have experienced unjustified discontinuation of disease-modifying antirheumatic drug (DMARD) therapies due to the short supply of hydroxychloroquine (HCQ) and tocilizumab.40 A multi-center patient survey revealed that 42% of respondents had difficulties with obtaining HCQ and 41% of them experienced worsened disease course due to the DMARDs shortage.41

    The efficacy of HCQ has raised numerous questions and concerns during the COVID-19 pandemic.42 Arshad et al.43 reported that the therapy with HCQ alone or combined with azithromycin significantly reduced COVID-19 mortality rates. However, Pham et al.44 stated there were no statistical differences in mechanical ventilation between subjects with RDs who were treated with HCQ compared to those who were not treated with HCQ (OR, 1.5; 95% confidence interval [CI], 0.3–6.3). Similar results were reported in relation to in-hospital mortality (OR, 0.8; 95% CI, 0.1–4.6).44

    Many other treatment strategies have been tried for SARS-CoV-2. The anti-inflammatory and immunomodulatory properties of glucocorticoids have been well explored.45 In multivariable models, prednisone dose ≥ 10 mg/day was associated with frequent hospital admissions (OR, 2.0; 95% CI, 1.1–4.0).46 Meanwhile, treating with conventional DMARDs alone or combined with biologics/Janus Kinase inhibitors was not linked to hospital admission (OR, 1.2; 95% CI, 0.7–2.2 and OR, 0.7; 95% CI, 0.4–1.5, respectively).46

    Overall, in the wake of the COVID-19 pandemic, patients with RDs on long-term corticosteroid therapy were advised to continuing immunosuppressive therapy and to gradually lowering corticosteroid doses to 5–7.5 mg/daily.47

    COVID-19 and neoplasms

    Numerous studies have revealed that COVID-19 patients with preexisting or active malignancy are at a greater risk of severe disease and even death.48, 49, 50, 51, 52 Higher mortality rates (OR, 2.3; 95% CI, 1.2–4.8) and higher rates of intensive care unit (ICU) admission (OR, 2.8; 95% CI, 1.6–5.1) were reported in COVID-19 subjects with malignancies.49

    Logistic regression analyses have showed that several factors were associated with increased 30-day COVID-19-related mortality: older age, male gender, smoking, and active cancer.53 Some studies have determined risk factors of COVID-19 severity in subjects with malignancy.54, 55 A multicentre, retrospective cohort study reported that advanced cancer stage (OR, 2.6; 95% CI, 1.1–6.4), high levels of tumour necrosis factor-α (OR, 1.2; 95% CI, 1.0–1.5), elevated NT-proBNP (OR, 1.7; 95% CI, 1.03–2.8), reduced CD4+ T cells (OR, 0.8; 95% CI, 0.7–0.9), and reduced albumin–globulin ratio (OR, 0.1; 95% CI, 0.02–0.8) were all distinguished as severe disease factors.54 In a global database (TERAVOLT) older age (above 65) (OR, 1.9; 95% CI, 1.0–3.6), smoking (OR, 4.2; 95% CI, 1.7–12.9), and chemotherapy (OR, 2.5; 95% CI, 1.1–6.1) were also associated with risk of death in COVID-19 patients with cancer.55 There were no differences in COVID-19 mortality rates between subjects with active and inactive cancer treatments.56

    COVID-19 patients with cancer were at risk of death due to delays in diagnosis and required therapies.57 There was about 10% higher risk of death in patients with breast malignancies during the pandemic compared to pre-pandemic period.57

    COVID-19 severity differed widely across different cancers. Subjects with leukemia, lymphoma, and myeloma experienced more severe COVID-19 than those with solid cancer (OR, 1.6; 95% CI, 1.2–2.2).58 Case fatality rate for cohorts with cancer who died due to COVID-19 was about 37% for hematologic malignancies and 25% for solid cancers.59

    Patients with cancer were susceptible to infections of the respiratory tract due to cancer-related immunosuppression, requiring more cautious approaches to immunosuppression therapies to mitigate risks of more severe outcomes.60

    COVID-19 and obesity

    Preliminary data suggest subjects with obesity experience more severe COVID-19.61, 62 Obesity has been reported as the second most common comorbidity in case series of COVID-19.7 Cai et al.61 reported that obese subjects often develop severe COVID-19 compared to those with normal weight (OR, 3.4; 95% CI, 1.4–2.9). Although COVID-19 pandemic generally led to the rise in body mass index (BMI) z-score (OR, 2.5; 95% CI, 2.0–2.9) to (OR, 2.6; 95% CI, 2.0–3.2) in children and adolescents with obesity,63 obese children presented with severe clinical course during the delta predominance (adjusted OR, 6.1; 95% CI, 1.2–29.6).64

    Obese people demonstrate reduced pulmonary compliance and chest wall compliance due to high pulmonary blood volume.65 Fat accumulation in the diaphragm and abdomen facilitates viral entry due to activated ACE-2 receptors, increases viral load, and stimulates proinflammatory cytokines efflux with low-grade inflammatory response.66 The proinflammatory state may deteriorate pro- and anticoagulant dysbalance and lead to thromboses.67 Additionally, high plasma leptin levels in obesity may contribute to severe COVID-19. In fact, circulating levels of leptin, tumor necrosis factor-α, C-X-C motif chemokine ligand 10, and monocyte chemoattractant protein-4 were all significantly associated with severe COVID-19 compared to healthy controls.62

    Obese patients with COVID-19 are at higher risk of hospitalization, ICU admission, and death.68 The need for invasive mechanical ventilation (IMV) increases with BMI.69 COVID-19 patients with BMI > 35 admitted to ICU have a 7-fold higher risk of IMV than those with BMI < 25.69 Patients below 60 years with BMI 30–34 were two times more likely to be hospitalized and admitted to ICU, compared to individuals with BMI < 30.70 Generally, age, gender, BMI ≥ 35 and smoking status predict oxygenation therapy.71

    Our bibliometric analysis has several limitations. We searched through the Scopus database only and the articles in language other than English were filtered out and not included in the study. We also focused on few comorbidities. Nevertheless, we managed to emphasize the need for personalized data on risk factors, clinical course, possible complications, and outcomes of COVID-19.

    In conclusion, comorbidities are typical in COVID-19 patients putting them at greater risk of adverse outcomes. Bibliometric analyses summarize available data and highlight directions of future research. Studies on specific types of chronic comorbidities need to be conducted. High priority should be placed on future studies of cohorts with comorbidities to provide specified clinical management.

    Notes

    Disclosure:The authors have no potential conflicts of interest to disclose.

    Author Contributions:

    • Conceptualization: Fedorchenko Yu.

    • Formal analysis: Fedorchenko Yu, Zimba O.

    • Writing - original draft: Fedorchenko Yu.

    • Writing - review & editing: Fedorchenko Yu, Zimba O.

    References

      1. Worldometer. COVID Live - coronavirus statistics. [Updated 2023]. [Accessed September 28, 2022].
        https://www.worldometers.info/coronavirus/#countries.
      1. Harvey WT, Carabelli AM, Jackson B, Gupta RK, Thomson EC, Harrison EM, et al. SARS-CoV-2 variants, spike mutations and immune escape. Nat Rev Microbiol 2021;19(7):409–424.
      1. Wang R, Chen J, Gao K, Wei GW. Vaccine-escape and fast-growing mutations in the United Kingdom, the United States, Singapore, Spain, India, and other COVID-19-devastated countries. Genomics 2021;113(4):2158–2170.
      1. Gupta L, Gasparyan AY, Misra DP, Agarwal V, Zimba O, Yessirkepov M. Information and misinformation on COVID-19: a cross-sectional survey study. J Korean Med Sci 2020;35(27):e256
      1. Ahmed S, Gasparyan AY, Zimba O. Comorbidities in rheumatic diseases need special consideration during the COVID-19 pandemic. Rheumatol Int 2021;41(2):243–256.
      1. 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;94:91–95.
      1. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York city area. JAMA 2020;323(20):2052–2059.
      1. Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020;55(5):2000547
      1. 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):1054–1062.
      1. Gasparyan AY, Ayvazyan L, Blackmore H, Kitas GD. Writing a narrative biomedical review: considerations for authors, peer reviewers, and editors. Rheumatol Int 2011;31(11):1409–1417.
      1. AlRyalat SA, Malkawi LW, Momani SM. Comparing bibliometric analysis using PubMed, Scopus, and Web of Science databases. J Vis Exp. 2019;(152)
      1. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507–513.
      1. Gęca T, Wojtowicz K, Guzik P, Góra T. Increased risk of COVID-19 in patients with diabetes mellitus-current challenges in pathophysiology, treatment and prevention. Int J Environ Res Public Health 2022;19(11):6555.
      1. Petrie JR, Guzik TJ, Touyz RM. Diabetes, hypertension, and cardiovascular disease: clinical insights and vascular mechanisms. Can J Cardiol 2018;34(5):575–584.
      1. Zhu L, She ZG, Cheng X, Qin JJ, Zhang XJ, Cai J, et al. Association of blood glucose control and outcomes in patients with COVID-19 and pre-existing type 2 diabetes. Cell Metab 2020;31(6):1068–1077.e3.
      1. Uchihara M, Bouchi R, Kodani N, Saito S, Miyazato Y, Umamoto K, et al. Impact of newly diagnosed diabetes on coronavirus disease 2019 severity and hyperglycemia. J Diabetes Investig 2022;13(6):1086–1093.
      1. Filippatos TD, Liontos A, Papakitsou I, Elisaf MS. SGLT2 inhibitors and cardioprotection: a matter of debate and multiple hypotheses. Postgrad Med 2019;131(2):82–88.
      1. Bornstein SR, Rubino F, Khunti K, Mingrone G, Hopkins D, Birkenfeld AL, et al. Practical recommendations for the management of diabetes in patients with COVID-19. Lancet Diabetes Endocrinol 2020;8(6):546–550.
      1. Assaad M, Hekmat-Joo N, Hosry J, Kassem A, Itani A, Dahabra L, et al. Insulin use in type II diabetic patients: a predictive of mortality in covid-19 infection. Diabetol Metab Syndr 2022;14(1):85.
      1. Esler M, Esler D. Can angiotensin receptor-blocking drugs perhaps be harmful in the COVID-19 pandemic? J Hypertens 2020;38(5):781–782.
      1. Guo W, Li M, Dong Y, Zhou H, Zhang Z, Tian C, et al. Diabetes is a risk factor for the progression and prognosis of COVID-19. Diabetes Metab Res Rev 2020;36(7):e3319
      1. 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):531–538.
      1. Guo T, Fan Y, Chen M, Wu X, Zhang L, He T, et al. Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19). JAMA Cardiol 2020;5(7):811–818.
      1. Puntmann VO, Carerj ML, Wieters I, Fahim M, Arendt C, Hoffmann J, et al. Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from coronavirus disease 2019 (COVID-19). JAMA Cardiol 2020;5(11):1265–1273.
      1. Madjid M, Safavi-Naeini P, Solomon SD, Vardeny O. Potential effects of coronaviruses on the cardiovascular system: a review. JAMA Cardiol 2020;5(7):831–840.
      1. Gupta A, Madhavan MV, Sehgal K, Nair N, Mahajan S, Sehrawat TS, et al. Extrapulmonary manifestations of COVID-19. Nat Med 2020;26(7):1017–1032.
      1. Gallagher PE, Ferrario CM, Tallant EA. Regulation of ACE2 in cardiac myocytes and fibroblasts. Am J Physiol Heart Circ Physiol 2008;295(6):H2373–H2379.
      1. Inciardi RM, Lupi L, Zaccone G, Italia L, Raffo M, Tomasoni D, et al. Cardiac involvement in a patient with coronavirus disease 2019 (COVID-19). JAMA Cardiol 2020;5(7):819–824.
      1. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, et al. Association of cardiac injury with mortality in hospitalized patients with COVID-19 in Wuhan, China. JAMA Cardiol 2020;5(7):802–810.
      1. Poissy J, Goutay J, Caplan M, Parmentier E, Duburcq T, Lassalle F, et al. Pulmonary embolism in patients with COVID-19: awareness of an increased prevalence. Circulation 2020;142(2):184–186.
      1. Guzik TJ, Mohiddin SA, Dimarco A, Patel V, Savvatis K, Marelli-Berg FM, et al. COVID-19 and the cardiovascular system: implications for risk assessment, diagnosis, and treatment options. Cardiovasc Res 2020;116(10):1666–1687.
      1. Zheng YY, Ma YT, Zhang JY, Xie X. COVID-19 and the cardiovascular system. Nat Rev Cardiol 2020;17(5):259–260.
      1. Lodigiani C, Iapichino G, Carenzo L, Cecconi M, Ferrazzi P, Sebastian T, et al. Venous and arterial thromboembolic complications in COVID-19 patients admitted to an academic hospital in Milan, Italy. Thromb Res 2020;191:9–14.
      1. Ahmed S, Zimba O, Gasparyan AY. COVID-19 and the clinical course of rheumatic manifestations. Clin Rheumatol 2021;40(7):2611–2619.
      1. Magro C, Mulvey JJ, Berlin D, Nuovo G, Salvatore S, Harp J, et al. Complement associated microvascular injury and thrombosis in the pathogenesis of severe COVID-19 infection: a report of five cases. Transl Res 2020;220:1–13.
      1. Landewé RB, Machado PM, Kroon F, Bijlsma HW, Burmester GR, Carmona L, et al. EULAR provisional recommendations for the management of rheumatic and musculoskeletal diseases in the context of SARS-CoV-2. Ann Rheum Dis 2020;79(7):851–858.
      1. Cook C, Cox H, Fu X, Zhang Y, Stone JH, Choi HK, et al. Perceived risk and associated shielding behaviors in patients with rheumatoid arthritis during the coronavirus 2019 pandemic. ACR Open Rheumatol 2021;3(12):834–841.
      1. D’Silva KM, Serling-Boyd N, Wallwork R, Hsu T, Fu X, Gravallese EM, et al. Clinical characteristics and outcomes of patients with coronavirus disease 2019 (COVID-19) and rheumatic disease: a comparative cohort study from a US ‘hot spot’. Ann Rheum Dis 2020;79(9):1156–1162.
      1. Pablos JL, Galindo M, Carmona L, Lledó A, Retuerto M, Blanco R, et al. Clinical outcomes of hospitalised patients with COVID-19 and chronic inflammatory and autoimmune rheumatic diseases: a multicentric matched cohort study. Ann Rheum Dis 2020;79(12):1544–1549.
      1. Puxeddu I, Ferro F, Bartoloni E, Elefante E, Baldini C, Scirè CA, et al. COVID-19: the new challenge for rheumatologists. One year later. Clin Exp Rheumatol 2021;39(1):203–213.
      1. Abualfadl E, Ismail F, Shereef RRE, Hassan E, Tharwat S, Mohamed EF, et al. Impact of COVID-19 pandemic on rheumatoid arthritis from a multi-centre patient-reported questionnaire survey: influence of gender, rural-urban gap and north-south gradient. Rheumatol Int 2021;41(2):345–353.
      1. Meo SA, Klonoff DC, Akram J. Efficacy of chloroquine and hydroxychloroquine in the treatment of COVID-19. Eur Rev Med Pharmacol Sci 2020;24(8):4539–4547.
      1. Arshad S, Kilgore P, Chaudhry ZS, Jacobsen G, Wang DD, Huitsing K, et al. Treatment with hydroxychloroquine, azithromycin, and combination in patients hospitalized with COVID-19. Int J Infect Dis 2020;97:396–403.
      1. Pham K, Torres H, Satlin MJ, Goyal P, Gulick RM. Failure of chronic hydroxychloroquine in preventing severe complications of COVID-19 in patients with rheumatic diseases. Rheumatol Adv Pract 2021;5(1):rkab014
      1. Rhen T, Cidlowski JA. Antiinflammatory action of glucocorticoids--new mechanisms for old drugs. N Engl J Med 2005;353(16):1711–1723.
      1. Gianfrancesco M, Hyrich KL, Al-Adely S, Carmona L, Danila MI, Gossec L, et al. Characteristics associated with hospitalisation for COVID-19 in people with rheumatic disease: data from the COVID-19 Global Rheumatology Alliance physician-reported registry. Ann Rheum Dis 2020;79(7):859–866.
      1. Misra DP, Agarwal V, Gasparyan AY, Zimba O. Rheumatologists’ perspective on coronavirus disease 19 (COVID-19) and potential therapeutic targets. Clin Rheumatol 2020;39(7):2055–2062.
      1. Liang W, Guan W, Chen R, Wang W, Li J, Xu K, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol 2020;21(3):335–337.
      1. Dai M, Liu D, Liu M, Zhou F, Li G, Chen Z, et al. Patients with cancer appear more vulnerable to SARS-CoV-2: a multicenter study during the COVID-19 outbreak. Cancer Discov 2020;10(6):783–791.
      1. New York State Department of Health. COVID-19 tracker. [Updated 2020]. [Accessed May 21, 2020].
        https://covid19tracker.health.ny.gov/views/NYS-COVID19-Tracker/NYSDOHCOVID-19Tracker-Map.
      1. World Health Organization (WHO). Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Geneva, Switzerland: World Health Organization; 2020.
      1. Robilotti EV, Babady NE, Mead PA, Rolling T, Perez-Johnston R, Bernardes M, et al. Determinants of COVID-19 disease severity in patients with cancer. Nat Med 2020;26(8):1218–1223.
      1. Kuderer NM, Choueiri TK, Shah DP, Shyr Y, Rubinstein SM, Rivera DR, et al. Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study. Lancet 2020;395(10241):1907–1918.
      1. Tian J, Yuan X, Xiao J, Zhong Q, Yang C, Liu B, et al. Clinical characteristics and risk factors associated with COVID-19 disease severity in patients with cancer in Wuhan, China: a multicentre, retrospective, cohort study. Lancet Oncol 2020;21(7):893–903.
      1. Garassino MC, Whisenant JG, Huang LC, Trama A, Torri V, Agustoni F, et al. COVID-19 in patients with thoracic malignancies (TERAVOLT): first results of an international, registry-based, cohort study. Lancet Oncol 2020;21(7):914–922.
      1. Lee LY, Cazier JB, Angelis V, Arnold R, Bisht V, Campton NA, et al. COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study. Lancet 2020;395(10241):1919–1926.
      1. Maringe C, Spicer J, Morris M, Purushotham A, Nolte E, Sullivan R, et al. The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study. Lancet Oncol 2020;21(8):1023–1034.
      1. Lee LYW, Cazier JB, Starkey T, Briggs SEW, Arnold R, Bisht V, et al. COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study. Lancet Oncol 2020;21(10):1309–1316.
      1. Mehta V, Goel S, Kabarriti R, Cole D, Goldfinger M, Acuna-Villaorduna A, et al. Case fatality rate of cancer patients with COVID-19 in a New York Hospital System. Cancer Discov 2020;10(7):935–941.
      1. Zhang L, Zhu F, Xie L, Wang C, Wang J, Chen R, et al. Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China. Ann Oncol 2020;31(7):894–901.
      1. Cai Q, Chen F, Wang T, Luo F, Liu X, Wu Q, et al. Obesity and COVID-19 severity in a designated hospital in Shenzhen, China. Diabetes Care 2020;43(7):1392–1398.
      1. Wang J, Xu Y, Zhang X, Wang S, Peng Z, Guo J, et al. Leptin correlates with monocytes activation and severe condition in COVID-19 patients. J Leukoc Biol 2021;110(1):9–20.
      1. Woo S, Yang H, Kim Y, Lim H, Song HJ, Park KH. Sedentary time and fast-food consumption associated with weight gain during COVID-19 lockdown in children and adolescents with overweight or obesity. J Korean Med Sci 2022;37(12):e103
      1. Choi YY, Choi SH, Choi JH, Kim DH, Lee JK, Eun BW, et al. SARS-CoV-2-naïve Korean children and adolescents hospitalized with COVID-19 in 2021. J Korean Med Sci 2022;37(42):e303
      1. Parameswaran K, Todd DC, Soth M. Altered respiratory physiology in obesity. Can Respir J 2006;13(4):203–210.
      1. Dicker D, Bettini S, Farpour-Lambert N, Frühbeck G, Golan R, Goossens G, et al. Obesity and COVID-19: the two sides of the coin. Obes Facts 2020;13(4):430–438.
      1. Korakas E, Ikonomidis I, Kousathana F, Balampanis K, Kountouri A, Raptis A, et al. Obesity and COVID-19: immune and metabolic derangement as a possible link to adverse clinical outcomes. Am J Physiol Endocrinol Metab 2020;319(1):E105–E109.
      1. Popkin BM, Du S, Green WD, Beck MA, Algaith T, Herbst CH, et al. Individuals with obesity and COVID-19: a global perspective on the epidemiology and biological relationships. Obes Rev 2020;21(11):e13128
      1. Simonnet A, Chetboun M, Poissy J, Raverdy V, Noulette J, Duhamel A, et al. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesity (Silver Spring) 2020;28(7):1195–1199.
      1. Lighter J, Phillips M, Hochman S, Sterling S, Johnson D, Francois F, et al. Obesity in patients younger than 60 years is a risk factor for COVID-19 hospital admission. Clin Infect Dis 2020;71(15):896–897.
      1. 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
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    Bibliometrics*
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    Cardiovascular Diseases
    Chronic Disease
    Diabetes Mellitus
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    Obesity
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